INVITED PAPER Practical Issues for Spectrum Management With Cognitive Radios This paper discusses some of the practical spectrum management issues that impact the adoption of cognitive radio technology.

By Stephen M. Dudley, Member IEEE, William Christopher Headley, Marc Lichtman, Student Member IEEE, Eyosias Yoseph Imana, Xiaofu Ma, Student Member IEEE, Mahi Abdelbar, Aditya Padaki, Student Member IEEE, Abid Ullah, Munawwar M. Sohul, Taeyoung Yang, Member IEEE,and Jeffrey H. Reed, Fellow IEEE

ABSTRACT | The policy of permanently assigning a frequency ASA Authorized shared access. band to a single application has led to extremely low utilization AWGN Additive white Gaussian noise. of the available spectrum. Cognitive radio, with its ability to be BRAN Broadband radio access network. both intelligent and frequency agile, is thought to be one of the CDBS Consolidated database system (FCC). prime contenders to provide the necessary capabilities needed CEPT Conference of Postal and for dynamic spectrum access systems. With this in mind, this Administrations (European). paper discusses the practical issues inherent to the deployment CR Cognitive radio. of spectrum management systems utilizing cognitive radios. DAC Digital-to-analog convertor. DSA Dynamic spectrum access. KEYWORDS | Cognitive radio; communication system security; EC European Commission. intelligent systems; management; ETSI European Telecommunications Standards communication; wireless networks Institute. EU European Union. FBI Federal Bureau of Investigation (the United Nomenclature States). 3G Third generation (cellular). FCC Federal Communications Commission. 3GPP Third-Generation Partnership Project (cellular). FSMS Federal Spectrum Management System. 4G Fourth generation (cellular). GAA General authorized access. AMT Aeronautical Mobile Telemetry. GHz Gigahertz. ADC Analog-to-digital convertor. GPS Global Positioning System. HF . IA Incumbent access. IETF Internet Engineering Task Force.

Manuscript received September 30, 2013; accepted December 23, 2013. Date of ISM Industrial, scientific, and medical. publication February 4, 2014; date of current version February 14, 2014. This work LDA Linear discriminant analysis (machine learning). was supported in part by the National Science Foundation (NSF) Enhancing Access to the Radio Spectrum (EARS) Program under Projects 1343222 and 1247928, and by LSA Licensed shared access. the TWC under Project 1228902. LTE Long-term evolution (cellular). The authors are with the Electrical and Computer Engineering Department, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-1019 USA MAC Media-access control. (e-mail: [email protected]). MBAN Medical body area network. Digital Object Identifier: 10.1109/JPROC.2014.2298437 MEMS Microelectromechanical systems. 0018-9219 2014 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. 242 Proceedings of the IEEE | Vol. 102, No. 3, March 2014 Dudley et al.: Practical Issues for Spectrum Management With Cognitive Radios

MHz Megahertz. Table 1 Applications of DSA Technologies Mil STD Military standard. MIMO Multiple-input–multiple-output (antenna). NIST National Institute of Standards (the United States). NPRM Notice of Proposed Rule Making (FCC). NTIA National Telecommunications and Information Administration. OFDM Orthogonal frequency-division multiplexing. PA Priority access. PAWS Protocol to Access White Space (IETF). PCA Principle components analysis (machine learning). PCAST President’s Council of Advisors on Science and Technology (the United States). PHY Physical layer. PUE Primary user emulation. REM Radio environment map. RF . RFIC Radio-frequency integrated circuit. SAW Surface-acoustic wave. SDR Software-defined radio. SNR Signal-to-noise ratio. SON Self-organizing networks (cellular). TDM Time-division multiplexing. TV . VoIP Voice-over-Internet Protocol. Wi-Fi Wireless fidelity (IEEE 802.11). WiMAX Worldwide interoperability for microwave access. WRAN Wireless regional area network.

I. INTRODUCTION Some predict that demand for cellular spectrum could see a1000Â rise over 3G demand [1]. Notwithstanding the move to smaller cells and off-loading to Wi-Fi, not enough spectrum appears to be available to meet this demand. Part of the ‘‘spectrum scarcity’’ problem is that the regulatory approach to spectrum allocation is extremely inefficient, resulting in spectrum being allocated but unused, or used Table 1). While spectrum sharing is not new (e.g., only occasionally, in many areas [2], [3]. Automatic Link establishment), the use of CR technologies A major factor driving us toward new spectrum-sharing may make it easier to develop and deploy systems that models is that the electromagnetic spectrum has been share spectrum. shown to be a catalyst for economic development [4]. In some ways, DSA is a radical change from fixed Eager to further spur their economies, nations are spectrum assignment. A change like this will not happen competing for leadership in technologies that allow for overnight, nor will it happen through technology advance- spectrum sharing [5]–[8]. CRs, which are capable of DSA, ment alone. Given these facts, this paper looks at some of have been claimed by proponents in the European Union the practical issues in the deployment of DSA using CRs. and the United States as the most effective solution to the spectral congestion problem. CRs can be a critical A. Paper Outline technology to spur positive change in the current This paper is divided into six sections. Section II regulatory policies (see [2], [9]–[11], and article 4.1 of provides some background information about new licens- [12]). Recently, there have been several efforts to ing models currently being debated within regulatory incorporate CR and DSA technologies into the develop- agencies, and an overview of a recently completed DSA ment of standards for a wide variety of applications (see standardVIEEE 802.22. Section III considers spectrum

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Fig. 1. Licensing models [2], [24].

management systems, and the various architectures that ical area, but must vacate the band when an incumbent is have been suggested for providing legacy user protection. present. Section IV looks at how individual radio nodes achieve The report noted that receiver performance can limit frequency agility, and the issues that are faced in designing efficient use of the spectrum and recommended the systems with these capabilities. Section V provides a brief management of receivers as well as transmitters. Declar- excursion into machine learning techniques. Section VI ing a receiver’s tolerance for interfering signals makes it considers oversight and regulatory issues. Section VII easier to manage spectrum decisions when new entrants concludes with a discussion of the implications on future arrive. standards of the topics considered in the paper. It was also recommended that the model for spectrum allocation be changed from the current ‘‘semipermanent assignment’’ system to a more flexible system that adds II. BACKGROUND short-term and medium-term licenses. Medium-term One of the implications of dynamic spectrum sharing is the licenses are envisioned to be three or fewer years and need for new licensing models. Both the European Union have no automatic rights of renewal. This scheme would and the United States are taking steps to update their allow firms to experiment with networks and business regulatory processes to include new forms of licensing, models. It would also provide assurance to government with commercial interests providing input [24]. In the area agencies that may need additional spectrum in the near that has been explored the longest, TV white space, the future. A short-term license, on the other hand, involves a IEEE 802.22 standard has been created. fixed set of standards, terms, and conditions, so as to accelerate the agreement process. The idea of a short-term A. Licensing Models license is new, and the meaning of ‘‘short term’’ will likely The U.S. PCAST issued a report on July 20, 2012, be shaped by the market over time. An example short-term relating to spectrum allocation [2]. Some of the high level license might be renting spectrum over the course of a few points made in that report are shown in Fig. 1 and are days when the Super Bowl is in a city in order to provide addressed in this section. The report recommended a adequate cellular service. The addition of medium-term three-tiered Federal Spectrum Access System that involves and short-term licensing will likely spur new and innovate classifying users into one of the following categories: 1) IA; wireless applications. 2) secondary access; and 3) GAA. ASA is an alternative spectrum-sharing structure that The incumbent users (also know as primary users) involves two tiers. ASA started as a joint project by seven would receive protection from interference from all other companies (Digital Europe, Ericsson, Huawei, Intel, types of access. Secondary access users would be issued Nokia, NSN, and Qualcomm) in order to promote the short-term priority operating rights in a specific geograph- use of unused spectrum in Europe through DSA and CR

