ABSTRACT

The main challenge of Cognitive Radio (CR) is to identify the occurrence of primary users (PU) effectively to mitigate interference with licenced communications. The occurrence of PU is identified by spectrum sensing (SS). Due to shadowing and deep fading, SS may produce false sensing results. Cooperative spectrum sensing (CSS) can mitigate these problems but at the cost of extra energy consumption especially when the CR users are battery functioned. In CSS, the fusion rule directly affects the energy efficiency (EE) of CR users, it can be optimised to increase EE. Moreover, the energy consumption of the CR users can be minimised if they are grouped into clusters. In this paper intra and inter fusion schemes have been proposed in a cluster-based CSS (CB-CSS). The overall EE is maximised by optimising the inter and intra fusion rule threshold of CB-CSS. An iterative algorithm has been presented that determines the optimal value of inter and intra fusion rule. Results show that for 6X6cluster size, optimum inter and intra fusion rule threshold is found to be 4 and 5, respectively.

摘要

认知无线电 (CR) 的主要挑战是有效识别主要用户 (PU) 的出现以减轻对许可通信的干扰。PU 的发生由频谱感知 (SS) 识别。由于阴影和深度衰落，SS 可能会产生错误的感测结果。合作频谱感知 (CSS) 可以缓解这些问题，但以额外的能源消耗为代价，尤其是当 CR 用户使用电池供电时。在 CSS 中，融合规则直接影响到 CR 用户的能源效率（EE），可以对其进行优化以提高 EE。此外，如果将 CR 用户分组到集群中，则可以将其能耗降至最低。在本文中，已经在基于集群的 CSS (CB-CSS) 中提出了内部和内部融合方案。通过优化 CB-CSS 的内部和内部融合规则阈值来最大化整体 EE。已经提出了确定帧间和帧内融合规则的最佳值的迭代算法。结果表明，对于 6发现 X 6簇大小、最佳的内部和内部融合规则阈值分别为 4 和 5。