In this paper, we investigate the energy efficiency of conventional collaborative compressive sensing (CCCS) scheme, focusing on balancing the tradeoff between energy efficiency and detection accuracy in cognitive radio environment. In particular, we derive the achievable throughput, energy consumption and energy efficiency of the CCCS scheme, and then formulate an optimization problem to determine the optimal values of parameters which maximize the energy efficiency of the CCCS scheme. The maximization of energy efficiency is proposed as a multi-variable, non-convex optimization problem, and we provide approximations to reduce it to a convex optimization problem. We highlight that errors due to these approximations are negligible. Subsequently, we analytically characterize the tradeoff between dimensionality reduction and collaborative sensing performance of the CCCS scheme, i.e., the implicit tradeoff between energy saving and detection accuracy. It is shown that the resulting loss due to compression can be recovered through collaboration, which improves the overall energy efficiency of the system.

中文翻译：

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认知无线电网络协同压缩感知方案的能效分析

在本文中，我们研究了传统协作压缩感知 (CCCS) 方案的能源效率，重点是在认知无线电环境中平衡能源效率和检测精度之间的权衡。特别地，我们推导出CCCS方案的可实现吞吐量、能耗和能效，然后制定优化问题来确定使CCCS方案的能效最大化的参数的最优值。能源效率的最大化被提议为一个多变量的非凸优化问题，我们提供了近似值以将其简化为凸优化问题。我们强调由于这些近似值引起的误差可以忽略不计。随后，我们分析表征了CCCS 方案的降维和协同感知性能之间的权衡，即节能和检测精度之间的隐式权衡。结果表明，压缩造成的损失可以通过协作恢复，从而提高了系统的整体能源效率。