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technology [12]. The ASA concept has been named LSA by the Radio Spectrum Policy Group within the European Union. LSA seeks to grant shared access licenses to operate on bands that have been licensed to other users [12]. One operator can pay another operator for a certain amount of bandwidth, at a certain quality of service. This type of system uses the idea of a licensed secondary user, in which the secondary user has rights to the spectrum in locations (be it time, frequency, and/or geography) where the primary user is not present. A licensed primary and secondary user can be thought of as two licensed primary users, where one has priority over the other. Having Fig. 2. IEEE 802.22 system functions [26]. licenses for shared access allows operators to predict the quality of service. The U.S. FCC is evaluating schemes for DSA [25]. The NPRM for the 3.5-GHz band echoes the PCAST three- manager acts as the cognitive engine inside each base tiered structure [8]. The NPRM describes IA in the 3.5-GHz station, and is responsible for tasks such as maintaining band as belonging to authorized federal users and grand- spectrum availability information, channel selection and fathered fixed satellite services. The second tier is the PA, management, scheduling spectrum sensing, enforcing which includes users with a definite need for guaranteed regulatory policies, and allowing self-coexistence. Fig. 2 access to broadband spectrum at specific facilities such as shows the logical interfaces of the IEEE 802.22 spectrum hospitals, utilities, government installation, and public safety manager. entities. Tier three is theGAA, for opportunistic use on The standard’s PHY implementation, which is OFDM noninterfering bases in specified geographical areas. based, can support a cell radius up to 30 km. To support The European Commission is also taking spectrum- multiple IEEE 802.22 cells in close proximity, self- sharing initiatives. The Radio Spectrum Policy Group, an coexistence procedures are defined. The IEEE working advisory group that assists the European Commission, group for IEEE 802.22 was formed in 2004, and the first released a report that explores dynamic spectrum-sharing standard was published in July 2011. As of the writing of approaches and the identification of higher frequency this paper, FCC rules require each spectrum manager to bands that could be candidates for shared spectrum [12]. check the FCC database daily, but no rules have yet to be SimilartoPCAST,thisreportproposesmultiplemodesof established to cover sensing applications (e.g., detecting spectrum sharing in order to remain flexible. The wireless microphones operating in the same band, for European Commission’s proposal differs from PCAST’s in example). that Europe is targeting all spectrum with its sharing initiative, while the United States is so far primarily C. IEEE 802.15.4j Medical Body Area Network interested in sharing of TV white space and spectrum Current MBAN solutions are mostly deployed in the currently allocated for government use [12]. 2.4-GHz ISM band. Since the ISM band is becoming more and more crowded, interference could limit large- B. IEEE 802.22 Wide-Area Regional Network scale deployment of MBAN applications. In the United IEEE 802.22 is a standard for WRANs using the TV States, the FCC recently allocated the 2360–2400-MHz white space [26]. The primary application of this spectrum for MBAN use on a secondary basis, sharing the technology is providing wireless broadband access to rural spectrum of aeronautical mobile telemetry. The IEEE homes. Using DSA techniques, IEEE 802.22 allows the 802.15 Task Group 4j (TG 4j) has been developing an sharing of spectrum allocated to TV broadcasters, as well amendment to the IEEE 802.15.4 standard to extend its asotherincumbentssuchaswirelessmicrophonesystems. PHY and MAC layer solutions to the MBAN spectrum. IEEE 802.22 uses a point-to-multipoint wireless access DSA protocols play an important role in allowing system (similar to cellular), formed by a base station and MBAN operations since aeronautical mobile telemetry connected users. Spectrum sensing data are fused with devices are mostly receive-only. To avoid requiring explicit occupancy data retrieved from a database service and used coordination between primary and secondary users on a by the base station to determine which channels are case-by-case basis, a beacon signal, called a hub, is placed available for operation. As such, each base station must near the patient, and low-power transmitters on the body include a GPS receiver for geolocation. To deal with low- can transmit only when they receive the beacon. The hub power incumbents (e.g., wireless microphones), the IEEE gets its authority to transmit from a key that it receives as 802.22.1 amendment was created to describe a beacon part of the general coordination process that grants signal that can be transmitted in order to indicate the spectrum access to the medical facility. For its part, the incumbent’s presence. In IEEE 802.22, the spectrum FCC decided not to require all users to apply for

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Fig. 3. Example spectrum management system.

authorization. MBAN users operate on a secondary user impossible, simply by doing thought experiments or basis, meaning they must not cause harmful interference running simulations, to know what real problems will and they must accept all interference from incumbents. come up when systems are actually deployed. Given that DSA is not just a single system, but rather a III. SYSTEMS FOR SPECTRUM general philosophy for many different kinds of systems, MANAGEMENT there are many cases for which metrics need to be identified, as well as decisions made about mechanisms to Fig. 3 provides a pictorial overview of the spectrum gauge effectiveness of legacy protection. What we have management system assumed in this paper. seen so far is willingness of some users (e.g., AMT) to Introduction of CRs into spectrum sharing and allow sharing with some organizations (e.g., the medical spectrum management opens up many avenues for community) to allow a specific application (e.g., MBAN) efficient system design. It also introduces new challenges, some of which will be discussed in this section. As shown in the figure, this paper assumes that CRs have frequency agility and spectrum sensing capabilities. The location of Table 2 Spectrum Management System Types cognitive engines and knowledge bases typically depends on the nature of the spectrum management system. This paper assumes a classification of spectrum management systems into the categories of supervised systems and unsupervised systems. For details, see Table 2. (Note that other taxonomies exist [27].)

A. Legacy Protection and Commercial Viability Without protection for legacy users, spectrum sharing will never be allowed by regulatory authorities. This makes legacy assurance the most important practical issue for DSA. The nature of the incumbent user and the potential secondary user significantly affects willingness of the incumbent user to enter into a sharing relationship. Research has not yet provided a reliable mechanism to gauge the level of protection that each type of DSA system canprovide.Thisisstillaverynewfield,anditis

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where the primary user has a relatively straightforward not omniscient. A research direction for decentralized mechanism to identify and hold the organization account- approaches is the utilization of distributed databases to able (e.g., allow only one user, or conform to a create more reliable REMs [29]. coordination process). It is unclear how long it will take Centrally supervised architectures are commonly to reach the point where all spectrum can be accessed by touted as most easily accommodating legacy assurance. any user simply by petitioning the spectrum management This is due to the fact that they can be made to comply with system and complying with its rules. It should be expected arbitrary policies or levels of security and do not require that there will be many trials of different types of spectrum radios to have a high degree of cognitive capabilities (yet management systems, with different kinds of primary and can accommodate those that do). However, there is a secondary users, before confidence in such systems will significant tradeoff between complexity, cost, and latency. reach that tipping point. Design approaches for these kinds of systems are still in their infancy. IEEE 802.22 is an example of a centrally B. Choosing the Right Architecture supervised system, as would be systems that involve the Choosing the right architecture is both a function of sharing of spectrum with cellular service providers (e.g., a the technical characteristics of the system, and the proposal for allowing cellular providers to use naval radar political realities of the parties involved. The question of spectrum at inland locations). tangible benefits to primary users has directed some of the Whether systems are unsupervised, have distributed discussion about regulatory policy and the types of supervision, or are centrally supervised, there may be a cooperation that can be achieved [28]. If the primary need for sensing. Likewise, there may be a role for the use user has no mechanism to benefit from sharing spectrum, of databases to maintain information about the environ- then cooperation is unlikely. For example, a system that ment. That information could be static (e.g., TV station incorporates spectrum trading may not be viable if the locations)ordynamic(e.g.,sensingofwirelessmicro- primary user is a federal organization that is forbidden by phone usage). Issues with sensing and databases will be law from receiving compensation for spectrum. discussed in subsequent sections. The ‘‘right’’ architecture is still being debated in both research and commercial communities. For many incum- C. Collaborative Sensing Issues bents, even if they are using spectrum inefficiently, they Collaborative sensing is one of the solutions proposed see huge risks in admitting secondary users. Although early for several sensing problems: sensing accuracy, spectrum research favored unsupervised systems using a pure coverage, processing complexity, and energy efficiency sensing-based approach, the failure to provide solid [33]–[38]. The intelligent combining of the spectrum guarantees of protection led to a shift toward researching sensing data and/or decisions from multiple CRs can centrally supervised systems and databases. Research into improve the sensing accuracy (with respect to the decentralized approaches is just beginning [29]. Research probability of detection and false alarm) while potentially is ongoing with all three types (unsupervised, centrally lowering the sensing requirements of all of the CRs in the supervised, and distributed supervision). Whether there group (with respect to sensing time, sensing approach, and will be many flavors of systems, each tailored to a specific energy usage) [38], [39]. circumstance, or whether there will be adrift toward a Issues faced by collaborative sensing systems are the general strategy for all DSA systems is not clear at this overhead that collaboration creates, the management of point. sensors (sensor clustering), fusion of data from sensors, An unsupervised approach does not suffer issues with and distributed spectrum search. Each will be considered latency in decision making, and is relatively low cost. in subsequent sections. However, selfish optimization without the knowledge of the network can result in low overall spectrum efficiency. 1) Overhead: There are two main approaches to In addition, there are types of primary users for which this collaborative spectrum sensing: centralized approaches type of system would be unsuitable. Given these facts, the [40] and distributed approaches [41]. In centralized design of algorithms for these systems also includes the approaches, the cooperating CRs send their spectrum study of game theory, in which games are devised that sensing information to a data fusion center. The data attempt to provide minimum performance guarantees fusion center then makes global spectrum decisions for all [30], [31]. of the cooperating CRs. In distributed approaches, each CR Decentralized supervision uses network information makes its own sensing decisions based on sensing from neighbors to make better decisions than could be made information from cooperating radios. In each of these if restricted to its own sensors and data (see Section III-C). Of approaches, there is a natural tradeoff between the per- the three general approaches, it is the one most suited for formance benefits gained from collaboration and the implementation with CRs since it requires collaboration to amount of overhead required [42]. This overhead takes the achieve its goals. However, as noted in [32], a decentralized form of information that must be passed among the CRs approach may not achieve the global optimum solution if it is (in distributed approaches) or to a data fusion center (in

