Joint transmission and cooperative spectrum sensing scheduling optimization in multi-channel dynamic spectrum access networks

A. Azarfar, Chun-Hao Liu, J. Frigon, B. Sansò, D. Cabric
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引用次数: 4

Abstract

Dynamic spectrum access (DSA) for secondary networks has the potential to improve spectrum utilization and thus mitigate the problem of spectrum scarcity by finding spectrum opportunities and exploiting them efficiently. A key factor in DSA networks with multiple channels and multiple users is to establish efficient spectrum sensing and transmission schedules. Multi-user cooperative spectrum sensing reduces the sensing time, thus increasing transmission throughput. At the same time, it may remove transmission opportunities for users participating in the sensing, thereby decreasing the throughput. Furthermore, in a multi-channel network, where the users experience different channel qualities, the problem of designing optimal sensing and transmission schedules becomes more complex. Sensing schedule indicates to each user the channel that it must sense at different sensing moments, and transmission schedules indicates which user should use a found opportunity. In this paper, we explore this problem and then investigate optimal ways to find a joint sensing and transmission schedule. We propose three joint sensing-transmission strategies. Within each one of them, several solutions striking a balance between throughput performance, memory usage, and computational complexity are proposed. Due to the complex nature of optimal solutions, we also propose different heuristics. Simulation results show that the proposed heuristics perform well and thus can be employed in practical scenarios.
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多通道动态频谱接入网络中的联合传输与协同频谱感知调度优化
二级网络的动态频谱接入(DSA)有可能提高频谱利用率,从而通过发现频谱机会并有效利用它们来缓解频谱稀缺的问题。建立高效的频谱感知和传输调度是多信道多用户DSA网络的关键。多用户协同频谱感知减少了感知时间,从而提高了传输吞吐量。同时,它可能会剥夺参与感知的用户的传输机会,从而降低吞吐量。此外,在多信道网络中,用户体验到不同的信道质量,设计最优的感知和传输调度问题变得更加复杂。感知调度指示每个用户在不同的感知时刻必须感知的信道,传输调度指示哪个用户应该使用发现的机会。本文对这一问题进行了探讨,并探讨了寻找联合传感和传输调度的最优方法。我们提出了三种联合传感传输策略。在每一种方案中,提出了几种在吞吐量性能、内存使用和计算复杂性之间取得平衡的解决方案。由于最优解的复杂性,我们也提出了不同的启发式方法。仿真结果表明,所提出的启发式算法性能良好,可用于实际场景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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