基于天线选择的CRN下行波束赋形方案

The scheme of CRN downlink beamforming with antenna selection

针对underlay模式下认知无线网络(CRN)的性能提升问题,提出一种基于天线选择的下行波束赋形方案。方案对由CRN模型得到的优化问题的非凸约束条件,包括秩1约束、二进制整数型变量和非线性约束等,分别采用双线性等效变换、松弛变量替换及添加惩罚项等方法转换为凸约束条件,得到了双凸优化问题。并给出了基于交替优化方法的问题求解算法。数值仿真结果表明,相对于固定天线,采用天线选择优化的CRN随着可选天线数目的增加,能量效率增大;在相同的服务质量下,下行功率减小,优化算法的可行解区域增大,而且对主网络基站的干扰具有鲁棒性。

Aiming at the performance improvement of cognitive radio network(CRN) in underlay mode, this paper proposes a scheme of downlink beamforming with antenna selection. The non-convex constrains of the optimization problem from the CRN model in the scheme, e.g. rank one constrains, binary integer variables constrains and nonlinear constrains etc, are transformed into the convex constrains by means of bilinear equivalent forms, slack variables and penalty terms. The biconvex optimization problem is obtained. And the alternative optimization algorithm of the problem is provided. The numerical simulation results demonstrate that compared with the CRN with fixed antenna, the energy efficiency of the CRN with antenna selection increases with the increase of the number of the selected antenna;the downlink powers decrease under the same quality of service conditions;the feasible region enlarges and the robustness to interferences of the primary base station is revealed.