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centralized approaches), thus increasing network traffic spectrum search in the wide spectrum bands [51]. The and energy needs. issue is that understanding the entire radio environment is In the literature [38], [43], it is typically assumed that a challenging task for a single node. Distributing the task of the collaboration channels (channels by which the spectrum search among multiple nodes reduces the impact cooperating CRs communicate with the fusion center to each individual node. and/or each other) are ideal. An issue not typically Conducting a spectrum search can be a multilayer considered in the literature that needs additional research process [52]. A receiver can be dedicated to scanning the is the impact of nonideal channels [44], [45]. spectrum, and the results maintained in a database. In addition, some MAC protocols have a learning feature that 2) Appropriate Clustering of Sensors: It is known that can characterize availability of channels based on past there are diminishing returns on the performance gains decisions [52], [53]. Optimizing the placement of learning that can be achieved through collaboration as the number processes, and the use of databases and cognitive engines of collaborating CRs increases. Therefore, when develop- to exploit this information, is an ongoing research area. ing collaborative approaches to spectrum sensing, it is important to consider how best to cluster the CRs to D. Database Reliability achieve adequate performance gains while keeping energy Information reliability is critical for database systems. needs reasonable. In other words, determining what is the As an example, geolocation databases are envisioned to appropriate way to group CRs together for the best maintain data about primary user locations and their cooperation results [46]–[48]. operation parameters (e.g., transmit power, antenna parameters, protection contours, and operational periods) 3) Fusion of Potentially Diverse Sensing Data: There is a [54]–[57]. Spectrum availability is calculated based on natural tradeoff between collaborative sensing perfor- these parameters [58]. Unreliable data would lead to mance and overhead between using hard and soft allocation of spectrum bands that are already in use by decisions. Hard decisions, in which each CR sends a primary users. distinct, or ‘‘hard,’’ decision to the fusion center, will tend Given that the spectrum management system is to lower overhead with respect to data transmissions in the database driven, primary user data are acquired by cooperation channels. However, there is a fundamental database administrators from regulatory databases (e.g., performance loss that will occur as a result of losing some the FCC CDBS [59]) and potentially through web of the detailed sensing information [43]. registration methods. The database administrators [56], On the other hand, soft decisions provide more of the [57] and regulators (e.g., FCC, NTIA, and CEPT) must detailed sensing information to the fusion center, leading ensure that primary user registration and update mechan- to more intelligent cooperative spectrum sensing decisions isms provide complete and accurate data. The reliability of to be made. Naturally, each CR sending more detailed database information is a subject of research [60]. Metrics spectrum sensing information will lead to an increase in are being devised to measure that reliability. These include data transmission overhead. Additionally, soft decisions utility, objectivity, and integrity of data. Utility is the are more prone to errors caused by nonideal collaboration usefulness of information to its intended user. Objectivity channels [49]. is the presentation of information in an accurate, clear, In an attempt to balance these tradeoffs between hard complete, and unbiased manner. Integrity is the protection and soft decisions, so-called softened hard, or hybrid, of information from unauthorized access or revision in decisions have been proposed for data fusion; see, for order to ensure information is not compromised through example, [50]. These approaches can provide lower overhead corruption or falsification. than purely soft decisions, while improving upon the sensing The IETF PAWS outlines secondary user device performance with respect to purely hard decisions. registration to a database, as well as spectrum requests Another critically important practical issue with and database responses [61]. The protocol also provides collaborative data fusion deals with the consideration of certain security measures for protection against PUE nonidentical, or heterogeneous, CR sensing capabilities attacks, spoofing the database, modifying or jamming a when performing collaboration. In the literature [49], the query request/response, and tracking the white space majority of works on collaborative spectrum sensing device location and identity. Significant effort is being assume that the sensors have identical sensing capabilities applied to improve the reliability of primary user’s and/or sensing channels. For example, they typically spectrum usage data in the regulatory spectrum licensing assume each sensor uses the same sensing approach databases [59], [62]. (cyclostationarity, likelihood-based, cumulants, etc.) or is Conventional data reliability methods cannot address impacted by the same type of channel. the problem of primary user parameter inference through normal secondary user database queries [63], [64]. For 4) Distributed Spectrum Search: Sharing between local example, is it necessary to prevent a secondary user from databases has been proposed as an enabling approach for inferring the presence or capabilities of another user (say

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radar, or FBI communications)? These techniques create main receiver as a sensing receiver so a secondary receive primary user privacy concerns in spectrum-sharing data- chain is not always required. It is also noted that since the bases, some of which will be addressed in Section VI-D. purpose of this receiver is detection of a signal, not Research is still needed in the area of primary user decoding of the message, that processing gains can operational privacy concerns within spectrum management sometimes be achieved. systems. Thedatabaseenabledspectrumsharingwillbedivided B. Radio Complexity into categories of federal and nonfederal spectrum users. Implementing DSA techniques in the radio, as The NTIA FSMS will maintain operational data about discussed in this section, has an impact on radio cost. federal primary users like radar systems, government One aspect of this cost is software. DSA applications often agencies, etc., and the FCC CDBS will maintain data about need the ability to be reconfigured in real time. Although nonfederal spectrum users like TV stations, satellite software techniques to do this are well known, real-time systems, cellular systems, etc. NTIA will make available configuration software is more difficult to write. This bits and pieces of spectrum that is not used by federal comes partly from the challenges imposed by software systems in frequency, space, and time to the geolocation validation and general testing, partly from the need to database manager for secondary use. This categorization of address new security issues, and partly from the large spectrum users will address the concerns of the federal number of use cases inherent to DSA. agencies whose operational privacy is one of the major DSA strategies within the radio also have to compete hurdles holding back the federal government from opening directly with simple packaging exercises that place up some of its spectrum for sharing with commercial multiple RF chains in a single device such as is currently systems. done for smartphones that operate with 3G, 4G, LTE, Bluetooth, and Wi-Fi. In the sections that follow will be a E. System/Network Latency brief discussion of hardware issues. This includes: Latency in system interactions is a practical issue facing achieving frequency flexibility in the RF chain, searching developers of spectrum management systems. As with any the spectrum for primary users, tradeoffs related to control system, the latency of the decision cycle can affect spectrum sensing, and the availability of propagation system stability, as well as limit the maximum number of models for higher frequencies. clients supported. The system can have two kinds of latencies. The first relates to how long it takes to establish C. Achieving Frequency Flexibility an initial security and trust association. The second relates CRs need to be operational over multiple frequency to how long it takes to query the database/server and bands. Using a sufficiently selective flexible RF removes receive a response. If the system is expected to provide the need for high-performance ADCs and DACs in CRs. guarantees of maximum latency in order to respond to Frequency flexibility can be achieved through the follow- events when all the nodes need to (re)register with a ing: wideband tunable oscillators, wideband antennas, and database at once, designing the servers can become an wideband tunable filters in transmitters and receivers (see economic issue involving both sizing of the server Fig. 4 and discussion below). infrastructure and the transport network. Although there is no strict need for research into better strategies to 1) Tunable Oscillators: RFICs with wide tuning range implement the network pieces of the system (since such have already been reported and are available in the market network design techniques are well known), choosing the [65]. However, oscillator noise is still a problem that needs best strategy requires careful engineering, and may benefit more research. from future research in the area of forming security and trust relations. 2) Wideband Antennas and RF Amplifiers: There is a fundamental limit theory addressing the well-known tradeoff between antenna size and achievable instanta- IV. THE RADIO neousgainbandwidthfortransmitantennas[66]–[69]. For receive antennas different limits apply. The funda- A. Cognitive Radio mental limit of receiver antenna size is related to SNR For the purposes of this paper, a CR is defined as a bandwidth and the noise figure of the antenna [70]. Noise radio that has sensing capabilities, frequency agility, and is and selectivity of RF front–ends are dominant factors operating in a spectrum management system under causing practical spectrum sensing issues in the receiver. cognitive control. A practical CR measures the state of Mitigation of coupling effects between small form- the spectrum using a locally implemented spectrum sensor factor MIMO systems remains a challenge. However, and/or by probing a network level database. The assump- ultrawideband electrically small antenna designs covering tion in this section is that CRs have a sensing receiver. If 3.1–10.6-GHz band have been extensively investigated in there are quiet periods in the operation, a CR can use its the literature (see [71] and [72] among others), and

