认知双向中继网络的功率分配优化算法研究

相对于传统的认知单向中继系统,认知双向中继网络由于引入了网络编码技术,减少了传输时隙,能获得更高的频谱效率．对采用时分广播(Time Division Broadcast,TDBC)传输协议的译码转发(Decode-and-Forward,DF)认知双向中继网络的和速率进行了分析,提出了一种功率分配的优化算法,能在满足次用户(Secondary Users,SUs)总功率约束以及对主用户(Primary Users,PUs)最大干扰功率(Maximum Tolerable Interference Power,MTIP)约束的前提下,最大限度提高次用户网络的和速率．并推导了不同情况下,次用户网络功率分配的最优解．数值仿真结果验证了该理论分析的正确性,同时表明,次用户的总功率以及主用户的干扰功率限制,对次用户网络的和速率有较大影响．

Optimal power allocation for cognitive two-way relaying networks with underlay spectrum sharing

Compared with the conventional one-way relaying system, cognitive two-way relaying networks can improve spectrum utilization further by applying network coding. This paper presents an analytical study on the sum rate for cognitive decode-and-forward (DF) two-way relaying networks with underlay spectrum sharing. The bidirectional protocol, i.e., three time-slot time division broadcast (TDBC), is considered. We proposed an optimization power allocation scheme, which maximizes the sum rate of secondary users (SUs) to afford the best communication performance under maximum tolerable interference power (MTIP) constraint to primary user (PU) and a total transmit power constraint to SUs. The optimal solutions to power allocation are obtained in different cases. Numerical simulations validate the theoretical analysis and demonstrate the total available power of SUs and the MTIP constraint have a great effect on the sum rate.