Superiorized Adaptive Projected Subgradient Method with Application to MIMO Detection

03/02/2022
by   Jochen Fink, et al.
0

In this paper, we show that the adaptive projected subgradient method (APSM) is bounded perturbation resilient. To illustrate a potential application of this result, we propose a set-theoretic framework for MIMO detection, and we devise algorithms based on a superiorized APSM. Various low-complexity MIMO detection algorithms achieve excellent performance on i.i.d. Gaussian channels, but they typically incur high performance loss if realistic channel models are considered. Compared to existing low-complexity iterative detectors such as approximate message passing (AMP), the proposed algorithms can achieve considerably lower symbol error ratios over correlated channels. At the same time, the proposed methods do not require matrix inverses, and their complexity is similar to AMP.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
05/21/2022

Graph Neural Network Enhanced Approximate Message Passing for MIMO Detection

Efficient multiple-input multiple-output (MIMO) detection algorithms wit...
research
03/15/2023

Low-Complexity Memory AMP Detector for High-Mobility MIMO-OTFS SCMA Systems

Efficient signal detectors are rather important yet challenging to achie...
research
05/29/2018

Large Multiuser MIMO Detection: Algorithms and Architectures

In this thesis, we investigate the problem of efficient data detection i...
research
09/25/2021

A Variational Bayesian Inference-Inspired Unrolled Deep Network for MIMO Detection

The great success of deep learning (DL) has inspired researchers to deve...
research
11/24/2011

Receiver Architectures for MIMO-OFDM Based on a Combined VMP-SP Algorithm

Iterative information processing, either based on heuristics or analytic...
research
05/05/2022

Low-complexity Beam Selection algorithms based on SVD for MmWave Massive MIMO Systems

To realize mmWave massive MIMO systems in practice, Beamspace MIMO with ...
research
11/21/2022

Structural Optimization of Factor Graphs for Symbol Detection via Continuous Clustering and Machine Learning

We propose a novel method to optimize the structure of factor graphs for...

Please sign up or login with your details

Forgot password? Click here to reset