Angle domain sparse beam forming algorithm based on 3D-MIMO system noisy channel coefficient

Abstract

The present invention belongs to the technical field of communication, and especially relates to an angle domain sparse beam forming algorithm based on a 3D-MIMO system noisy channel coefficient. The angle domain sparse beam forming algorithm enables a 3D beam forming problem to be modeled as an optimization model of minimum base station transmitting power by aiming at a single cell MU-MIMO downlink channel system; then converts the original problem into an equivalence optimization problem in the angle domain through angle domain conversion; and adds an l1 norm penalty term of an angle domain pre-code to the beam forming optimization problem by utilizing the angle domain sparse characteristics of a 3D-MIMO channel, so that the obtained angle domain pre-code meets certain sparsity, and is further approximate to the actual solution of the optimal angle domain pre-code, thereby improving system performance; and finally converts the optimization problem into a second-order cone programming problem through variable substitution, and then solves the problem through a convex optimization tool. A simulation result shows that the system performance of the angle domain sparse beam forming algorithm of the present invention is greatly better than the system performance of a non-robustness beam forming algorithm in the scene with big channel noise errors.

Description

technical field [0001] The invention belongs to the technical field of communications, and in particular relates to a method for optimizing the design of 3D beamforming in the angle domain for noisy channels based on the sparse characteristics of 3D-MIMO spatial channel information in the angle domain. Background technique [0002] Multiple-Input Multiple-Output (MIMO) is an important technology in modern wireless communication networks, especially in multi-user MIMO systems, the base station can simultaneously serve multiple users, thereby increasing system throughput. The key problem in the multi-user MIMO system is inter-user interference, which is usually eliminated completely or reduced according to a certain criterion through beamforming precoding at the base station. The more classic precoding methods include zero forcing (ZF) [1] , Block Diagonalization (BD) [2] , the maximum signal-to-leakage-to-noise ratio (SLNR) [3] and other algorithms. Among them, an optimi...

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Problems solved by technology

However, these methods often convert the robust beamforming design problem into a semi-infinite (finite constraint variables, infinite constraints) optimization problem, which brings high computational complexity

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