针对大规模多输入单输出的多点协作下行系统,本文主要研究协同波束成形和功率控制,以达到最大化最差用户信干噪比的目的。为了求解原始下行的非凸优化问题,首先将原始优化问题转化成等价的上行优化问题进行求解。尽管在有限系统里可通过迭代算法获得波束矢量和发射功率,但是该算法依赖于瞬时信道信息,功率也需要瞬时更新。为了减少功率更新计算复杂度,本文进一步利用随机矩阵理论,提出了只需要依赖统计信道信息的算法来获得发射功率。数值仿真验证了单基站功率约束下所提算法的有效眭以及相对于最大比发送算法的优越性。
This paper studies joint beamforming and power allocation for maximizing the minimum signal-to-interference- plus-noise ratio optimization problem in multi-cell multiuser multiple-input single-output downlink network. To solve the o- riginal downlink non-convex optimization problem, the original optimization problem is transformed into an equivalent uplink optimization problem. Although the beamformer and power allocation can be obtained by the iterative algorithm in the finite system, it depends on the instantaneous channel state information which requires instantaneous power update. To reduce the complexity of power updating, an algorithm that only requires statistical channel state information is designed to derive pow- er allocation by applying the random matrix theory. Numerical results validate the effectiveness of our proposed algorithm and show the advantages of our proposed algorithm over maximal-ratio transmit in the single base station power constraint.