认知无线电网络中的 IRS 辅助频谱感知与灰狼优化

IF 2 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC Physical Communication Pub Date : 2024-07-05 DOI:10.1016/j.phycom.2024.102436

Vishwas Srivastava, Binod Prasad

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引用次数: 0

摘要

认知无线电（CR）对于有效管理有限的频谱资源至关重要。然而，其性能有赖于高效的频谱感知。本文研究了一种适用于认知无线电网络的新方法，该方法利用智能反射面（IRS）专门进行频谱感知，并利用非正交多址接入（NOMA）进行数据传输。我们提出了一种基于灰狼优化（GWO）的 IRS 优化方法，以最大限度地提高频谱感应性能。独立于 IRS，NOMA 被用来提高数据传输过程中的频谱效率。通过吞吐量和频谱感知参数（即误报和漏检概率）对性能进行评估。数值和仿真结果表明，基于 GWO 的 IRS 优化明显优于传统的自然启发算法，频谱感测精度提高了约 97%。根据改进后的频谱感应结果，通过大量仿真评估和验证了有效的数据传输吞吐量。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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IRS assisted spectrum sensing in cognitive radio network with grey wolf optimization

Cognitive radio (CR) is of crucial importance in providing efficient management of limited spectrum resources. However, its performance relies on efficient spectrum sensing. This paper investigates a novel approach for CR networks that leverages intelligent reflecting surface (IRS) specifically for spectrum sensing and non-orthogonal multiple access (NOMA) for data transmission. We propose a Grey-Wolf Optimization (GWO) based IRS optimization approach to maximize spectrum sensing performance. Independent of the IRS, NOMA is employed to improve spectral efficiency during data transmission. The performance is evaluated in terms of throughput and spectrum sensing parameters, namely probability of false alarm and missed detection. Numerical and simulation results demonstrate that GWO-based IRS optimization significantly outperforms conventional nature-inspired algorithms, achieving approximately 97% improvement in spectrum sensing accuracy. Based on the improved spectrum sensing results, the effective data transmission throughput is evaluated and validated through extensive simulation.

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来源期刊

Physical Communication ENGINEERING, ELECTRICAL & ELECTRONICTELECO-TELECOMMUNICATIONS

CiteScore

5.00

自引率

9.10%

发文量

212

审稿时长

55 days

期刊介绍： PHYCOM: Physical Communication is an international and archival journal providing complete coverage of all topics of interest to those involved in all aspects of physical layer communications. Theoretical research contributions presenting new techniques, concepts or analyses, applied contributions reporting on experiences and experiments, and tutorials are published. Topics of interest include but are not limited to: Physical layer issues of Wireless Local Area Networks, WiMAX, Wireless Mesh Networks, Sensor and Ad Hoc Networks, PCS Systems; Radio access protocols and algorithms for the physical layer; Spread Spectrum Communications; Channel Modeling; Detection and Estimation; Modulation and Coding; Multiplexing and Carrier Techniques; Broadband Wireless Communications; Wireless Personal Communications; Multi-user Detection; Signal Separation and Interference rejection: Multimedia Communications over Wireless; DSP Applications to Wireless Systems; Experimental and Prototype Results; Multiple Access Techniques; Space-time Processing; Synchronization Techniques; Error Control Techniques; Cryptography; Software Radios; Tracking; Resource Allocation and Inference Management; Multi-rate and Multi-carrier Communications; Cross layer Design and Optimization; Propagation and Channel Characterization; OFDM Systems; MIMO Systems; Ultra-Wideband Communications; Cognitive Radio System Architectures; Platforms and Hardware Implementations for the Support of Cognitive, Radio Systems; Cognitive Radio Resource Management and Dynamic Spectrum Sharing.