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.

中文翻译：

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MIMO网络中性能保证的功率最小化的最优条件：一种分布式算法及其可行性

针对多小区多用户（MCMU）多输入多输出（MIMO）系统的信号干扰加噪声比（SINR）保证的功率最小化（SGPM）问题，提出了一种分布式方法。与现有的SGPM方法不同，所提出的技术基于解决必要和充分的最优性条件，这些条件是通过将原始问题分解为前向和后向（FB）子问题而派生的，同时确保每个子问题的强对偶性。所提出的分布式SGPM算法分别利用FB自适应和Jacobi递归来进行迭代滤波器设计和功率分配。基于矩阵逆-正理论，分析了所提出的分布式算法可行性的充分条件。与现有的完全分布式FB滤波器更新算法不同，所提出的方法保证了目标SINR性能及其收敛到固定点。仿真结果表明，与现有的分布式技术相比，所提方法的性能保证提高了电源效率。