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Service Discovery and Device Identification in Cognitive Radio

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Service Discovery and Device Identification in Cognitive Radio 1 Service Discovery and Device Identification in Cognitive Radio Networks Rob Miller, Wenyuan Xu, Pandurang Kamat, Wade Trappe Wireless Information Network Laboratory (WINLAB), Rutgers University. Email: f wenyuan, pkamat, trappe [email protected] Abstract— Cognitive Radios (CR) will be able to commu- incompatible. Such communication can aid in interfer- nicate adaptively in an effort to optimize spectral efficiency. ence avoidance and therefore result in more efficient An integral step towards this goal involves obtaining a spectral collaboration. Cognitive radios (CR) achieve this representative view of the various services operating in level of cross-protocol communication since they expose a local area. Although it is possible to load different the lower-layers of the protocol stack to researchers and software modules to identify each potential service, such an approach is needlessly inefficient. Instead, rather than use developers. a collection of complete protocols on a CR, we believe that Because cognitive radios support dynamic physical it is essential to have a separate identification module that layer adaptation, future wireless networks will consist of is capable of reliably identifying services and devices while various wireless devices communicating with each other minimizing the code needed. In particular, by effectively using one or more protocols. Figure 1 shows a future leveraging protocol-specific properties, we show that it is wireless network where WiFi and Bluetooth devices are possible to utilize data from narrowband spectral sampling in order to identify broader band services and individual operating amongst cognitive radios. In this scenario, devices. We demonstrate the feasibility of such service and WiFi device W can communicate with CR C and CR device identification using GNU Radio and the Universal D via 802.11. Bluetooth device T can receive packets Software Radio Peripheral (USRP) platform by identifying from CR E and CR F using 802.15, while CR D and radio services in the industrial, scientific, and medical CR E can communicate via 802.11, 802.15 or any other (ISM) radio band. Further, we show that physical layer protocol they desire. The success of communication signatures may be used to reliably identify devices, thereby between these devices depends on many factors, such allowing CRs to exploit physical layer information in as the availability of the spectrum and the interference support of basic authentication functionality. conditions in the region. A CR may influence these Index Terms— Cognitive Radio, GNU Radio, USRP, factors with knowledge of the protocols and services that Spectral Sensing. the existing wireless devices can support. In addition, it would be advantageous for a CR to know how many I. INTRODUCTION networks exist, how many users are associated with each network, and even certain properties about the devices Traditional communication systems and devices are themselves. To achieve this level of information, it is heavily constrained. Many functions associated with the essential for a cognitive radio to gather an accurate physical (PHY) layer (e.g. modulation) are hard-coded picture of the RF environment. in hardware, and numerous operations in the media access control (MAC) layer are protected in firmware. In this paper we investigate the problem of service Furthermore, it is infeasible to alter the protocol bound to discovery, where CRs identify different network services these devices once they are manufactured. For example, (e.g. Bluetooth, WiFi), and device identification, where a typical WiFi (IEEE 802.11) PCMCIA card cannot CRs identify distinct wireless devices and networks. be reprogrammed to communicate with a device that Service discovery and device identification provide the employs the Bluetooth (IEEE 802.15.1) protocol. This is necessary building blocks for constructing efficient and true even though they use the same “open spectrum” (i.e. trustworthy CR networks. These processes can be per- 2.4 GHz). As wireless devices become more and more formed in the PHY layer or the MAC layer by a CR. pervasive, problems of device-coexistence are inevitable. The rest of the paper is organized as follows. Sec- Not only will devices with different static-protocols be tion II motivates the problem and describes the system incapable of communicating with each other, but they model. Section III focuses on service discovery, while also pose the risk of interference [1]. It is therefore Section IV illustrates device identification using a cur- desirable to have a generic platform that can bridge the rent Software Defined Radio (SDR) platform. Finally, communication gap between devices that are otherwise Section V summarizes our results. 