Jie Yang;Wanchen Hu;Yi Jiang;Shuangyang Li;Xin Wang
{"title":"Achievable Rate Maximization in MIMO-BICM Systems: A Unified Transceiver Design","authors":"Jie Yang;Wanchen Hu;Yi Jiang;Shuangyang Li;Xin Wang","doi":"10.1109/TSP.2025.3592835","DOIUrl":null,"url":null,"abstract":"Transceiver designs for multiple-input multiple-output (MIMO) systems have been extensively studied in the past decades. However, in the context of finite constellation inputs, existing transceiver designs do not guarantee optimal performance across all SNR ranges or varying code rates. In this paper, we propose a novel maximum achievable rate transceiver (MART) design for bit-interleaved coded modulation in MIMO (MIMO-BICM) systems. Our proposed MART scheme combines channel matrix decomposition and decision feedback equalization (DFE), decomposing the MIMO channel into multiple parallel subchannels. We establish a tight lower bound for achievable rates in MIMO-BICM, based on which we transform the sophisticated problem to the optimization of the output signal-to-noise ratios (SNRs) of subchannels. We consider the achievable rate maximization under both zero-forcing (ZF) and minimum mean-square error (MMSE) criteria and provide a unified solution framework for both two problems. To simplify the optimization process, we further propose an alternative near-optimal scheme for both ZF and MMSE problems. Numerical results show the optimality of the proposed MART scheme across all SNR ranges, demonstrating its potential in practical MIMO-BICM systems.","PeriodicalId":13330,"journal":{"name":"IEEE Transactions on Signal Processing","volume":"73 ","pages":"3346-3361"},"PeriodicalIF":5.8000,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Signal Processing","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/11099053/","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
Transceiver designs for multiple-input multiple-output (MIMO) systems have been extensively studied in the past decades. However, in the context of finite constellation inputs, existing transceiver designs do not guarantee optimal performance across all SNR ranges or varying code rates. In this paper, we propose a novel maximum achievable rate transceiver (MART) design for bit-interleaved coded modulation in MIMO (MIMO-BICM) systems. Our proposed MART scheme combines channel matrix decomposition and decision feedback equalization (DFE), decomposing the MIMO channel into multiple parallel subchannels. We establish a tight lower bound for achievable rates in MIMO-BICM, based on which we transform the sophisticated problem to the optimization of the output signal-to-noise ratios (SNRs) of subchannels. We consider the achievable rate maximization under both zero-forcing (ZF) and minimum mean-square error (MMSE) criteria and provide a unified solution framework for both two problems. To simplify the optimization process, we further propose an alternative near-optimal scheme for both ZF and MMSE problems. Numerical results show the optimality of the proposed MART scheme across all SNR ranges, demonstrating its potential in practical MIMO-BICM systems.
期刊介绍:
The IEEE Transactions on Signal Processing covers novel theory, algorithms, performance analyses and applications of techniques for the processing, understanding, learning, retrieval, mining, and extraction of information from signals. The term “signal” includes, among others, audio, video, speech, image, communication, geophysical, sonar, radar, medical and musical signals. Examples of topics of interest include, but are not limited to, information processing and the theory and application of filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals.