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Joint Optimization of Cooperative Spectrum Sensing and Resource Allocation in Multi-channel Cognitive Radio Sensor Networks

机译:多通道认知无线电传感器网络中协作频谱感知和资源分配的联合优化

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Cooperative spectrum sensing (CSS) that utilizes multi-user diversity to mitigate channel instability and noise uncertainty is a promising technique in cognitive radio networks (CRNs). However, the spectrum-sensing parameters which affect the channel-access opportunities of secondary users (SUs) are conventionally regarded as static and treated independently from the resource-allocation strategies. In this paper, joint optimization of CSS, channel access and resource allocation is investigated in an overlay CRN in which each SU carries multi-channel spectrum sensing and transmits the detected energy to a fusion centre in the imperfect reporting channel. An access factor is introduced to describe the channel-access strategies in both cooperative and non-cooperative schemes. Based on the aggregate interference and the transmit power constraints, an optimization problem of multi-channel CSS is formulated to obtain the optimal transmit powers, allocation-access strategies, and sensing threshold of CR system for maximization of the opportunistic throughput. To solve the non-convex problems in both the single and multiple CR systems, the efficient iterative algorithms are developed by exploiting the hidden convexity of the optimization problems. Numerical results show that the performance of our approaches yields a significant enhancement compared with the equal channel-access and equal power-allocation strategy.
机译:利用多用户分集来减轻信道不稳定性和噪声不确定性的协作频谱感测(CSS)在认知无线电网络(CRN)中是一种很有前途的技术。但是,影响次级用户(SU)信道访问机会的频谱感知参数通常被认为是静态的,并且与资源分配策略无关。在本文中,在覆盖CRN中研究了CSS,信道访问和资源分配的联合优化,其中每个SU承载多信道频谱感知并将检测到的能量传输到不完美报告信道中的融合中心。引入访问因子来描述合作和非合作方案中的信道访问策略。基于总干扰和发射功率约束,提出了多通道CSS的优化问题,以获得最优的发射功率,分配访问策略和CR系统的感知阈值,以最大化机会吞吐量。为了解决单CR和多CR系统中的非凸问题,通过利用优化问题的隐性凸度来开发有效的迭代算法。数值结果表明,与相同的信道访问和相同的功率分配策略相比,我们的方法的性能得到了显着提高。

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