2 ² Provide access to both the PHY and the MAC layer. WiFi ² Give more control over intra-device and inter-device Bluetooth interference. WiFi Bluetooth ² Allow for re-use of processed data for different Cognitive Radio protocols. ² Don’t need to employ a full implementation of a protocol. Instead, as we shall show later, CRs can extract the desired information by leveraging only Fig. 1. A future cognitive radio network will be composed of a small portions of the protocols and/or using only broad array of simple-protocol devices, as well as cognitive radios narrowband data! capable of adjusting their protocol stack. The capabilities of CR networks are closely tied to the II. MOTIVATION technology of the underlying SDR platforms. Currently, there are several platforms that possess the processing Cognitive radios will play an integral role in the power and flexibility needed to support spectrum sens- success of future wireless networks. By taking advantage ing, flexible waveform generation, spectrum negotiation, of information gathered during spectral sensing, cogni- and other functions envisioned for true cognitive func- tive radios will foster communication between protocol- tionality. Notable amongst these platforms are the Rice disparate devices. CRs will also have the power to WARP platform [3], the high-performance cognitive intelligently guide decisions within existing networks, radio platform being developed by WINLAB, Georgia and may also conduct spectrally-efficient operations with Tech, and Lucent [4], and the the small form factor SDR other CRs. Clearly, an essential technological require- platform from Texas Instruments [5]. ment of a CR is accurate service discovery and device identification. However, a natural question that arises is whether cognitive radios are needed to achieve this goal, B. Security Concerns and whether a powerful PC with the appropriate dongles Physical/network layer adaptability, coupled with the provide equivalent functionality. open-source nature of supporting software, makes a cognitive radio a powerful but dangerous device. It is A. Why Cognitive Radio? easily conceivable that inexpensive and widely avail- able CRs could become an ideal platform for abuse. While much functionality can be obtained by em- It is therefore essential that next generation wireless ploying multiple radio dongles (e.g. WiFi by way of platforms have methods to ensure that the radio device PCMCIA card, Bluetooth via a USB dongle), many and the implementations of their lower layer protocols shortcomings and limitations exist: are trustworthy, and that all CRs are held accountable ² The number of dongles/peripherals a PC can sup- for not following locally acceptable spectrum etiquette. port limits the number of supportable protocols. Towards this goal, we have proposed TRIESTE (A ² Dongles may interfere with each other. Trusted Radio Infrastructure for Enforcing SpecTrum ² Dongles connected to the same PC redo much of the Etiquettes) in [6], which employs two levels of eti- same processing (e.g. energy detection, filtering). quette enforcement mechanisms. One is an on-board ² More dongles use more system power. enforcement mechanism, while the other is an external ² Dongles do not give full access to the PHY layer! infrastructure consisting of police agents that monitor While much can be gained by analyzing MAC layer the radio environment and punish CRs if violations are information, it may be more advantageous to consider detected. raw PHY layer information [2]. In particular, a simple At the heart of TRIESTE, and any other viable secu- consequence of the data processing inequality is the rity mechanism for CR networks, is the ability to identify implication that there is more information contained in both the services and the individual devices that are a PHY layer waveform than in the MAC-layer infor- operating in a region. The ability to identify services will mation that arises as a consequence of this waveform. not only allow individual devices to discover potential Concrete examples of PHY layer information that are networks to join, but will also allow users or external useful for basing CR decisions upon, and are not readily monitoring devices to detect the operation of prohibited available at higher layers using the radio dongles, include networks (e.g. a Bluetooth network operating in a region characteristics such as amplitude variations, frequency that is deemed WiFi-only). Further, being able to identify drifts, and phase offsets. Considering the limitations and individual devices in a manner that is not reliant upon constraints of a multi-dongle solution, it is clear that CRs higher-layer authenticators (e.g. certificates) is essential are a much better choice. Cognitive radios: to rapid anomaly detection and response mechanisms. 3 2465 2465.5 2466 2466.5 2467 2467.5 Frequency (MHz) 2468 2468.5 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 Time (s) Fig. 3. Spectrogram of the ISM band centered at 2467 MHz and Fig. 2. The experiment setup. spanning 4 MHz. 2465 C. System Details 2465.5 The SDR platform used within the context of this 2466 ← Bluetooth paper consists of GNU Radio, the USRP board, and 2466.5 the RFX-2400 daughterboard (shown in Figure 2). GNU 2467 WiFi → Radio is an open source, free software toolkit that pro- 2467.5 vides a library of signal processing blocks for developing Frequency (MHz) communications systems and experiments.
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