CR-NOMA系统中基于能效的功率分配算法

Energy efficiency based power allocation algorithm in CR-NOMA system

针对移动通信系统存在频谱利用率不高、能耗开销大和能量效率低的问题,在基于认知无线电非正交多址(Cognitive Radio Non-Orthogonal Multiple Access,CR-NOMA)网络系统中,提出一种基于改进人工鱼群算法的功率分配方案.系统包含多个主次用户,首先为提升频谱效率和降低解调的误码概率以及时延,次用户以非正交多址的形式接入系统,并采用一种均匀信道增益差的策略对用户进行分组.其次,考虑到传统人工鱼群算法对次用户功率寻优易掉进局部最优解、寻优能力弱和种群多样性差等不足,将约束算子机制和自适应策略引入人工鱼群算法中;最后,使用该算法联合优化各子信道间功率与子信道内次用户功率,寻求次用户最佳发射功率以最大化系统总能量效率.实验结果表明,在次用户为30的条件下,改进的人工鱼群算法所获总能量效率比传统人工鱼群算法提升了10.6%,具有更好的系统性能.

The current mobile communication system has problems such as low spectrum utilization,high energy consumption,and low energy efficiency.In the Cognitive Radio Non-Orthogonal Multiple Access(CR-NOMA)network system,a power allocation scheme based on improved artificial fish swarm algorithm is proposed.The system includes multiple primary and secondary users.Firstly,in order to improve spectral efficiency,reduce error probability and delay of demodulation,secondary users access the system in the form of non-orthogonal multiple access,and a user grouping strategy with uniform channel gain difference is adopted.Secondly,considering that the traditional artificial fish swarm algorithm is easy to fall into the local optimal solution,weak optimization ability and poor population diversity for the secondary user power optimization,the constraint operator mechanism and adaptive strategy are introduced into the artificial fish swarm algorithm.Finally,the algorithm is used to jointly optimize the power between each subchannel and the power of secondary users within the subchannel,seeking the optimal transmission power of secondary users,and maximizing the total energy efficiency of the system.The experimental results show that when the secondary user is 30,compared with the traditional artificial fish swarm algorithm,the total energy efficiency of improved artificial fish swarm algorithm is improved by 10.6%,and the system performance is better.