Applications of Repeated Games in Wireless Networks: A Survey

A repeated game is an effective tool to model interactions and conflicts for players aiming to achieve their objectives in a long-term basis. Contrary to static noncooperative games that model an interaction among players in only one period, in repeated games, interactions of players repeat for multiple periods; and thus the players become aware of other players' past behaviors and their future benefits, and will adapt their behavior accordingly. In wireless networks, conflicts among wireless nodes can lead to selfish behaviors, resulting in poor network performances and detrimental individual payoffs. In this paper, we survey the applications of repeated games in different wireless networks. The main goal is to demonstrate the use of repeated games to encourage wireless nodes to cooperate, thereby improving network performances and avoiding network disruption due to selfish behaviors. Furthermore, various problems in wireless networks and variations of repeated game models together with the corresponding solutions are discussed in this survey. Finally, we outline some open issues and future research directions.Comment: 32 pages, 15 figures, 5 tables, 168 reference

Distributed CSMA with pairwise coding

We consider distributed strategies for joint routing, scheduling, and network coding to maximize throughput in wireless networks. Network coding allows for an increase in network throughput under certain routing conditions. We previously developed a centralized control policy to jointly optimize for routing and scheduling combined with a simple network coding strategy using max-weight scheduling (MWS) [9]. In this work we focus on pairwise network coding and develop a distributed carrier sense multiple access (CSMA) policy that supports all arrival rates allowed by the network subject to the pairwise coding constraint. We extend our scheme to optimize for packet overhearing to increase the number of beneficial coding opportunities. Simulation results show that the CSMA strategy yields the same throughput as the optimal centralized policy of [9], but at the cost of increased delay. Moreover, overhearing provides up to an additional 25% increase in throughput on random topologies.United States. Dept. of Defense. Assistant Secretary of Defense for Research & EngineeringUnited States. Air Force (Air Force Contract FA8721-05-C-0002

“CSMA-Based Link Scheduling in Multihop MIMO Networks using SINR Model ”

The main aim of this study to resolve the problem of distributed scheduling in multi-hop MIMO networks. We will first develop a “MIMO pipe” model which will provide the required SINR , which gives the rate-reliability tradeoff in MIMO communications.Here we are going to study development of CSMA-based MIMO-pipe scheduling especially under the SINR model.We are going to choose the SINR model over the conventionally studied matching or protocol-based interference models because it has ability to capture the impact of interference in wireless networks. Here each node is equipped with an antenna array. In CSMA based scheduling, nodes will first sense the channel activity before attempting transmissions, whenever the channel is sensed to be idle, the nodes will continue with data transmissions. When the channel is detected to be busy, the nodes have to wait for a random amount of backoff time before reattempting the transmission.We will study that protocol model based throughput-optimal CSMA based scheduling, would not work well under the SINR model because its has dynamic and intrinsic link coupling. To tackle this challenge,CSMA-based MIMO-pipe scheduling is develpoed in both discrete-time system and continuous-time system

Towards a System Theoretic Approach to Wireless Network Capacity in Finite Time and Space

In asymptotic regimes, both in time and space (network size), the derivation of network capacity results is grossly simplified by brushing aside queueing behavior in non-Jackson networks. This simplifying double-limit model, however, lends itself to conservative numerical results in finite regimes. To properly account for queueing behavior beyond a simple calculus based on average rates, we advocate a system theoretic methodology for the capacity problem in finite time and space regimes. This methodology also accounts for spatial correlations arising in networks with CSMA/CA scheduling and it delivers rigorous closed-form capacity results in terms of probability distributions. Unlike numerous existing asymptotic results, subject to anecdotal practical concerns, our transient one can be used in practical settings: for example, to compute the time scales at which multi-hop routing is more advantageous than single-hop routing