基于功率控制的认知无线网络能效研究

Study on Energy-efficient of Cognitive Wireless Networks Based on Power Control

针对Underlay频谱共享模式下的认知无线网络的能量效率问题,提出了一种双重改进的粒子群功率控制优化算法(Dual Improved Particle Swarm Optimization,DIPSO),通过最小化约束条件下认知用户的发射功率以实现网络能量效率优化.在仿真过程中,以保证认知用户基本通信的同时不对主用户正常通信构成影响为基本前提,对信道衰落及噪声干扰进行了综合考虑,搭建出多约束条件下的网络能量效率函数,实现认知无线网络中认知用户发射功率的最小化.仿真结果表明:该算法可有效提升无线网络的能量效率.

Aiming at the problem of cognitive wireless network energy efficiency under underlay spectrum sharing mode,a double improved particle swarm optimization algorithm(DIPSO)for power control was proposed.The optimization of network energy efficiency was realized by recognizing the transmitted power of users under the condition of minimizing constraints.In the simulation process,under the circumstance of considering channel fading and noise interference,the fuction of network energy efficiency and relevant constraints were constructed on the premise where the normal communication of main users was not affected,the basic communication of users was guaranteed,and the transmission power of cognitive users in the cognitive wireless network was minimized.The simulation shows that the proposed algorithm can effectively improve the energy efficiency of wireless network.