摘要
在认知无线网络中,对于电池供电的认知设备,如何高效地利用其能量资源极为重要。在将能量效率(能效)定义为认知网络频谱利用效率和平均功率消耗之比的基础上,提出了一种高能效优化算法,在加性高斯白噪声(AWGN)信道、Rayleigh衰落信道和Nakagami衰落信道条件下使融合中心门限达到最优,并求得了最佳的参与协作的用户数。通过蒙特卡洛仿真对认知网络的能效进行了性能评估,结果表明所提算法能有效提升认知网络的能量效率。
In CR （Cognitive Radio） networks and for battery-powered SUs （Secondary Users）, how to use energy resources efficiently is of great significance. In this paper, EE （Energy Efficiency） is defined as the ratio of spectrum utilization efficiency of CR network to average power consumption. A high energy-ef- ficient optimization algorithm is proposed, and the threshold in FC （Fusion Center） is optimal under the condition of AWGN （Additive White Gaussian Noise） channels, Rayleigh fading channels and Nakagami fading channels, with the optimal number of cooperating SUs derived. EE performance of CR network is e- valuated via Monte-Carlo simulation, and the results show that the proposed algorithm can effectively im- prove the energy efficiency of CR network.
出处
《通信技术》
2015年第4期435-440,共6页
Communications Technology
关键词
认知无线网络
高能效
协作频谱感知
衰落环境
cognitive radio
energy-efficient
cooperative spectrum sensing
fading environment
