Optimality Conditions of Performance-Guaranteed Power Minimization in MIMO Networks: A Distributed Algorithm and Its Feasibility
Optimality Conditions of Performance-Guaranteed Power Minimization in MIMO Networks: A Distributed Algorithm and Its Feasibility
复制标题
DOI：
10.1109/tsp.2020.3035877
复制
发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Guojun Xiong;Taejoon Kim;D. Love;E. Perrins
中科院分区：
文献类型：
--
作者：
Guojun Xiong;Taejoon Kim;D. Love;E. Perrins
针对多小区多用户（MCMU）多输入多输出（MIMO）系统的信噪比（SINR）保证功率最小化问题，提出了一种分布式方法。与先前的SGPM方法不同，该方法基于求解充分和必要最优性条件，该条件通过将原问题分解为前向和后向子问题而得到，同时保证每个子问题的强对偶性。本文提出的分布式SGPM算法分别利用FB自适应和Jacobi递归进行迭代滤波器设计和功率分配。基于矩阵逆正理论，分析了分布式算法可行的充分条件。与现有的全分布式FB滤波器更新算法不同，该方法既保证了目标信噪比性能，又保证了其收敛到平稳点。仿真结果表明，与现有的分布式技术相比，该方法在保证性能的前提下提高了功率效率。
—A distributed approach is proposed to the problem of signal-to-interference-plus-noise-ratio (SINR)-guaranteed power minimization (SGPM) for multicell multiuser (MCMU) multiple-input multiple-output (MIMO) systems. Unlike prior SGPM approaches, the proposed technique is based on solving necessary and sufficient optimality conditions, which are derived by decomposing the original problem into forward and backward (FB) subproblems, while ensuring the strong duality of each subproblem. The proposed distributed SGPM algorithm makes use of FB adaptation and Jacobi recursion, respectively, for iterative filter design and power allocation. A sufficient condition for the feasibility of the proposed distributed algorithm is analyzed, based on the matrix inverse-positive theory. Unlike the existing fully distributed FB filter update algorithms, the proposed approach guarantees target SINR performance as well as its convergence to a stationary point. Simulation results illustrate the enhanced power efficiency with the performance guarantees of the proposed method compared to the existing distributed techniques.