Rajavel S Esakki, Devaraj Stalin Allwin, Roobert A Andrew, Kumar Om Prakash, Vincent Shweta
Electronics and Communication Engineering, Faculty of Engineering, Karpagam Academy of Higher Education, Coimbatore, Tamil Nadu, 641021, India.
Electronics and Communication Engineering, Francis Xavier Engineering College, Tirunelveli, Tamil Nadu, 627003, India.
Sci Rep. 2025 May 4;15(1):15566. doi: 10.1038/s41598-025-00068-5.
The large bandwidth of 5G wireless networks results in a discontinuous optimal spectrum. This study leverages cognitive radio networks and collaborative spectrum sensing to improve the transmission performance in 5G communication. Energy limitations for each secondary user (SU) and potential errors in secondary transmission within cognitive nodes during cooperative transmissions and spectrum sensing contribute to the dynamic energy efficiency. This paper details an Electronic Energy Relay Selection (EERS) system. The weighted average function determines the optimal relays when the network communication power consumption and spectrum-detection levels are equal. The EERS system examines the correlation between energy efficiency and detection precision. The proposed EERS system surpasses the performance of the compressed sensing collaborative detection (CSCD) system. MATLAB was used to evaluate and compare performance metrics such as weighted energy consumption, number of collaborative SU relays, and probability of missing detection with those of compressed sensing-based collaborative detection.
5G无线网络的大带宽导致频谱最优解不连续。本研究利用认知无线电网络和协作频谱感知来提高5G通信中的传输性能。每个次用户（SU）的能量限制以及协作传输和频谱感知期间认知节点内二次传输中的潜在误差导致了动态能量效率。本文详细介绍了一种电子能量中继选择（EERS）系统。当网络通信功耗和频谱检测水平相等时，加权平均函数确定最优中继。EERS系统研究了能量效率与检测精度之间的相关性。所提出的EERS系统优于压缩感知协作检测（CSCD）系统。使用MATLAB评估并比较了加权能耗、协作SU中继数量和漏检概率等性能指标与基于压缩感知的协作检测的性能指标。