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Fig. 4. Achieving frequency selectivity over a wideband.

commercial off-the-shelf products are available in the frequency RF filters found in devices such as cell phones. market. Practical issues for designing receive antennas There are two traditional approaches to construct come from performing tradeoffs between selectivity and frequency flexible RF filters in receivers, multiband filters sensitivity of the RF front–end as opposed to being unable and tunable filters. A nontraditional approach is relaxing to design wideband antennas. the selectivity specifications of the filters. Superwideband low-noise amplifiers and mixers with • Multiband filters (using multiple frequency- good linearity performance, as well as wideband power dedicated filters): A major challenge with this amplifiers with good linearity and efficiency performance, strategy is the insertion loss of the switching have been proposed [73], [74]. However, a similar level of network (which affects the SNR), and the physical progress has not been achieved in RF filtering. The size of each filter. Miniaturization of surface problem of RF filtering is a major challenge for making CR acoustic wave and bulk acoustic wave filter tech- a reality [75]. This is mainly because of the technical nologies is addressing the latter problem. For tradeoffs between high selectivity and broad tuning range example, some commercial smartphones support in RF filters. a dozen frequency bands on a single device using very small fixed filters. However, as the number of 3) RF Bandpass Filters in Receivers: Pre-selector required frequency bands increases, managing (bandpass) filters are often placed at the input of the them becomes more costly, and at some point main receiver and the sensing receiver. The pre-selector becomes impractically large. filters attempt to maximally reject all undesired adjacent • Tunable filter: RF filter implementation technol- channel signals with minimal effect on the desired signal. ogies such as SAW-based devices and ceramics are Without pre-selector filters, an excess amount of undesired not suitable for making tunable filters. For this signal enters the receiver and distorts the desired signal. reason, different technologies such as semicon- This degrades both the quality of the signal for demodu- ductor varactors, ferroelectric materials, and lation purposes and for spectrum sensing purposes. MEMS are used to make tunable filters. However, The selectivity specification of the pre-selector filter flexible RF filter technologies provide significantly can be very stringent when adjacent channels are very inferior selectivity performance compared to fixed close to the desired frequency band. The selectivity RF filters [76]. specification can be even more challenging in full duplex • Relaxing selectivity specification: When RF filters systems where the full transmit power may appear on the cannot be sufficiently selective, approaches that receive antenna. Noise generated by a wideband transmit relax the selectivity specifications can be consid- poweramplifier,aswellasleakagefromthetransmitted ered. For example, designing the network to be signal, can easily degrade the sensitivity of the receivers. half-duplex significantly relaxes the selectivity Therefore, selectivity of wideband tunable RF filters in specifications of the RF filters. In [77], Marshall DSA capable receivers must be comparable to fixed proposed a network level technique in which

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transmission frequencies are selected such that the sensing focuses on improving the detection reliability [81] expected nonlinearity distortion in the receiver is of the primary user signal. minimized. Marshall showed that this technique A significant practical issue is the time it takes for has the potential of significantly relaxing the reliable detection. A common research goal is to speed up selectivity and linearity specifications of the the channel search process by designing a sensing policy receiver. that identifies the desired signals quickly. In [82], random Incorporating cognitive control of receiver parameters, and serial search mechanisms are proposed for indepen- such as sampling frequency and local oscillator frequency dent and correlated channel occupancies. The perfor- of the receiver, relative to the state of the spectrum, has mance of these search schemes is compared in terms of the been proposed. This technique potentially relaxes the mean time to detect the primary user signal. In [83] and selectivity and linearity specifications of the receiver since [84], a two-stage channel search is proposed to reduce the it avoids worst case situations that may be a lot worse than average channel search time by focusing on frequency the expected cases. Techniques to reconstruct the effects channels which are more likely to be vacant. These of RF front–end nonlinearity in wideband spectrum approaches perform better than conventional methods sensing have also been proposed that would allow when the spectrum is crowded. In [85], a wideband mitigation to be applied, thus further reducing the worst channel clustering scheme is proposed to cluster users case nonlinearity.1 with smaller bandwidth requirements in order to avoid unnecessary blockage to users with larger bandwidth 4) RF Bandpass Filters in Transmitters: For efficient requirements. spectrum sharing, each transmitter needs to emit the desired signal with minimal interference on other E. Sensing Constraints and Tradeoffs frequency bands. Undesired transmissions can originate At the expense of implementation complexity, multi- from harmonics, spectral sidelobes due to discontinuities layer and clustering-based channel search can be used to in the pulsing of the signal, and spectral regrowth due to reduce the average channel search time by giving unequal power amplifier nonlinearity. focus on different channels based on aprioriinformation The same mitigation strategies for receivers (multiband [83], [84]. The secondary user applies single-channel filters or tunable filters) can be used to eliminate sensing on each individual channel to determine if it is transmissions outside the desired band. Because harmo- vacant. Practical issues involved in single-channel sensing nics are relatively far off in frequency, the specification of are discussed below. the transmitter’s RF filter is not as strict as that of the receiver. Tunable filters are not mature enough for RF 1) Time Constraints: There are two types of CR filtering in the transmitter. architectures typically discussed that are relevant to In terms of relaxing the need for tight filter specifica- spectrum sensing, single-receiver designs, and dual- tions, the transmitter can also implement one or more of receiver designs [86]. In single-receiver designs, spectrum the following: digital pulse-shaping filters to reduce sensing must be accomplished during the so-called ‘‘quiet spectral sidelobes, backoff in the power amplifier to times’’ when data transmission is idle. This architecture reduce spectral regrowth, and implementing half-duplex inherently requires a time slot for sensing and a time slot (e.g., time-division duplex) versus full duplex systems. for data transmission. In dual-receiver designs, these quiet times are only necessary when sensing must be performed on the band being used for data transmission. The D. Spectrum Search necessity of quiet times to perform spectrum sensing Fast and reliable spectrum search is an important leads to a tradeoff between spectrum sensing accuracy and aspect of white space characterization. One way to detect data throughput [87]. available white space is to test for primary users operating Detrimental channel effects, such as shadowing and within the communication range of a secondary user. multipath, determine how long spectrum sensing decisions Searching for primary users over a wideband spectrum will remain relevant (due to Doppler spread and channel sensing allows nodes to search for primary user signals in a coherence effects, for example), thus dictating the needed wide spectrum band [78]. update rate. For example, spectrum sensing in mobile Initial approaches to wideband spectrum sensing used applications, where the wireless channel is changing multiresolution spectrum radios based on wavelet trans- rapidly, requires much faster sensing capabilities than form [79] and fast Fourier transform processors [80]. The static or slowly varying channels. idea is to estimate the power spectral density of the In many cases, the specific spectrum management wideband signal using an RF front–end with a wideband application will provide constraints upon the availability architecture. Most of the existing literature on wideband and length of quiet times. For example, in IEEE 802.22, it 1This technique is developed at Wireless@Virginia Tech. Papers is specified that the maximum time it should take to detect describing the technique were recently submitted for publication. licensed primary users within a given channel, during

