Distributed Channel Probing for Efficient Transmission Scheduling in Wireless Networks
Distributed Channel Probing for Efficient Transmission Scheduling in Wireless Networks
复制标题
用于无线网络中高效传输调度的分布式信道探测
DOI：
10.1109/tmc.2014.2346757
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发表时间：
2015
影响因子：
7.9
通讯作者：
A. Eryilmaz
中科院分区：
文献类型：
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作者：
Bin Li;A. Eryilmaz
在无线衰落信道的机会调度中，所有用户在每次传输决策前都要持续地估计信道质量，这是一种费时费力的问题。这一观察结果促使我们了解，在显著减少信道探测需求的情况下，在没有竞争用户之间的集中协调的情况下，是否以及如何实现机会主义收益。为此，我们首先研究一个简单的场景，该场景促使我们考虑一般设置，并开发适合分布式实现的探测和传输方案。在描述了探测约束下的最大可达吞吐量区域后，给出了一种最优探测算法。注意到集中式解决方案实现中的困难，我们开发了一种新的顺序贪婪探测（SGP）算法，该算法自然非常适合物理实现和分布式操作。我们证明了SGP算法在对称和独立的ON-OFF衰落信道的重要场景下是最优的。然后，我们研究了SGP算法在一般衰落信道中的一种变体，得到了它的效率比作为信道统计量和速率的显式函数，并注意到它在对称和独立的ON-OFF衰落场景中的紧密性。我们进一步讨论了使用Fast-CSMA技术实现这些贪心解的分布式实现。
It is energy-consuming and operationally cumbersome for all users to continuously estimate the channel quality before each transmission decision in opportunistic scheduling over wireless fading channels. This observation motivates us to understand whether and how opportunistic gains can still be achieved with significant reductions in channel probing requirements and without centralized coordination amongst the competing users. To that end, we first study a simple scenario that motivates us to consider the general setup and develop probing and transmission schemes that are amenable to distributed implementation. After characterizing the maximum achievable throughput region under the probing constraints, we provide an optimal probing algorithm. Noting the difficulties in the implementation of the centralized solution, we develop a novel Sequential Greedy Probing (SGP) algorithm, which is naturally well-suited for physical implementation and distributed operation. We show that the SGP algorithm is optimal in the important scenario of symmetric and independent ON-OFF fading channels. Then, we study a variant of the SGP algorithm in general fading channels to obtain its efficiency ratio as an explicit function of the channel statistics and rates, and note its tightness in the symmetric and independent ON-OFF fading scenario. We further discuss the distributed implementation of these greedy solutions by using the Fast-CSMA technique.