This paper proposes a novel cooperative spectrum sensing network (CSSN) with improved energy detector (IED) based cognitive radio (CR) users. Every CR user is furnished with multiple antennas (M) and performs itself selection combining (SC) operation. All the CRs sense a primary user (PU) via erroneous sensing channels (S) and send the data to a fusion center (FC) via erroneous reporting channels (R). At FC, decision about PU is evaluated with the assistance of k-out-of-N rule. Detection probability expressions for a CR and FC subject to noise plus Rayleigh/Rician fading are developed. Also both simulation and analytical frameworks for throughput analysis are presented. The analytical performance results are also validated using simulation performance results. Performance comparisons between IED and conventional energy detectors (CED) are presented in terms of throughput and total error rate for several parameter values. Further, overall performance of throughput and total error rate in Rayleigh/Rician fading channels is investigated. The joint effects of diversity and fading on the CSSN throughput is also additionally discussed. Channel error (r) impact on the throughput and total error performances for each proposed and traditional networks is studied. Optimization of several parameters for maximizing the throughput and minimizing the total error is also studied. Throughput overall performance of proposed CSSN is plenty better than the conventional network in each fading channel. For several values of M and r, \(p_{\mathrm{{opt}}}\), \(\lambda _{\mathrm{{n, opt}}}\) and \(N_{\mathrm{{opt}}}\) values are calculated subject to each fading environment. Both analytical and MATLAB simulation results are matched. Under imperfect channel conditions, performances in terms of throughput and total error are not up to the mark but significant performance improvement has been obtained with diversity at each CR level.

本文提出了一种新型协作频谱感知网络 (CSSN)，它具有基于改进的能量检测器 (IED) 的认知无线电 (CR) 用户。每个CR用户配备多根天线（M）并执行自己的选择组合（SC）操作。所有 CR 通过错误的感知通道 (S) 感知主用户 (PU)，并通过错误的报告通道 (R) 将数据发送到融合中心 (FC)。在 FC，在k -out-of- N的帮助下评估关于 PU 的决定规则。开发了受噪声和瑞利/莱斯衰落影响的 CR 和 FC 的检测概率表达式。还介绍了吞吐量分析的模拟和分析框架。还使用仿真性能结果验证了分析性能结果。IED 和传统能量检测器 (CED) 之间的性能比较是在几个参数值的吞吐量和总错误率方面呈现的。此外，研究了瑞利/莱斯衰落信道中吞吐量和总错误率的整体性能。此外还讨论了分集和衰落对 CSSN 吞吐量的联合影响。通道误差（r) 对每个提议的和传统的网络的吞吐量和总错误性能的影响进行了研究。还研究了用于最大化吞吐量和最小化总误差的几个参数的优化。在每个衰落信道中，提议的 CSSN 的吞吐量整体性能比传统网络好得多。对于M和r 的几个值，\(p_{\mathrm{{opt}}}\)、\(\lambda _{\mathrm{{n, opt}}}\)和\(N_{\mathrm{{选择}}}\）值是根据每个衰落环境计算的。分析结果和 MATLAB 仿真结果都匹配。在不完美的信道条件下，吞吐量和总错误方面的性能达不到标准，但在每个 CR 级别的多样性已经获得了显着的性能改进。