Near-Optimal Hybrid Processing for Massive MIMO Systems via Matrix Decomposition

Abstract

For the practical implementation of massive multiple-input multiple-output (MIMO) systems, the hybrid processing (precoding/combining) structure is promising to reduce the high cost rendered by large number of RF chains of the traditional processing structure. The hybrid processing is performed through low-dimensional digital baseband processing combined with analog RF processing enabled by phase shifters. We propose to design hybrid RF and baseband precoders/combiners for multi-stream transmission in point-to-point massive MIMO systems, by directly decomposing the pre-designed unconstrained digital precoder/combiner of a large dimension. The constant amplitude constraint of analog RF processing results in the matrix decomposition problem non-convex. Based on an alternate optimization technique, the non-convex matrix decomposition problem can be decoupled into a series of convex sub-problems and effectively solved by restricting the phase increment of each entry in the RF precoder/combiner within a small vicinity of its preceding iterate. A singular value decomposition based technique is proposed to secure an initial point sufficiently close to the global solution of the original non-convex problem. Through simulation, the convergence of the alternate optimization for such a matrix decomposition based hybrid processing (MD-HP) scheme is examined, and the performance of the MD-HP scheme is demonstrated to be near-optimal.

Hybrid Beamforming in mm-Wave MIMO Systems Having a Finite Input Alphabet

“…Oman et al [8] FAS Basis Pursuit Matrices of equal gain elements/ Least squares Ahmed et al [9], [10] beam steering vectors based solution Weiheng et al [11] FAS Convex Quadratic Matrices of equal gain elements Least squares Programming based solution Jaspreet et al [12] ASA Dominant beam Matrices of beam Predefined set of selection based approach steering vectors matrices [16] Linglong et al [13] ASA Successive interference Matrices of equal gain elements Mean Square Error (MSE) cancellation minimization solution obtain the necessary condition for the precoding and combining matrices to maximize the mutual information (MI) of our system considering a finite input alphabet. This solution is referred to as the unconstrained solution.…”

“…We then obtain the constrained solution via matrix decomposition [11] in order to obtain an equal gain element matrix and a unit norm matrix, which are used as analog and digital precoding/combining matrices, respectively. Furthermore, motivated by the recent developments in directional beamforming (DBF) in the context of mm-wave communication [17]- [19], we propose a low-complexity gradient-ascent aided DBF (GA-DBF) that strikes a beneficial trade-off between the complexity imposed and the performance attained.…”

“…In this paper, we consider the geometric channel model often used for modelling practical mm-wave channel [8]- [11], given by…”

Spectral and Energy Efficiency of Multi-Pair Massive MIMO Relay Network With Hybrid Processing

“…With only a limited number of RF chains, however, it would be hard to implement full dimensional digital precoding for massive antenna elements. Therefore, hybrid digital and analog precoding design is necessary for massive MIMO with limited RF chains [21]- [24].…”

“…Under the practical RF-chain constraint, [21] considered multi-stream transmission in point-to-point (P2P) massive MIMO and proposed a near-optimal matrix decomposition based hybrid precoding (MD-HP). Downlink transmission for multiuser massive MIMO with limited RF chains was studied in [22] and [23].…”