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normal operation, should be much less than 2 s, under the because of physical location, severe multipath fading, or constraints of over 90% probability of incumbent detection shadowing, this will cause unwanted interference to the and a false alarm rate of less than 10% [26]. In more primary user. Cooperative sensing is proposed in the unpredictable and critical spectrum-sharing applications, literature for handling this kind of practical issue [102]. where a variety of wireless devices and wireless commu- nication standards are simultaneously in operation (such F. Need for New Propagation Models as in hospital environments), the sensing time and update Propagation models are crucial for spectrum manage- rate need to be much faster [88]. ment systems to ascertain the spectral reuse factor and to obtain interference maps. Ample propagation models are 2) Performance Tradeoffs: There are a large number of available at conventional frequency bands, typically up to spectrum sensing algorithms to choose from. In general, 3 GHz. However, propagation models and vector channel low complexity spectrum sensing algorithms (e.g., energy modelsforfrequenciesgreaterthan3GHzisanareathat detection [89] and eigenvalue decomposition [90]) per- is still developing. Several attempts have been made by form poorly in bad channel conditions, but may be the only researchers to obtain the propagation model with the choice given receivers with low processing power. The popularization of the WiMAX standard. However, there is setting of detection thresholds for these cases is still a an ample scope for developing better propagation models. highly researched topic [91], [92]. On the other hand, A propagation model specifically designed for the more accurate and highly complex algorithms (e.g., 3.5-GHz range is the Stanford University Interim model cyclostationarity detection [93], [94], wavelet approaches formulated for the IEEE 802.16 working group [103]. The [95], and cumulants [96]) provide more information about ECC-33 model was a new propagation model developed by the signal than mere detection. These algorithms typically fitting the Okumura data, and works similar to the popular require some sort of pattern recognition approach in order Cost Hata 231 model. The WINNER project has developed to perform decision making, leading to additional channel models, which are classified as 3GPP spatial complexity and overhead. For more in-depth details of channel models for MIMO [104]. However, they are different spectrum sensing algorithms and their associated geometry-based channel models and not specific to 3.5 GHz tradeoffs, the reader is referred to [31], [33], [34], [86], or small cells. Phase 2 of the project included several and [97]–[99]. system level simulation studies and presented an in-depth When performing spectrum sensing, the performance study of outdoor-to-indoor communication channels [105]. of the sensing algorithm improves as the observation time Not all of these models are specific to high-frequency of the signal of interest increases. This tradeoff between channels being considered for commercial use on a sharing performance and observation interval is typically referred basis. At present, the Stanford University Interim or to as processing gain. In DSA applications, the optimum ECC-33 models provide reasonable fits, but not good point is dictated by the tolerance of the primary spectrum enough to ensure an adequate quality of service. Moreover, user to interference. In other words, the time required to exhaustive building penetration studies and vector channel sense the primary user and vacate its spectrum is a models for MIMO systems need to be carried out for deciding factor for system viability. successful system implementations at these frequencies. One intriguing idea suggested by Ronan Farrell is the 3) Environmental Constraints: An important practical useofCRstoimprovemodelsbycomparingwhatthe issue to consider when choosing a spectrum sensing model predicts with what the radio is actually seeing. In algorithm is the sensing channel. Although AWGN and essence, this is a call for a longitudinal study of radio flat-fading assumptions are sufficient under some condi- models, looking for inferences about when or where the tions (e.g., in sparsely cluttered line-of-sight environ- models do not match actual conditions. ments), they do not suit more general wireless operating environments, where multipath and frequency-selective G. Decision Reliability in a DSA Environment fading effects may be prominent. As a means of dealing Traditionally, propagation models (sensing papers) with these issues, MIMO systems have been discussed as a have only concerned themselves with the channel between possible solution [100], [101]. Exploiting resolvable the primary user transmitter and the sensor. From this multipath with modified spectrum sensing algorithms channel model, they determine a probability of detection such as modified energy detectors and equal gain detection and probability of false alarm of the primary user. Michael can actually improve the detection performance. However, Marcus has proposed that this view be amended to include these approaches introduce their own practical issues (i.e., all three channels between the primary user transmitter, interantenna spacing to guarantee independency of signal secondary user, and primary user receivers [106]. The streams). reasoning behind this is that there may be correlation Another issue that has a severe effect on sensing between two or more of the channels. This makes it more reliability is the hidden node problem [86]. If the DSA difficult to answer the question of how likely it is that the transceiver is unable to detect the primary user, either failure to detect a primary user signal down to some

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arbitrary level (say À120 dBm) means that the secondary the ability to classify current situations in order to see if it users’ transmission will be below some threshold (say is similar to one or more previous situations. À80 dBm) by the time it reaches any primary user. The use of situational awareness leads to a cognitive engine that has a case-based reasoning component to it. This type of cognitive engine uses optimization augmented V. COGNITIVE ENGINES by learning. For example, a cognitive engine may use a genetic algorithm for optimization and a neural network to Cognitive engines are implied for spectrum management perform situation classification, but a case-based reasoner systems that employ CRs. Cognitive engines may exist tostorewhatithaslearned.Theresultisaradiothatcan either in the radio (for unsupervised systems or distributed save time and/or reach better solutions by leveraging supervision systems) or in designated servers somewhere previously gathered knowledge. A practical issue in the network. Cognitive engines are based on either concerning case-based reasoning is the amount of memory machine learning or optimization techniques, and the required to hold previous cases, actions, and results. most common techniques are listed in Table 3. The tasks Solutions include forgetting the oldest case (treating it like that cognitive engines are assigned include achieving a first-in–first-out buffer) and eliminating cases that had situation awareness, parameter adaption, and pattern poor results when compared to similar cases [108]. recognition. Each of these tasks, and issues that they engender, will be considered in this section. B. Choosing Utility Functions for Parameter Adaption A. Achieving Situation Awareness In CR applications, prior knowledge of a given situation As shown in Fig. 5, situation awareness is the first step is typically in the form of optimization results; in other in the cognitive cycle. A given situation can be described words, identifying the best set of knobs (adjustable by the environment, user’s needs, or any other observable parameters) for a given situation. The best set of knobs problem. The goal of situation awareness is to use previous can then be immediately used by the radio, or can act as a knowledge that was gathered in the past under the same, seed for additional optimization [108]. Table 4 lists or similar, situations for decision making purposes. common knobs and meters in CR applications. Therefore, a major component in situation awareness is When performing these multiobjective optimizations, a utility function must be chosen. When multiple factors are involved, the typical strategy is to turn the problem into a Table 3 Cognition Toolbox single objective optimization by assigning weights to each of the factors. Although there are numerous optimization algorithms available, genetic algorithms have gained wide use in CR applications [108], [111]. Commonly used utility functions include weighted sum, exponential, and constant elasticity of substitution [108]. The weights in the chosen utility function are typically chosen manually, based on the importance of each objective for the given application. Unfortunately, the importance of each objective is not always clear. Additional complexity may be added when the weights of each objective change based on the situation. For example, when sending VoIP data, the system will have strict latency requirements but may not require high throughput. Conversely, for streaming video or large file transfer, throughput may be an issue, and not latency. For a survey on intelligence in CR parameter adaption, we refer the reader to [111].

C. Choosing Features for Pattern Recognition Patterns in the spectrum access of incumbents, opportunistic users, or malicious users can be used to improve situation awareness, leading to improved com- munications and threat avoidance. For example, an opportunistic user in another channel could use incum- bent patterns to predict where the next channel is likely to

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Fig. 5. Cognitive cycle [108].

be available, in the event that it has to immediately Dimensionality reduction is rarely performed in real evacuate the current channel. time. Instead, it is used during the design of the classifier, Pattern recognition can often be formulated as a in order to reduce the number of features the classifier machine learning classification problem, using algorithms must process. By reducing the number of features, the such as k-nearest neighbors, support vector machines, or computational complexity of training and using the neural networks [112]. When developing a pattern classifier is reduced, and less system memory is required. recognition system, one practical issue is choosing the In order to perform dimensionality reduction during the appropriate set of features. Another is having enough design process, a large and realistic set of training data training data to represent real-world conditions. must be obtained. If the training data do not reflect real- In any pattern recognition algorithm, there is the risk world conditions, then an important feature may be of using too many features. For example, in signal unknowingly removed from the set and the accuracy of classification, one might take into account a signal’s decision making degraded. modulationscheme,bandwidth,receivedpower,center Dimensionality reduction is a well-researched area of frequency, etc. If the goal is to classify incumbent signals, statistics and machine learning. Common procedures then all of these features may not be required as inputs to include PCA [113] and LDA [114]. When the training data the classifier. In machine learning and statistics, the set is small (which often occurs in CR), PCA can outperform process of dimensionality reduction is used to reduce the LDA [115]. For a tutorial on PCA, we refer the reader to [113]. number of random variables, or features, under consider- ation. The goal of dimensionality reduction is to find a D. Self-Organizing Networks subset of the original features that provides equal or One of the strategies for dealing with spectrum similar performance. A linear combination of two or more congestion for LTE deployments is to move toward a features may also be used (this can be thought of as heterogeneous network (Het-Net) of small cells and merging features prior to classification). macrocells. This results in a large number of network elements with complex interactions among them. Manag-

Table 4 Common Knobs and Meters in CR ing the complexity of manual approaches to managing the radio access network leads to SONs [116], [117]. Three focus areas exist within this umbrella: self-configuration, self-optimization, and self-healing. Self-configuration is needed to reduce the costs of installing new nodes and managing larger network structures such as domains. Self- optimization is needed given that channel conditions and connectivity situations are different over geography and time. Self-healing is needed to control network manage- ment costs [117]–[121].

