摘要
协作频谱感知是认知无线电网络的基础和关键阶段,频谱检测过程中的节点分配策略将直接决定联合频谱感知的结果。介绍了多种分配认知终端的方法,旨在提高频谱感知的效率和公平性。针对不同子频带的感知效率,提出了一种称为由频点占用导致的无效传输参数(inefficient transport parameter,ITP)指标来评估通信性能,给出了感知效率优化问题的闭式表达解,设计的场景包括终端对相同频带有不同的感知性能和相同的感知性能。针对不同子频带间的感知公平性,提出了两种分配算法:弓形分配算法和类划分分配算法。子频带间的公平性通过评估子带中最差的感知性能进行衡量。为了适用于实际场景,加入了频段属性参数来增强公平性,该参数考虑了主用户使用不同频段的优先级及抗干扰能力。仿真结果表明,所提出的策略显著改善了认知无线电网络中的ITP,特别是在子频带利用率不同的情况下,提出的弓形分配算法在公平性不明显降低的情况下,复杂度有明显改善。
Cooperative spectrum sensing is regarded as the foundation and a key stage of cognitive radio networks.The node allocation strategy during the spectrum detection process was directly determined by the results of joint spectrum sensing.Various methods for allocating cognitive terminals to enhance the efficiency and fairness of spectrum sensing were introduced.Aiming at the perceptual efficiency of different sub-bands,an indicator called the inefficient transmission parameter(ITP)was proposed to evaluate communication performance,and a closed-form expression solution to the perceptual efficiency optimization problem was provided.The designed scenarios included terminal pairs with the same frequencies having different perceptual properties and the same perceptual properties.For the perceived fairness among different sub-bands,two allocation algorithms were proposed:the arcuate allocation algorithm and the class division allocation algorithm.Fairness between sub-bands was measured by evaluating the worst perceived performance in the sub-band.In order to be applicable to actual scenarios,the frequency band property parameter was added to enhance fairness.This parameter was taken into account the priority and anti-interference ability of the main user using different frequency bands.Simulation results show that the proposed strategy significantly improves ITP in cognitive radio networks,especially when sub-band utilization is different,and the proposed arcuate allocation algorithm significantly improves the perceived fairness of the system.
作者
吴志强
刘千里
刘佳斌
冯青
肖善鹏
刘尚
WU Zhiqiang;LIU Qianli;LIU Jiabin;FENG Qing;XIAO Shanpeng;LIU Shang(PKU-Wuhan Institute for Artificial Intelligence,Wuhan 430075,China;Tibet University Mount Everest Research Institute,Lhasa 850000,China;Systems Engineering Institute,Academy of Military Science,PLA,Beijing 100082,China;School of Information and Electronics,Beijing Institute of Technology,Beijing 100081,China;China Mobile Research Institute,Beijing 100053,China)
出处
《电信科学》
北大核心
2024年第6期100-113,共14页
Telecommunications Science
基金
国家重点研发计划项目(No.2022YFE0136800)
国家自然科学基金资助项目(No.U20A20162)
武汉市科技局知识创新曙光专项(No.2023010201020490)
武汉市网信委项目(No.2023005)
水声技术国家重点实验室稳定支持基金资助项目(No.JCKYS2023604SSJS009)
西藏科技计划高新社发领域揭榜挂帅项目(No.XZ202303ZY0009G)。
关键词
协作频谱感知
节点分配
感知高效性
感知公平性
cooperative spectrum sensing
terminal assignment
sensing efficiency
sensing fairness