认知无线网络中基于联合波束形成和功率分配的低复杂度SINR均衡算法

摘要

As an effective technique to improve the spectrum utilization,cognitive radio has been attached great importance to in the wireless communication.In this paper,we consider the SINR balancing problem involving joint beamfoming and power allocation in the cognitive radio network,wherein the single-input multi-output multiple access channels are assumed.Subject to two sets of constraints:the interference constraints of primary users and the transmission power constraints of cognitive users,a low-complexity joint beamforming and power allocation algorithm is proposed.Compared with the existing algorithm,the proposed algorithm can reduce the number of matrix inversions and matrix eigen-decompositions significantly,especially when large numbers of PUs and CUs are active,while still providing the optimal balanced SINR level for all the CUs.The convergence and optimality of the proposed algorithm are proved in theory and the computational complexity is analyzed in detail.Both the theory and the simulations demonstrate that in the multi-user cognitive networks,the average complexity of the proposed algorithm can be reduced by more than 50％ compared with the existing algorithm.%认知无线电作为提高频谱使用效率的有效手段成为当前通信领域的研究热点.本文研究了单输入多输出的多用户认知无线网络,在主用户的干扰功率约束和认知用户的发射功率约束下,针对认知用户的信干噪比均衡问题,提出了一种低复杂度的联合波束形成和功率分配算法.与已有算法相比,该算法可以在保证最优的均衡信干噪比水平的同时,大幅度降低矩阵求逆和矩阵特征值分解的次数,特别是当处于通信状态的主用户和认知用户数目很多时.本文理论证明了所提算法的收敛性和最优性,并进行了详细的复杂度分析.理论分析和仿真结果均表明在多用户的认知无线网络中,本文所提算法可以将已有算法的平均运算复杂度降低50％以上.