arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 0908.2941cs.ITmath.IT
收藏

有限状态马尔可夫衰落信道下S-ALOHA网络的时延敏感分布式功率和传输门限控制

Delay-Sensitive Distributed Power and Transmission Threshold Control for S-ALOHA Network with Finite State Markov Fading Channels

Huang Huang, Vincent K. N. Lau

摘要:

本文研究了FSMC衰落信道下S-ALOHA网络中时延敏感的功率和传输门限控制设计。随机接入系统由具有K个竞争用户的接入点组成,每个竞争用户可以访问本地信道状态信息(CSI)和队列状态信息(QSI)以及来自接入点的公共反馈(ACK/NAK/冲突)。我们试图推导出延迟-最优控制策略(由阈值和功率控制组成)。该优化问题属于无记忆策略K-agent无限时域分散马尔可夫决策过程(DEC-MDP),找到最优策略是计算上难以解决的。为了获得一个可行的和低复杂度的解决方案,我们重铸的优化问题分为两个子问题,即功率控制和阈值控制问题。对于给定的阈值控制策略,功率控制问题被分解为单用户的简化状态MDP,因此总体复杂度为O(N/J),其中N和J是缓冲区大小和CSI状态的基数。对于门限控制问题,我们利用冲突信道的一些特殊结构和公共反馈信息来推导出一个低复杂度的解决方案。所提出的设计的延迟性能示出相对于传统的吞吐量优化方法S-ALOHA有很大的增益。

英文摘要:

In this paper, we consider the delay-sensitive power and transmission threshold control design in S-ALOHA network with FSMC fading channels. The random access system consists of an access point with K competing users, each has access to the local channel state information (CSI) and queue state information (QSI) as well as the common feedback (ACK/NAK/Collision) from the access point. We seek to derive the delay-optimal control policy (composed of threshold and power control). The optimization problem belongs to the memoryless policy K-agent infinite horizon decentralized Markov decision process (DEC-MDP), and finding the optimal policy is shown to be computationally intractable. To obtain a feasible and low complexity solution, we recast the optimization problem into two subproblems, namely the power control and the threshold control problem. For a given threshold control policy, the power control problem is decomposed into a reduced state MDP for single user so that the overall complexity is O(NJ), where N and J are the buffer size and the cardinality of the CSI states. For the threshold control problem, we exploit some special structure of the collision channel and common feedback information to derive a low complexity solution. The delay performance of the proposed design is shown to have substantial gain relative to conventional throughput optimal approaches for S-ALOHA.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