A Stochastic Optimization Approach to Hybrid Processing in Massive MIMO Systems

Georgios K. Papageorgiou; Mathini Sellathurai; Konstantinos Ntougias; Constantinos B. Papadias

doi:10.1109/LWC.2020.2969203

A Stochastic Optimization Approach to Hybrid Processing in Massive MIMO Systems

Georgios K. Papageorgiou, Mathini Sellathurai, Konstantinos Ntougias, Constantinos B. Papadias

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

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Abstract

The high cost and energy consumption of fully digital massive multiple-input multiple-output (MIMO) systems has led to hybrid designs with fewer radio frequency (RF) chains than antennas. In this letter, we propose an efficient hybrid processing algorithm for point-to-point (P2P) massive MIMO systems that operate in either rich or poor scattering environments. The proposed scheme, i.e., hybrid processing via stochastic approximation with Gaussian smoothing (HPSAGS), alternates between a digital baseband and an analog RF precoder/combiner computation step. The method achieves state-of-the-art performance with low computational cost, which is essential for large MIMO systems.

Original language	English
Pages (from-to)	770-773
Number of pages	4
Journal	IEEE Wireless Communications Letters
Volume	9
Issue number	6
Early online date	24 Jan 2020
DOIs	https://doi.org/10.1109/LWC.2020.2969203
Publication status	Published - Jun 2020

Keywords

Gaussian smoothing
Hybrid processing
massive MIMO
millimeter waves
stochastic approximation

ASJC Scopus subject areas

Control and Systems Engineering
Electrical and Electronic Engineering

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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AB - The high cost and energy consumption of fully digital massive multiple-input multiple-output (MIMO) systems has led to hybrid designs with fewer radio frequency (RF) chains than antennas. In this letter, we propose an efficient hybrid processing algorithm for point-to-point (P2P) massive MIMO systems that operate in either rich or poor scattering environments. The proposed scheme, i.e., hybrid processing via stochastic approximation with Gaussian smoothing (HPSAGS), alternates between a digital baseband and an analog RF precoder/combiner computation step. The method achieves state-of-the-art performance with low computational cost, which is essential for large MIMO systems.

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A Stochastic Optimization Approach to Hybrid Processing in Massive MIMO Systems

Abstract

Keywords

ASJC Scopus subject areas

UN SDGs

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