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Random Access in Wireless Ad Hoc Networks for Throughput Maximization

机译:无线Ad Hoc网络中的随机访问以实现吞吐量最大化

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We consider the distributed random access algorithms for wireless ad hoc networks in which each node needs to tune its persistent probability so as to optimize its own the total throughput. First, we present an asynchronous algorithm for updating persistent probabilities and prices to avoid collision using local coordination. By casting this algorithm as a best response in a cooperative game, we characterize its convergence analytically. We further model that each node attempts to maximize a selfish local payoff function. We characterize the Nash equilibrium (NE) of the non-cooperative game and prove the convergence of a best response algorithm to the unique NE. Then we study the energy efficient throughput maximization problem when the wireless nodes are constrained by their battery power. Despite the inherent difficulty of non-separability of the constraint set, we propose a distributed primal-based algorithm. Its convergence is studied numerically
机译:我们考虑了用于无线自组织网络的分布式随机访问算法,其中每个节点都需要调整其持久性概率,以优化其自身的总吞吐量。首先,我们提出了一种异步算法,用于更新持久概率和价格,以避免使用局部协调发生冲突。通过将该算法转换为合作博弈中的最佳响应,我们可以分析其收敛性。我们进一步建模,每个节点都试图最大化自私的本地收益函数。我们刻画了非合作博弈的纳什均衡(NE),并证明了对唯一NE的最佳响应算法的收敛性。然后,我们研究了无线节点受电池电量约束时的高能效吞吐量最大化问题。尽管约束集具有不可分离性的内在困难,我们还是提出了一种基于分布式原始算法。对其收敛性进行了数值研究

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