采用注水因子辅助搜索的能效优先子载波功率联合优化算法

Joint Optimization Algorithm for Subcarrier and Power with Priority of Energy Efficiency Based on Water-Filling Factor Aided Search

针对认知无线网络中以频带利用率为目标进行资源分配网络能效低的问题,提出了一种采用注水因子辅助搜索的能效优先子载波功率联合优化(EE-WFAS)算法。首先,以最大化认知用户总能效作为优化目标,考虑在认知用户发射功率控制、主用户干扰功率限制和认知用户最低信息传输速率限制等多个约束条件下,构造最优化函数;然后,通过能效优先子载波分配与注水因子辅助搜索(WFAS)的功率分配求解优化函数,即根据认知用户的信道增益和能效进行子载波分配;最后,对拉格朗日乘子运用二分查找法结合WFAS进行以能效为目标的功率分配。EE-WFAS优化算法可以在认知用户信息传输速率限制条件下保证系统总能效。仿真结果表明:与子载波功率平均分配算法相比,EE-WFAS优化算法的能效提高了约1.2kbit/J。

A joint optimization algorithm for subcarrier and power with priority of energy efficiency based on a water-filling factor aided search （EE-WFAS） is proposed to solve the problem of traditional spectral efficiency oriented resource allocation in cognitive radio network （CRN） that energy efficiency is in low level.Firstly,the proposed algorithm constructs a constrained optimization problem with maximization of the total energy efficiency of secondary user （SU） as an optimization objective under constraints of SU transmission power control,primary user （PU） interference powercontrol,and limitation of minimum information transfer rate of SU.Then,the optimization problem is solved via subcarrier assignment with priority of energy efficiency and power allocation using WFAS,that is,subcarriers are assigned in accordance with SU channel gain and energy efficiency.Eventually,the optimal power allocation with energy efficiency objective is obtained by a combination of bisection search of the Lagrangian multipliers and the EE-WFAS method.The proposed algorithm guarantees the total energy efficiency under given limitation of information transfer rate of SU.Simulation results and a comparison with the subcarrier and power equal-allocation algorithm show that the proposed algorithm enhances energy efficiency by approximate 1.2 kbit/J.