Cooperative spectrum sensing (CSS) systems use underlay or overlay strategies to identify underused or unused bands to achieve higher spectrum utilization. In hybrid underlay and overlay systems, spectrum sensing results may be sparse and a general reporting strategy is required to take multiple spectrum usage status into account. In this paper, we propose a general quantized soft decision (QSD) based compressive sensing and reporting strategy for hybrid systems. Our objective is to provide a general framework to report more reliable sensing results to improve the sensing precision and reduce the collision probability with the low complexity. To this end, the soft sensing decisions are quantized to multiple levels, then they are compressed and encoded, while the characteristic information of secondary users (SUs) including the index of the SUs, the interference tolerance level etc, is transmitted over equivalent bit channels. Furthermore, considering that different users may have different quality of service requirements, we propose four methods to allow SUs to deliver local sensing results with different precisions. Simulations are performed over additive white Gaussian noise (AWGN) and Rayleigh fading channels. The results validate the theoretical analysis, and demonstrate that our scheme effectively improves the sensing decision precision and reduces the collision probability.

中文翻译：

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用于底层/重叠协作认知无线电网络的基于量化软决策的压缩报告设计

合作频谱感知 (CSS) 系统使用底层或重叠策略来识别未充分利用或未使用的频段，以实现更高的频谱利用率。在混合底层和重叠系统中，频谱感知结果可能很少，并且需要通用报告策略来考虑多种频谱使用状态。在本文中，我们为混合系统提出了一种基于通用量化软决策（QSD）的压缩感知和报告策略。我们的目标是提供一个通用框架来报告更可靠的传感结果，以提高传感精度并降低低复杂度的碰撞概率。为此，将软感知决策量化为多个级别，然后对其进行压缩和编码，而二级用户（SU）的特征信息包括 SU 的索引，干扰容限等级等通过等效位信道传输。此外，考虑到不同的用户可能有不同的服务质量要求，我们提出了四种方法来允许 SU 以不同的精度提供本地感知结果。模拟是在加性高斯白噪声 (AWGN) 和瑞利衰落信道上执行的。结果验证了理论分析，表明我们的方案有效地提高了感知决策精度并降低了碰撞概率。模拟是在加性高斯白噪声 (AWGN) 和瑞利衰落信道上执行的。结果验证了理论分析，表明我们的方案有效地提高了感知决策精度并降低了碰撞概率。模拟是在加性高斯白噪声 (AWGN) 和瑞利衰落信道上执行的。结果验证了理论分析，表明我们的方案有效地提高了感知决策精度并降低了碰撞概率。