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The concepts associated with CR are suited for the task of implementing SONs. SON typically applies to the automatic configuration and optimization of LTE base stations. Therefore, the SON algorithms could be im- plemented on the base stations themselves or on a centralized server that communicates with the base stations. For example, when a new base station is added, surrounding base stations could automatically reconfigure their emission power and antenna tilt using optimization techniques. Implementing SON has its own practical issues. One of the practical issues in SON implementations is reliability in a multivendor scenario [122]. Another issue is resolving goals. Nine use cases have been identified for SON. The goals of energy savings, load balancing, coverage, and interference mitigation are conflicting. Research is begin- ning to identify algorithms that allow an operator to Fig. 6. Security threats associated with dynamic spectrum sharing [128]. choose the desired behavior (see, for example, [123] for a discussion of load balancing and handover tradeoffs and [124] for node optimization interactions). the spectrum sensing data falsification attack, which is described in the following section. VI. OVERSIGHT 2) Spectrum Sensing Data Falsification: In any DSA A. Security application that involves sharing sensing data between Security has typically not been an issue on the critical nodes, an attack known as spectrum sensing data path leading to deployment. More often, it is considered as falsification is possible. The decision engine in CRs relies a postdeployment mitigation process. However, most of heavily on valid spectrum occupancy information. When the bands available for spectrum sharing are controlled by this information is fused between nodes, the spectrum Federal or civilian agencies (defense, aeronautical, mari- sensing data falsification attack involves injecting false time, public safety, etc.) whose mission cannot afford to be sensing information [126]. This could be done by a greedy compromised. It should be expected that all reasonable node who wants to improve its own throughput, a security threats and mitigation approaches be identified malicious node causing denial of service, or even a before sharing will be allowed. What follows are some malfunctioning node that is unintentionally sending wrong threats that must be considered for DSA (individual information (e.g., broken hardware). approaches may also incur other threats). Most proposed detection strategies involve building a trust or reputation value for each node based on past 1) Primary User Emulation: PUE involves an adversary or reports, in which outliers are used to indicate a possible malicious node emulating the signal of the incumbent in a lack of trust [126]. The ability for a radio to identify given band, so that the opportunistic users will evacuate malicious or malfunctioning entities is a practical issue in the channel(s) [125]. A greedy node may perform PUE in dynamic spectrum sharing, and these detection strategies order to improve its own throughput, or an adversary may should be considered during the design process. perform the attack with the goal of causing denial of service. Thus, PUE threatens the objectives of availability 3) Cognitive Control Channel Attack: DSA protocols often and access control. have a common control channel used to share information, PUE detection strategies can be split up into location which could be corrupted by jamming or by packet based and nonlocation based [126]. Location-based strat- flooding. Avoiding such points of failure is a practical issue egies involve knowing the location of all primary users, and in the design of DSA systems. One research direction is the using some metric to estimate location at each radio. use of a rendezvous strategy instead of a statically allocated Nonlocation-based strategies assume either that the common control channel [129]. adversary is moving, or that the adversary is much closer than the primary user, or that the primary user has a digital 4) SDR Hacking: Policies used in DSA will likely evolve signature incorporated into its signal [127]. In many overtime,andCRsneedawaytoadjusttopoliciesthatare dynamic spectrum applications, these assumptions will not created after the design process. If nodes are designed to be valid, thus the PUE attack is a practical issue that needs be updated remotely through the Internet, then there are additional research. Fig. 6 illustrates the PUE attack and clear hacking vulnerabilities. Furthermore, if users have

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control over software on their own radios, then they may spectrum management. In a recent report by the U.S. either deliberately or inadvertently disable policies Government Accountability Office [137], a survey of the intended to protect incumbent users. It may even be receiver performance, and their impact on spectrum, has possible for an adversary to hack radios and turn them into been described. The Receivers and Spectrum Working hostile jammers. Research into secure downloading Group of the FCC has reported elaborate means to describe systems for firmware or policy updates is, therefore, the interference limits, and the means to incorporate them needed. as a policy, in [138]. A final issue with regard to certification is the question B. Industry and Government Regulation of how and when certification is required. The current The issue of standardization occurs at multiple levels, system is based either on onetime certification testing and several of these levels will be addressed here. There is (usually with a very small number of units), or on a clear need to standardize the expression of capabilities providing manufacturing guarantees of low power. With a and needs. This shows up both in the form of device radio able to operate in bands with sensitive primary classifications and in dealing with policies. There is also a users, the question may become how to ensure over time need to minimize the amount of information that needs to that the radio is still fit for duty across all bands; passive be transmitted in order to convey meaning. Additionally, filters will no longer be a guarantee of noninterference. there is a need for standardization of metrics to facilitate The definition of ‘‘over time’’ includes both whether they interoperability and regulation. Each of these will be are still being manufactured to meet the original specs as considered. well as whether fielded units are still meeting those specs. 1) Device Classification and Certification: There are, as of yet, a relatively small number of devices capable of 2) Policy Drift Over Geography and Time: As spectrum supporting DSA. From a search of the FCC database [130], management systems are developed, the question of how only 336 approvals for SDR capable devices were given to deal with differences in policy becomes more signifi- between 2005 and 2012 (compared to a total of 16 000 cant. Barring the existence of a universal set of policies approvals per year for all radio devices). applicable worldwide, a CR that crosses a national It is likely that new classifications will be required, but boundary will be required to adhere to different policies. the fear that the approval process may be a bottleneck is It may also need to communicate with a different type of likely more perceived than real. Organizations like the spectrum management system, as well as with common FCC maintain a knowledge basethatcontainsguidancefor control channels operating at different frequencies. The cases that come up between rule making events (for questionofwhetherthiswillbeabalkanizingissuehasyet example, see [131]). The European Union maintains a set to be answered and, while it is not a technical issue per se, of what are called harmonized standards (see [132] and it will affect device design and the willingness of [133]). When new cases come up, there is a process to manufacturers to invest. provide a notified body of opinion from a certification lab. Another practical issue in dynamic spectrum sharing is Each has mechanisms for dealing with the kinds of changes how to deal with evolving capabilities of new radios and envisioned. with policy changes that occur after a radio is designed and Receiver performance characteristics play a crucial role manufactured. Making the radio flexible enough to deal in spectral efficiency and quality of service. Receiver with future policy changes has been proposed as a way of characterization has traditionally not been considered in dealing with this. spectrum management processes in favor of a system based At the heart of the question of how to deal with policy on characterizing only the transmitters. However, DSA over time is the tradeoff between expressiveness and creates new situations, such as spectrum placement of new complexity. In general, the more expressive the mecha- users adjacent to incumbent users. nism, the more flexible it is. Given this fact, a significant A literature survey reveals that most studies related to amount of research has been devoted to the concept of this have been carried out by regulatory and government policy reasoners that can interpret whatever policies they bodies (FCC, Ofcom, etc.). One of the initial studies into are given (see [139]–[143]). However, at the other receiver performance standards was carried out in [134]. A extreme, there is caution about trying to create more detailed analysis and methodology of receiver perfor- complexity than is really needed. Systems that come with mance, and the relevant influencing factors, has been expensive processing requirements will not be acceptable presented in [135]. to the community. As expressed in [143], ‘‘In this effort, The U.K. Office of Communications has reported the two fundamental dangers must be avoided: development of various receiver characteristics specific to several receiver a perfect language that nobody wants to use (similar to Ada architectures in [136]. The PCAST report [2] also gives a or Esperanto) and development of a large number of non- brief description about receiver regulations and the compatible languages that each solve one piece of the specific receiver characteristics needed to aid in better problem but not an efficient composite solution.’’

