Wireless local area networks (WLANs) based on IEEE 802.11 standards are becoming ubiquitous today and typically support multiple data rates. In such multi-rate WLANs, distributed medium access and rate adaptation are two key elements to achieve efficient radio resource utilization, especially in non-cooperative environments. In this paper, we present an analytical study on the non-cooperative multi-rate WLANs composed of selfish users jointly adjusting their data rate and contention window size at the medium access level to maximize their own throughput, irrespective of the impact of their selfish behaviors on overall system performance. Specifically, we develop an adapted Tit-For-Tat (TFT) strategy to guide the system to an efficient equilibrium in non-cooperative environments. We model the interactions among selfish users under the adapted TFT framework as a non-cooperative joint medium access and rate adaptation game. A systematic analysis is conducted on the structural properties of the game to provide insights on the interaction between rate adaptation and 802.11 medium access control in a competitive setting. We show that the game has multiple equilibria, which, after the equilibrium refinement process that we develop, reduce to a unique efficient equilibrium. We further develop a distributed algorithm to achieve this equilibrium and demonstrate that the equilibrium achieves the performance very close to the system optimum in a social perspective.
Cooperative Game-Theoretic Credit Assignment for Multi-Agent Policy Gradients via the Core
Key Laboratory of Intelligence, Games and Information Processing in Shaanxi Province（陕西省智能信息处理重点实验室）；Unmanned System Research Institute（无人系统研究院）；Northwestern Polytechnical University（西北工业大学）；School of Mathematics and Statistics（数学与统计学院）；Information Science Academy（信息科学学院）；China Electronics Technology Group Corporation（中国电子科技集团有限公司）
Co-Investment with Payoff-Sharing Mechanism for Cooperative Decision-Making in Network Design Games
Institute for Dynamic Systems and Control, ETH Zurich（苏黎世联邦理工学院动态系统与控制研究所）；Laboratory for Information and Decision Systems, Massachusetts Institute of Technology（麻省理工学院信息与决策系统实验室）
