The question of providing throughput guarantees through distributed scheduling, which has remained an open problem for some time, is addressed in this paper. It is shown that a simple distributed scheduling strategy, maximal scheduling, attains a guaranteed fraction of the maximum throughput region in arbitrary wireless networks. The guaranteed fraction depends on the "interference degree" of the network, which is the maximum number of transmitter-receiver pairs that interfere with any given transmitter-receiver pair in the network and do not interfere with each other. Depending on the nature of communication, the transmission powers and the propagation models, the guaranteed fraction can be lower-bounded by the maximum link degrees in the underlying topology, or even by constants that are independent of the topology. The guarantees are tight in that they cannot be improved any further with maximal scheduling. The results can be generalized to end-to-end multihop sessions. Finally, enhancements to maximal scheduling that can guarantee fairness of rate allocation among different sessions, are discussed. KeywordsFairness guarantees, maximal scheduling, throughput guarantees, wireless networks This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it. Abstract-The question of providing throughput guarantees through distributed scheduling, which has remained an open problem for some time, is addressed in this paper. It is shown that a simple distributed scheduling strategy, maximal scheduling, attains a guaranteed fraction of the maximum throughput region in arbitrary wireless networks. The guaranteed fraction depends on the "interference degree" of the network, which is the maximum number of transmitter-receiver pairs that interfere with any given transmitter-receiver pair in the network and do not interfere with each other. Depending on the nature of communication, the transmission powers and the propagation models, the guaranteed fraction can be lower-bounded by the maximum link degrees in the underlying topology, or even by constants that are independent of the topology. The guarantees are tight in that they cannot be improved any further with maximal scheduling. The results can be generalized to end-to-end multihop sessions. Finally, enhancements to maximal scheduling that can guarantee fairness of rate allocation among different sessions, are discussed.

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We design transmission strategies for medium access control (MAC) layer multicast that maximize the utilization of available bandwidth. Bandwidth efficiency of wireless multicast can be improved substantially by exploiting the feature that a single transmission can be intercepted by several receivers at the MAC layer. The multicast nature of transmissions, however, changes the fundamental relations between the quality of service (QoS) parameters, throughput, stability, and loss, e.g., a strategy that maximizes the throughput does not necessarily maximize the stability region or minimize the packet loss. We explore the tradeoffs among the QoS parameters, and provide optimal transmission strategies that maximize the throughput subject to stability and loss constraints. The numerical performance evaluations demonstrate that the optimal strategies significantly outperform the existing approaches. KeywordsMulticast, optimization, scheduling, stability, stochastic control, throughput, wireless This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.This journal article is available at ScholarlyCommons: http://repository.upenn.edu/ese_papers/148 1954 IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 51, NO. 6, JUNE 2005 Wireless Multicast: Theory and Approaches Prasanna Chaporkar, Student Member, IEEE, and Saswati Sarkar, Member, IEEE Abstract-We design transmission strategies for medium access control (MAC) layer multicast that maximize the utilization of available bandwidth. Bandwidth efficiency of wireless multicast can be improved substantially by exploiting the feature that a single transmission can be intercepted by several receivers at the MAC layer. The multicast nature of transmissions, however, changes the fundamental relations between the quality of service (QoS) parameters, throughput, stability, and loss, e.g., a strategy that maximizes the throughput does not necessarily maximize the stability region or minimize the packet loss. We explore the tradeoffs among the QoS parameters, and provide optimal transmission strategies that maximize the throughput subject to stability and loss constraints. The numerical performance evaluations demonstrate that the optimal strategies significantly outperform the existing approaches.

In broadcast fading channel, channel variations can be exploited through what is referred to as multiuser diversity and opportunistic scheduling for improving system performance. To achieve the gains promised by this kind of diversity, the transmitter has to accurately track the channel variations of the various receivers, which consumes resources (time, energy, bandwidth), and thus reduces the resources remaining for effective data transmissions. The transmitter may decide not to acquire or probe the channel conditions of certain receivers, either because these receivers are presumably experiencing severe fading, or because the transmitter wishes to spare resources for data transmissions. It may also decide to transmit to a receiver without probing its channel; in such cases, the transmitter guesses the channel state, which often results in a reduction of the transmission rate compared to when the transmitter knows the channel state. Ultimately, the transmitter has to decide to which receiver it should transmit. In this paper, we identifying the joint probing and transmission strategies realizing the optimal trade-off between the channel state acquisition and the effective data transmission. The objective is to maximize the system throughput. Finally, we propose several extensions of the proposed strategy, including a scheme to maximize the system utility and a scheme to ensure the system stability.

Opportunistic scheduling is a key mechanism for improving the performance of wireless systems. However, this mechanism requires that transmitters are aware of channel conditions (or CSI, Channel State Information) to the various possible receivers. CSI is not automatically available at the transmitters, rather it has to be acquired. Acquiring CSI consumes resources, and only the remaining resources can be used for actual data transmissions. We explore the resulting trade-off between acquiring CSI and exploiting channel diversity to the various receivers. Specifically, we consider a system consisting of a transmitter and a fixed number of receivers/users. An infinite buffer is associated to each receiver, and packets arrive in this buffer according to some stochastic process with fixed intensity. We study the impact of limited channel information on the stability of the system. We characterize its stability region, and show that an adaptive queue length-based policy can achieve stability whenever doing so is possible. We formulate a Markov Decision Process problem to characterize this queue lengthbased policy. In certain specific and yet relevant cases, we explicitly compute the optimal policy. In general case, we provide a scheduling policy that achieves a fixed fraction of the system's stability region. Scheduling with limited information is a problem that naturally arises in cognitive radio systems, and our results can be used in these systems.