在阻塞的无线信道上使链路传输质量最大化的在线算法

R. Kannan, Shuangqing Wei, C. Busch, A. Vasilakos
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引用次数: 2

摘要

我们考虑了发射机在受干扰的无线链路上向接收机发送信号的问题,并开发了两种在线功率控制算法来最大化无线链路质量(传输速率)。我们假设发射机发射和干扰机在M个时隙内进行干扰。干扰器的影响是在无线信道存在的时隙中恶化无线信道的质量。我们假设有一个强大的随机干扰器,能够任意降低信道质量并影响任意(未知)时隙的数量。由于干扰机的存在是任意的,在给定时间段内的完整干扰模式(信道质量)是未知的先验的。当前信道质量在当前时隙开始时向发射机显示,而未来信道质量仍然未知。然后发射机必须在只知道当前信道质量的情况下,优化分配功率,以最大限度地提高M个时隙的总传输速率,从而产生在线功率控制问题。我们开发了两种在线功率控制算法,以最大化无线链路质量(传输速率)。第一种算法基于恒定功率缩放,当M个时隙(ĥhgPT/M)的平均接收功率质量非常小或非常大时,其竞争比为0(1)。但当ĥhgPT = O(M)时,该算法的竞争比有一个上界为O(logM/log logM}。这个上界很紧。第二种基于恒速率缩放的在线算法具有给定方程的最坏情况竞争比。根据平均接收功率的离线可用参数,合理选择算法,可以保证在所有情况下,竞争比几乎不变,从而使链路质量最大化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Online algorithms for maximizing quality of link transmissions over a jammed wireless channel
We consider the problem of a transmitter transmitting to its receiver over a wireless link subject to jamming and develop two online power control algorithms for maximizing wireless link quality (transmission rate). We assume that the transmitter transmits and the jammer interferes over a period of M time slots. The impact of the jammer is to deteriorate the quality of the wireless channel during time slots in which it is present. We assume a powerful random jammer with the ability to arbitrarily decrease the channel quality and affect any (unknown) number of time slots. Since the presence of the jammer is arbitrary, the complete jamming pattern (channel quality) over the given time period is unknown apriori. The current channel quality is revealed to the transmitter at the start of the current time slot while future channel quality remains unknown. The transmitter must then allocate power optimally to maximize the total transmission rate over M slots given only its knowledge of the current channel quality, thus giving rise to an online power control problem. We develop two online power control algorithms for maximizing the wireless link quality (transmission rate). The first algorithm is based on constant power scaling and has O(1) competitive ratio when the average received power quality over M time slots (ĥhgPT/M) is either very small or very large. However when ĥhgPT = O(M), this algorithm has an upper bound on its competitive ratio of O(logM/log logM}. This upper bound is tight. The second online algorithm based on constant rate scaling has a worst case competitive ratio of given equation. By judiciously choosing which algorithm to use based on the offline available parameter of average received power, we can assure an almost constant competitive ratio for maximizing link quality under all cases.
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