信道不对称多细胞网络中加权和速率最大化的有效解
Efficient Solutions for Weighted Sum Rate Maximization in Multicellular Networks With Channel Uncertainties
摘要：
多小区环境中的加权和速率最大化（WSRM）问题本质上对信道估计误差敏感。在本文中，我们研究如何最大限度地提高加权和率的线性预编码多小区下行链路系统中的接收机配备了一个单一的天线。在基站具有完善的信道信息的情况下，我们首先提出了一种新的快速收敛算法来解决WSRM问题。然后，该假设被放宽到信道估计中的误差向量被假设为位于由有限椭球的相交形成的不确定性集合中的情况。作为我们的主要贡献，我们提出了两个程序来解决棘手的非凸鲁棒设计的最坏情况下的原则。所提出的迭代算法解决了半定规划在其每个步骤，并证明收敛到鲁棒WSRM问题的局部最优解。所提出的方法进行了数值比较，以确定其对信道估计不完善的鲁棒性。结果清楚地表明，性能增益的情况下，在设计过程中忽略信道的不确定性。对于某些情况下，我们还量化了建议的近似值和精确解之间的差距。
英文摘要：
The important problem of weighted sum rate maximization (WSRM) in a multicellular environment is intrinsically sensitive to channel estimation errors. In this paper, we study ways to maximize the weighted sum rate in a linearly precoded multicellular downlink system where the receivers are equipped with a single antenna. With perfect channel information available at the base stations, we first present a novel fast converging algorithm that solves the WSRM problem. Then, the assumption is relaxed to the case where the error vectors in the channel estimates are assumed to lie in an uncertainty set formed by the intersection of finite ellipsoids. As our main contributions, we present two procedures to solve the intractable nonconvex robust designs based on the worst case principle. The proposed iterative algorithms solve the semidefinite programs in each of their steps and provably converge to a locally optimal solution of the robust WSRM problem. The proposed approaches are numerically compared against each other to ascertain their robustness towards channel estimation imperfections. The results clearly indicate the performance gain compared to the case when channel uncertainties are ignored in the design process. For certain scenarios, we also quantify the gap between the proposed approximations and exact solutions.
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