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The ability to change configuration of the radios, and/ how it should be used. One potential use case is that a or their policies, introduces the issue of maintaining spectrum manager could access the database and use a synchronization between a radio’s configuration and the regulatory-approved interference prediction model for configuration needed to operate correctly with the authorizing access, or for optimizing the spectrum spectrum management system. More research in this allocation process. In this mode, it might get items such area is needed. as the following from the database: interference power spectral density limits for incumbents, channel models, 3) Metrics for Regulatory Agencies: In the past, regulatory spectrum masks for secondary user transmitters, underlay agencies made band plans and system allocations with masks for receivers, cochannel and adjacent channel knowledge of component limitations of specific electronic interference limits for receivers, etc. It could then run implementations. With DSA, there are no specific calculations locally to coordinate spectrum assignments passband filters or RF characteristics that all hardware between secondary users, or even to detect noncompliance will contain. Therefore, it is not possible to achieve and enforce interference limits. spectrum management goals (like transmit spectrum bounds) simply by controlling hardware characteristics. D. Information Privacy The metrics used by regulatory agencies for determining A database service that holds spectral occupancy suitability become more complex with DSA. information could be tampered with or probed in order Governments are mandating spectrum efficiency when to gain information about the location of important considering purchase of spectrum-dependent systems [6], entities (e.g., Navy ships). An adversary could be a valid [12]. However, one of the findings of the PCAST report is CR that joins a network under normal conditions, but that the traditional metric used for determining spectrum requests spectrum occupancy information beyond what is efficiency, bits per second per hertz, has not guaranteed appropriate, such as information in a geographical area that all available spectrum is being used. New metrics need that the radio has no intention to be in. Although to be defined, and not just for efficiency. Other parameters database security is a well-researched area, the question are important, such as receiver performance, time taken to of how to provide information from the database without vacate , interference tolerance metrics, probability unintentionally disclosing sensitive information is an area that spectrum is available, etc. New models also have to be in need of further research. For example, military users developed to deal with issues such as propagation may not want their location or capability information in a characteristics. database. This could be a fundamental problem with applying a database approach to spectrum shared with C. Enforcement Methodologies military users. The traditional method of enforcing spectrum usage is Another issue deals with who is authorized to collect based on equipping engineers with spectrum analyzers and and analyze data coming from another radio. As an sending them to an area where violations are continuously example, collecting and analyzing spectrum data from a occurring. With a static allocation process, it is easy to military system is considered a felony in some countries. determine that any user transmitting in an unauthorized Does the presence of sensors on a radio in the same band as band is a violator. With DSA, the difficulty greatly a military system, and the ability to either store data or increases. Not only is every secondary user device a process data via cognitive engines on a radio, constitute a potential violator, but also they may only be causing a violation of those laws? If so, the impact could be that problem episodically, so having engineers sitting and systems that share spectrum with military radios may not waiting for an event could be very costly. be able to exploit learning (because of data storage), Research into mechanisms that could assist enforce- spectrum fingerprinting, or perhaps even be equipped with ment agencies takes several forms. There is research into a cognitive engine that could be used to process signals. It locating users by receive signal strength, time-of-arrival would also impact the ability to exploit collaboration differences, watermarking transmitters (inserting some- between nodes and/or spectrum managers. thingintothesignaltoprovideidentity),andspectral The 2013 Presidential Memorandum on Expanding fingerprinting (identifying radio characteristics unique to a America’s Leadership in Wireless Innovation states that transmitter). ‘‘All policies, practices, and templates shall be subject to Regulatory requirements specify a framework for safeguards reasonably necessary to protect classified, sharing spectrum bands that can be used for proactive sensitive, and proprietary data’’ [6]. A similar injunction enforcement using regulatory databases [2], [144], [145]. exists in the EU Commission Implementing Decision of The use of a database in this manner is foreseen by the FCC April 23, 2013, to ‘‘ensure the protection of information CDBS [59]. It contains a list of stations that require which is considered confidential or classified by a Member protection. state’’ [146]. Research into algorithms and approaches that Additional research is needed to decide the full details deal with the necessity of sharing position and capability of what should be included in a regulatory database, and information are needed to meet these requirements.

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E. Creating Confidence: Test Beds spectrum sensing, it is envisioned that the evolution of A serious challenge facing implementation of DSA LTE will lead toward use in shared spectrum. There is an systems is proving that the system will work as advertised. abundance of literature proposing CR and DSA schemes Incumbent users and regulatory agencies need confidence for LTE, in both frequency-division duplex and time- that dynamic sharing of spectrum will not cause harmful division duplex modes [148]. While most of the proposed interference to existing equipment before they will allow schemes involve spectrum sharing, it is possible to systems to be deployed. Commercial entities need to feel implement a simple version of dynamic spectrum sharing that opportunistic spectrum access is reliable, both from a by requiring all LTE base stations to query a spectrum technology standpoint and a regulatory standpoint, before occupancy database before transmitting. This database they will pursue significant investment. This dependency method will likely represent the first wave of DSA-enabled was recognized in the PCAST spectrum report. It LTE, simply because it does not require as many additions recommended that the NTIA and the NIST provide test to the specifications. services to support the development of policies and Release 10 introduced a feature known as carrier underlying technologies [2]. In terms of scale, a ‘‘test city’’ aggregation, which allows the user and base station to and a ‘‘mobile test service’’ were suggested as components. communicate on multiple blocks of spectrum, known as component carriers. These component carriers can be adjacent, nonadjacent and in the same band, or nonadja- VII. IMPLICATIONS FOR cent and in different bands. Each component carrier can FUTURE STANDARDS have a bandwidth of 1.4, 3, 5, 10, 15, or 20 MHz and a It is clear that regulators and commercial interests alike maximum of five component carriers can be aggregated (for a believe that spectrum allocations in the future will stress- max of 100 MHz). Initially, carrier aggregation will only be sharing mechanisms. IEEE 802.22 is one of the first DSA- specified for a few specific operating bands. This means that based standards, and is paving the road for next-generation the technology cannot be directly applied to any given piece DSA technology. The two market places that have proven to of spectrum that allows opportunistic sharing. However, it is be lucrative in the past, Wi-Fi and cellular, are the next tar- one step closer to realizing DSA-enabled LTE. gets in standards efforts. The IEEE 802.11 standard is getting An example scenario that combines carrier aggregation a DSA update in the form of 802.11af, and LTE is looking to and dynamic spectrum sharing involves an LTE network exploit its carrier aggregation feature for DSA. A brief which operates in spectrum owned by the network discussion of IEEE 802.11af, LTE, and cognitive radar follows. provider, but includes aggregate carriers in shared bands which turn on and off based on the spectrum availability. It A. IEEE 802.11af White-Fi is possible to turn off an aggregate carrier while the system IEEE 802.11af is a technical standard currently under is running, given that vital control information is carried development with the goal of providing Wi-Fi in the TV on the primary carrier operating in the network operator’s white space. The standard will define modifications to spectrum. Turning off ‘‘extra carriers’’ simply reduces the both the 802.11 physical layers and the 802.11 MAC layers, capacity of the link. Although LTE is not specifically a DSA to meet the legal requirements for channel access and technology, it may evolve into a technology with DSA coexistence in the unused spectrum between TV stations. capabilities, and features such as carrier aggregation and The TV occur below 1 GHz, which means SONs will surely aid in this evolution. 802.11af has the potential for much greater distances than the previous versions of 802.11. Future devices that include 802.11af technologies will most likely also include C. Cognitive Radar other Wi-Fi technologies such as 802.11ac and 802.11n. The idea of using cognition in radar systems is an area The physical layer of 802.11af is based on IEEE 802.11ac, of research seeing increasing interest in recent years except scaled down to work with 6-, 7-, and 8-MHz [149]–[151]. The basic idea is that performance improve- channels [147]. Multiple channels can be in an aggregated ments can be achieved over traditional radar systems contiguous or noncontiguous manner. One of the design through the added capabilities of observation, memory, requirements of 802.11af is an adjacent channel leakage and learning of the radar’s geographical, temporal, and ratio of À55 dB, which is much higher than the current spectral environments. More specifically, it is envisioned Wi-Fi requirements [12]. The MAC layer protocol will also that a cognitive radar system could, in real time, make be based on previous Wi-Fi technology, with the addition intelligent adjustments to its system parameters in order to of spectrum sensing and a method of communicating with deal with changes in its environment, to more closely track a central database containing occupancy information. its targets of interest, and to adjust for potential interference sources [152]. It is due to this last point that B. LTE and LTE-Advanced cognitive radar is thought of as a key technology for the Even though the 3GPP LTE and LTE-Advanced successful development of spectrum-sharing applications specifications do not include CR mechanisms such as in the government controlled radar bands.

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Fig. 7. Summary of practical issues for spectrum management.

