项目名称: 噪声不确定下基于计算智能的多跳认知无线电网络协作频谱感知优化
项目编号: No.61501253
项目类型: 青年科学基金项目
立项/批准年度: 2016
项目学科: 无线电电子学、电信技术
项目作者: 岳文静
作者单位: 南京邮电大学
项目金额: 19万元
中文摘要: 为解决噪声不确定下多跳认知无线电网络(多跳CRN)协作频谱感知中主用户检测、感知控制和CR用户协作等关键问题,利用计算智能及相关框架和算法,首先研究基于混合群智能的多跳CRN主用户频谱特征检测的分布式融合计算策略和协同决策多目标优化方法,然后探索基于Memetic算法的多跳CRN频谱感知控制优化方法,最后研究基于进化博弈的多跳CRN频谱感知认知用户高效协作框架及其进化稳定策略和分布式学习算法等,并通过理论论证、实验测试、仿真模拟、敏感度分析等手段保证上述研究成果的可靠性或稳定性。本项目的研究将通过协同进化和动态优化提高噪声不确定下多跳CRN主用户检测准确度,均衡获得协作频谱感知最佳控制参数和决策阈值,解决在信息不完全和有限理性条件下CR用户协作问题,切实提高实际动态应用环境中多跳CRN协作频谱感知性能。
中文关键词: 认知无线电网络;协作频谱感知;认知无线电
英文摘要: To solve the key issues of primary users’ detection, sensing control and CR users’ cooperation in cooperative spectrum sensing of multi-hop cognitive radio networks (multi-hop CRN) with noise uncertainty, this project uses computational intelligence and the related frameworks and algorithms, firstly, to study the hybrid swarm intelligence based distributed fusion computing strategies and collaborative decision-making multi-objective optimization methods for CRN primary user spectrum feature detection in multi-hop CRN, then to explore the memetic algorithm based spectrum sensing control optimization methods of multi-hop CRN, and finally to study the evolutionary game based CR uses’ efficient cooperative frameworks, evolutionary stable strategy and distributed learning algorithm for the spectrum sensing of multi-hop CRN, and to ensure the reliability or stability of the above research results through theoretical argumentation, experimental test, simulation, sensitivity analysis. The studies of the project will improve the primary user detection accuracy through the co-evolution and dynamic optimization in multi-hop CRN with noise uncertainty, balanced obtain the best spectrum sensing control parameters and cooperative decision thresholds, solve CR users’ cooperation problems under the conditions of the incomplete information and limited rationality, and effectively improve the cooperative spectrum sensing performance in the actual dynamic application environment of multi-hop CRN.
英文关键词: Cognitive Radio Networks;Cooperative Spectrum Sensing;Cognitive Radio