Superiorized Adaptive Projected Subgradient Method with Application to MIMO Detection
| Autor: | Jochen Fink, Renato Luís Garrido Cavalcante, Sławomir Stańczak |
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| Rok vydání: | 2022 |
| Předmět: |
Signal Processing (eess.SP)
FOS: Computer and information sciences Computer Science - Information Theory Information Theory (cs.IT) Signal Processing FOS: Electrical engineering electronic engineering information engineering Electrical Engineering and Systems Science - Signal Processing Electrical and Electronic Engineering |
| DOI: | 10.48550/arxiv.2203.01116 |
| Popis: | 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 (e.g., correlated channels) are considered. Compared to existing low-complexity iterative detectors such as individually optimal large-MIMO approximate message passing (IO-LAMA), 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 IO-LAMA. Comment: Submitted to IEEE Transactions on Signal Processing for possible publication |
| Databáze: | OpenAIRE |
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