Dynamic Bandwidth Allocation Algorithms for High-Speed Data Wireless Networks Matthew Andrews, Simon C

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Dynamic Bandwidth Allocation Algorithms for High-Speed Data Wireless Networks Matthew Andrews, Simon C ♦ Dynamic Bandwidth Allocation Algorithms for High-Speed Data Wireless Networks Matthew Andrews, Simon C. Borst, Francis Dominique, Predrag R. Jelenkovic, Krishnan Kumaran, K. G. Ramakrishnan, and Philip A. Whiting Next-generation wireless networks are expected to support a wide range of high- speed data services, with Web browsing as one of the major applications. Although high data rates have been shown feasible in a single-user setting, the resource allo- cation issues that arise in a multiple-user context remain extremely challenging. Compared with voice, data traffic is typically more bursty, while the users are less sensitive to delay. These characteristics require resource allocation strategies to oper- ate in a fundamentally different manner if the spectrum is to be used efficiently. In this paper we propose several algorithms for scheduling the efficient transmission of data to multiple users. As a new feature, the various schemes exploit knowledge of the buffer contents to achieve high throughput, while maintaining fairness by pro- viding quality of service (QoS) to individual users. The proposed algorithms are back- ward compatible with existing cellular and personal communications services (PCS) standards such as IS-136. They provide a powerful approach to improving spectrum efficiency in forthcoming high-speed data cellular services. The extensive simulation experiments we present in this paper demonstrate that the algorithms significantly outperform conventional schemes. Introduction Present mobile cellular systems have only a lim- modest bandwidth requirements of a few megahertz. ited ability to transmit data, a fact that has been To understand our approach, the reader must bear observed by I. Alanko et al.1 and C. J. Mathias.2 For in mind two important distinctions between voice and example, the Global System for Mobile data traffic. First, data traffic is much more bursty than Communications (GSM) and IS-95 standards permit a voice traffic. Second, data traffic has different quality- transmission rate up to about 10 kb/s. This rate, how- of-service (QoS) requirements than those of voice traf- ever, is too low to satisfy the requirements of many fic. On the one hand, data traffic is much more tolerant applications. In this paper we present algorithms for to delay than voice traffic; response times of several dynamically allocating carriers to mobile units to pro- seconds are acceptable for data, whereas voice signals vide peak rates on the order of 400 kb/s. These algo- can only be delayed a fraction of a second. On the rithms can be implemented in conjunction with a other hand, data is much more sensitive to bit errors, group of narrowband time division multiple access requiring error rates of 10-6, whereas voice can be satis- (TDMA) carriers, such as the North American IS-136 factorily transmitted with 10-3. system or the European GSM system. Indeed, they These distinctions led us to very different can be used in existing networks and operated within approaches for allocating bandwidth. In particular, the 30 Bell Labs Technical Journal ◆ July–September 1998 allocation of a dedicated connection to a data user is Panel 1. Abbreviations, Acronyms, and Terms less reasonable than to a voice user. A low-speed con- nection produces delays that are unacceptably high; a DCA—dynamic channel assignment high-speed connection reduces delay, but cannot be FCA—fixed channel assignment GSM—Global System for Mobile used efficiently because of the bursty nature of data Communications traffic. However, the tolerance of data applications to ILP—integer linear program delay makes it possible to coordinate base stations and LP—linear program to schedule transmissions. Such an approach has also MSC—mobile switching center been suggested by J.-P. M. G. Linnartz,3 who proposed PCS—personal communications services tight synchronization at the time slot level, to be used QoS—quality of service along with a reservation scheme. Linnartz also TDMA—time division multiple access describes an alternative collision resolution approach.3 Of course, sophisticated scheduling would not be distance according to worst-case conditions, making it necessary if fixed channel assignment (FCA) provided unnecessary to obtain on-line propagation or interfer- an adequate QoS at a cost acceptable to network oper- ence measurements. The sole problem remaining is ators. This is not the case, however. In FCA, the base scheduling, which is subject to these reuse constraints. stations are partitioned into reuse groups—that is, Unfortunately, the optimal solution to such a schedul- groups of mutually non-interfering cells—and the car- ing problem is not known. Furthermore, even if the riers are statically divided among the reuse groups. solution were known, its complexity would make it Because the carriers are