D. Other Areas incumbents, and the business models of the secondary There is an ongoing debate within the public safety users, could see development of standards for some of the community about how to deal with the spectrum allocated other architectures (distributed supervision, or sense-only, to FirstNet [17] for building a United States-wide public systems). safety network. Building a complete network is a very expensiveproposition,andgiventhatitismostlikelytobe based on LTE, there have been a number of proposals for VIII. CONCLUSION thespectrumtobesharedbetweenpublicsafetyand commercial carriers. If this comes to pass, LTE standards There is currently a paradigm shift underway in the would be affected. management of RF spectrum. Regulatory bodies are Although hospitals have long been the place where you coming face to face with the realization that the current were most likely to be asked to turn off your cell phone, policies of fixed spectrum allocations are spectrally the hospital room of the future is destined to be one of the inefficient and undesirable given the current explosion densest RF environments anywhere. A large number of of demand for wireless technologies. Regulatory policy medical devices are moving toward wireless interfaces, and makers, as well as the research community at large, RFID tagging is beginning to be used to track equipment envision DSA technologies as one of the key enablers to within the hospital (e.g., to reduce costs of finding this move away from rigid spectrum assignments. equipment when it must be calibrated or updated as part The development of spectrum management systems is of a safety recall). Using strictly the ISM bands (e.g., Wi-Fi) still in its infancy and introduces unique issues typically will not be sufficient for the volumes of data produced in unconsidered in traditional systems. These issues will need these environments when doctors begin to place wearable to be addressed by equipment designers, network devel- medical monitoring devices on their patients. MBANs are opers, policy makers, and even end users to guarantee the first, but not likely the only, foray into spectrum sharing success. Given these facts, the purpose of this paper has for hospitals. been to review some of the immediate practical issues Given the convenience and cost reduction often inherent to the development of spectrum management afforded by going wireless, and the increased traffic flow systems utilizing CRs for DSA. A summary of the issues occasioned by machine-to-machine communications in the discussed can be found in Fig. 7. Internet of Things, it should be expected that new types of While this paper could not possibly cover all of the spectrum-sharing arrangements will be created in the possible practical issues, the authors are hopeful that it will h future. So far, we have seen the development of standards aid in the up-and-coming spectral evolution/revolution. for a centrally supervised database system (IEEE 802.22) and an unsupervised beacon-based system (IEEE 802.14.4j). We expect to see centrally supervised database systems for Acknowledgment LTE and for IEEE 801.11af. The former would manage a The authors would like to thank the many reviewers who potentially large number of bands from 1 to 3.5 GHz and the provided them with feedback about on how to approach some latter would manage TV white space. As other bands are of these topics, including M. Marcus, R. Farrell, P. Stanforth, considered, the legacy protection requirements of the S. Hasan, and R. Pavlak.

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ABOUT THE AUTHORS Stephen M. Dudley (Member, IEEE) received the Xiaofu Ma (Student Member, IEEE) received the B.Sc. degree in electrical engineering from the B.S. degree in electronics from Northwest Uni- University of Alberta, Edmonton, AB, Canada, in versity, Xi’an, China, in 2008 and the M.S. degree 1980 and the M.S. degree in electrical engineering in computer science from Tongji University, from Georgia Institute of Technology, Atlanta, GA, Shanghai, China, in 2011. Currently, he is working USA, in 1995. Currently, he is working toward the toward the Ph.D. degree in electrical engineering Ph.D. degree in electrical engineering at Virginia at Virginia Polytechnic Institute and State Univer- Polytechnic Institute and State University, sity,Blacksburg,VA,USA. Blacksburg, VA, USA, studying wireless networks His research interests include network optimi- for disaster recovery. zation, cognitive radio, dynamic spectrum access, and wireless healthcare. William Christopher Headley received the B.S. and M.S. degrees in electrical engineering (with first class honors) from Virginia Polytechnic Insti- tute and State University, Blacksburg, VA, USA, in Mahi Abdelbar graduated with honors and 2006 and 2009, respectively. He is a Virginia Tech received the M.S. degree from the Electronics Bradley Fellow alumnus, and is currently working and Communications Department, Engineering toward the Ph.D. degree in electrical engineering Faculty, Mansoura University, Mansoura, Egypt, with Wireless @ Virginia Tech. in 2010. Currently, she is working toward the Ph.D. His research interests include wireless com- degree in electrical engineering at the Wireless @ munications, signal detection and classification, VT laboratory, Electrical Engineering Department, signal parameter estimation, and collaborative spectrum sensing. Virginia Polytechnic Institute and State University, Blacksburg, VA, USA. Her research interests include distributed sig- Marc Lichtman (Student Member, IEEE) received nal detection and classification, spectrum sensing, and cognitive radio the B.S. and M.S. degrees in electrical engineering networks. from Virginia Polytechnic Institute and State University, Blacksburg, VA, USA, in 2011 and 2012, respectively, where he is currently working toward the Ph.D. degree, under the advisement of Aditya Padaki (Student Member, IEEE) received Dr.J.H.Reed. the B.S. degree in electronics and communication His research is focused on designing anti-jam engineering from PES Institute of Technology, approaches against sophisticated jammers, using Bangalore, India, in 2009 and the M.S. degree in machine learning techniques. He is also interested electrical engineering from Missouri University of in analyzing the vulnerability of LTE to jamming. Science and Technology, Rolla, MO, USA, in 2012. He is currently working toward the Ph.D. degree at Eyosias Yoseph Imana received the B.S. degree Wireless @ VT, Virginia Polytechnic Institute and in electrical engineering from Bahir Dar Universi- State University, Blacksburg, VA, USA. ty, Bahir Dar, Ethiopia, in 2007 and the M.S. degree His current research is on evolving receiver in electrical engineering from Florida Institute of performance metrics for efficient cognitive spectrum access. He is Technology, Melbourne, FL, USA, in 2009. Cur- interested in dynamic spectrum access, cognitive radio, multiple-input– rently, he is working toward the Ph.D. degree in multiple-output (MIMO) systems, radio-frequency (RF) system design, etc. electrical engineering at Virginia Polytechnic In- stitute and State University, Blacksburg, VA, USA. His research interest is radio-frequency (RF) front–ends of flexible radios and implementation Abid Ullah is currently working toward the Ph.D. degree in electrical of wireless devices. His paper on cognitive RF front–end control was engineering at Virginia Polytechnic Institute and State University, named as the best R&D track paper in the 2012 software-defined radio Blacksburg, VA, USA. forum. He is also a recipient of the Virginia innovation partnership I6 His research interests include database systems for spectrum grant to develop mobile software-defined radios. planning.

Vol. 102, No. 3, March 2014 | Proceedings of the IEEE 263 Dudley et al.: Practical Issues for Spectrum Management With Cognitive Radios

Munawwar M. Sohul received the B.Sc. degree in Jeffrey H. Reed (Fellow, IEEE) receivedtheB.S.E.E., electrical and electronics engineering from M.S.E.E., and Ph.D. degrees from the University of Bangladesh University of Engineering and Tech- California Davis, Davis, CA, USA, in 1979, 1980, and nology (BUET), Dhaka, Bangladesh and the M.Sc. 1987, respectively. degree in communication and signal processing Currently, he serves as Director of Wireless @ from Imperial College, London, U.K. Currently, he is VT, Virginia Polytechnic Institute and State Uni- working toward the Ph.D. degree in electrical versity, Blacksburg, VA, USA. He is the Founding engineering in the Bradley Department of Electri- Faculty member of the Ted and Karyn Hume cal and Computer Engineering, Virginia Polytech- Center for National Security and Technology and nic and State University, Blacksburg, VA, USA, served as its interim Director when founded in working with Dr. J. H. Reed. 2010. His book Software Radio: A Modern Approach to Radio Design was His research interest in wireless communication and signal processing published by Prentice-Hall. He is cofounder of Cognitive Radio Technologies includes carrier aggregation, self-organizing networks, spectrum shar- (CRT), a company commercializing of the cognitive radio technologies; Allied ing, and cognitive radios. Communications, a company developing technologies for 5G systems; and for Power Fingerprinting, a company specializing in security for embedded Taeyoung Yang (Member, IEEE) received the B.S. systems. and M.S. degrees in electronic engineering from Dr. Reed became Fellow to the IEEE for contributions to software Sung-Kyun-Kwan University, Korea, in 1997 and radio and communications signal processing and for leadership in 1999, respectively, and the M.S. and Ph.D. degrees engineering education, in 2005. He is also a Distinguished Lecturer for in electrical engineering from Virginia Polytechnic the IEEE Vehicular Technology Society. In 2013, he was awarded the Institute and State University, Blacksburg, VA, International Achievement Award by the Wireless Innovations Forum. In USA, in 2003 and 2012, respectively. 2012, he served on the President’s Council of Advisors of Science and He is currently a Research Scientist with the Technology Working Group that examines ways to transition federal Bradley Department of Electrical and Computer spectrum to allow commercial use and improve economic activity. Engineering, Virginia Polytechnic Institute and State University. He has strong theoretical background on radiation physics, co-site interference, and size-performance limits of wireless devices. Along with the theoretical background, he also has extensive hands-on experience in antennas, RF, sensors, and measurements. He developed fully functional prototypes to prove new technologies and demonstrate innovative wireless solutions. His current research empha- sis is on developing core technologies in the area of spectrum sharing and management, cognitive medical wireless infrastructure, medical software-defined radio user equipment, and medical cloud services. Collaborating with academic, nonprofit, and industry partners, he is leading Health Care of the Future research initiative at the Wireless @ Virginia Tech.

264 Proceedings of the IEEE | Vol. 102, No. 3, March 2014