Random Access Game and Medium Access Control Design

Motivated partially by a control-theoretic viewpoint, we propose a game-theoretic model, called random access game, for contention control. We characterize Nash equilibria of random access games, study their dynamics, and propose distributed algorithms (strategy evolutions) to achieve Nash equilibria. This provides a general analytical framework that is capable of modeling a large class of system-wide quality-of-service (QoS) models via the specification of per-node utility functions, in which system-wide fairness or service differentiation can be achieved in a distributed manner as long as each node executes a contention resolution algorithm that is designed to achieve the Nash equilibrium. We thus propose a novel medium access method derived from carrier sense multiple access/collision avoidance (CSMA/CA) according to distributed strategy update mechanism achieving the Nash equilibrium of random access game. We present a concrete medium access method that adapts to a continuous contention measure called conditional collision probability, stabilizes the network into a steady state that achieves optimal throughput with targeted fairness (or service differentiation), and can decouple contention control from handling failed transmissions. In addition to guiding medium access control design, the random access game model also provides an analytical framework to understand equilibrium and dynamic properties of different medium access protocols

A Game-Theoretic Framework for Medium Access Control

In this paper, we generalize the random access game model, and show that it provides a general game-theoretic framework for designing contention based medium access control. We extend the random access game model to the network with multiple contention measure signals, study the design of random access games, and analyze different distributed algorithms achieving their equilibria. As examples, a series of utility functions is proposed for games achieving the maximum throughput in a network of homogeneous nodes. In a network with n traffic classes, an N-signal game model is proposed which achieves the maximum throughput under the fairness constraint among different traffic classes. In addition, the convergence of different dynamic algorithms such as best response, gradient play and Jacobi play under propagation delay and estimation error is established. Simulation results show that game model based protocols can achieve superior performance over the standard IEEE 802.11 DCF, and comparable performance as existing protocols with the best performance in literature

Medium Access Control and Network Coding for Wireless Information Flows

This dissertation addresses the intertwined problems of medium access control (MAC) and network coding in ad hoc wireless networks. The emerging wireless network applications introduce new challenges that go beyond the classical understanding of wireline networks based on layered architecture and cooperation. Wireless networks involve strong interactions between MAC and network layers that need to be jointly specified in a cross-layer design framework with cooperative and non-cooperative users. For multi-hop wireless networks, we first rediscover the value of scheduled access at MAC layer through a detailed foray into the questions of throughput and energy consumption. We propose a distributed time-division mechanism to activate dynamic transmitter-receiver assignments and eliminate interference at non-intended receivers for throughput and energy-efficient resource allocation based on stable operation with arbitrary single-receiver MAC protocols. In addition to full cooperation, we consider competitive operation of selfish users with individual performance objectives of throughput, energy and delay. We follow a game-theoretic approach to evaluate the non-cooperative equilibrium strategies at MAC layer and discuss the coupling with physical layer through power and rate control. As a cross-layer extension to multi-hop operation, we analyze the non-cooperative operation of joint MAC and routing, and introduce cooperation stimulation mechanisms for packet forwarding. We also study the impact of malicious transmitters through a game formulation of denial of service attacks in random access and power-controlled MAC. As a new networking paradigm, network coding extends routing by allowing intermediate transmitters to code over the received packets. We introduce the adaptation of network coding to wireless environment in conjunction with MAC. We address new research problems that arise when network coding is cast in a cross-layer optimization framework with stable operation. We specify the maximum throughput and stability regions, and show the necessity of joint design of MAC and network coding for throughput and energy-efficient operation of cooperative or competitive users. Finally, we discuss the benefits of network coding for throughput stability in single-hop multicast communication over erasure channels. Deterministic and random coding schemes are introduced to optimize the stable throughput properties. The results extend our understanding of fundamental communication limits and trade-offs in wireless networks

Near-Optimal Deviation-Proof Medium Access Control Designs in Wireless Networks

Distributed medium access control (MAC) protocols are essential for the proliferation of low cost, decentralized wireless local area networks (WLANs). Most MAC protocols are designed with the presumption that nodes comply with prescribed rules. However, selfish nodes have natural motives to manipulate protocols in order to improve their own performance. This often degrades the performance of other nodes as well as that of the overall system. In this work, we propose a class of protocols that limit the performance gain which nodes can obtain through selfish manipulation while incurring only a small efficiency loss. The proposed protocols are based on the idea of a review strategy, with which nodes collect signals about the actions of other nodes over a period of time, use a statistical test to infer whether or not other nodes are following the prescribed protocol, and trigger a punishment if a departure from the protocol is perceived. We consider the cases of private and public signals and provide analytical and numerical results to demonstrate the properties of the proposed protocols.Comment: 14 double-column pages, submitted to ACM/IEEE Trans Networkin

Cognitive Medium Access: Exploration, Exploitation and Competition

This paper establishes the equivalence between cognitive medium access and the competitive multi-armed bandit problem. First, the scenario in which a single cognitive user wishes to opportunistically exploit the availability of empty frequency bands in the spectrum with multiple bands is considered. In this scenario, the availability probability of each channel is unknown to the cognitive user a priori. Hence efficient medium access strategies must strike a balance between exploring the availability of other free channels and exploiting the opportunities identified thus far. By adopting a Bayesian approach for this classical bandit problem, the optimal medium access strategy is derived and its underlying recursive structure is illustrated via examples. To avoid the prohibitive computational complexity of the optimal strategy, a low complexity asymptotically optimal strategy is developed. The proposed strategy does not require any prior statistical knowledge about the traffic pattern on the different channels. Next, the multi-cognitive user scenario is considered and low complexity medium access protocols, which strike the optimal balance between exploration and exploitation in such competitive environments, are developed. Finally, this formalism is extended to the case in which each cognitive user is capable of sensing and using multiple channels simultaneously.Comment: Submitted to IEEE/ACM Trans. on Networking, 14 pages, 2 figure