allocated on a fixed basis, the impractical to implement. approach lacks flexibility. When the number of mobile In our approach to this problem, we devised a units has reached the maximum that can be supported number of heuristics, each of which determines carrier by the carriers allocated to a base station, further allocations to base stations for a fixed period based on requests for service must be rejected. In reality, of the number of packets awaiting transmission. Once course, a simple reallocation of carriers might have the carriers are allocated, a common algorithm deter- made it possible to support these extra mobile units at mines how they are used to transmit the mobile pack- little cost to other network users. ets. J. M. Harris and S. P. Kumar4 address the related A similar difficulty arises if packets build up at a and easier question of how to schedule the transmis- particular base station; this can occur even if the sion of a given set of packets onto carriers whose allo- mobile units are evenly distributed. Once again, extra cation to base stations has already been determined. carriers cannot be allocated because the number at The model in Harris and Kumar4 includes the possibil- each base station is fixed, even though few packets are ity that mobile units are able to receive packets from being presented for transmission at base stations more than one base station, which is not considered nearby. This is in contrast to voice systems, where the here. Closely coupled in the circumstances described peak bandwidth requirements are fixed at a relatively in Harris and Kumar are the dual problems of how to low level. Thus, the inefficiency of FCA in allocating assign carriers to base stations and then assign these spectrum precludes its use by operators. carriers to mobile units. The algorithms we present here are for wireless The rest of this paper is organized as follows. First networks operated according to a frequency reuse we describe the model set-up and the issues surround- plan, but they do allow for dynamic channel assign- ing our choice for the source model. The next three ment (DCA). In DCA, carriers are not statically sections propose a number of heuristic carrier alloca- assigned to base stations; they may be diverted in a tion algorithms defined within a common format. In dynamic fashion from cells with traffic lulls to cells the section that follows, we evaluate the communica- with traffic peaks. A frequency reuse plan limits the tion requirements and computational complexity of interference between co-channel users by geographic the various algorithms. Next, we present a series of Bell Labs Technical Journal ◆ July–September 1998 31 simulation experiments, in which we consider the start of the t-th time slot, that is, the number of pack- impact of the burstiness and the duration of the sched- ets for user i waiting for transmission. The queue uling interval on the delay and throughput perfor- lengths evolve over time as mance. We conclude with our expectations for =+[] −+ , QAQZit()+1 it it it next-generation wireless networks. + where [z] := max {z, 0} and Ait is the number of pack- Model Description ets that arrive for user i during the t-th time slot. We consider a wireless network of N base stations Suppose that a packet for user i arrives in a queue ′ supporting M users. Packets destined for the users of length Qit′ during the t -th time slot. The delay arrive at the serving base station, where they are experienced by that packet, measured in time slots, is queued until they are transmitted. (Throughout, we then defined to be (t ′′ – t ′), with focus on the stream of packets from the base station t ′′:. = ≥ down to the users. We do not consider the flow of tt:ZQmin ∑ it it ′ =′+ packets from the users up to the base station.) The tt 1 base stations share a pool of K orthogonal carriers for We now discuss the traffic model. The most basic transmitting packets down to the users. Transmission statistical model that can capture data “burstiness” and occurs in a slotted fashion, with exactly one packet a complex dependency structure is the so-called transmitted on a single carrier during a time slot. “on-off model,” first investigated by J. W. Cohen6 and Base stations may reuse carriers subject to certain M. Rubinovitch.7 For two-state Markov (fluid) on-off interference constraints. We assume the reuse con- models, D. Anick, D. Mitra, and M. M. Sondhi8 ana- straints may be described in the form of an interference lyzed the impact of the burstiness on queuing perfor- graph, with the vertices corresponding to the base sta- mance. Subsequent studies explored more general tions and the edges representing the pairs of interfer- Markov models with finite state space. These led to the ing base stations. Thus, if the interference graph equivalent-bandwidth theory for Markovian (or in contains the edge { j1, j2 }, then base stations j1 and j2 general exponentially bounded) arrival processes, are barred from transmitting on the same carrier in the which was treated by A.
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