{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T13:03:01Z","timestamp":1777035781116,"version":"3.51.4"},"reference-count":24,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2025,6,5]],"date-time":"2025-06-05T00:00:00Z","timestamp":1749081600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Platform of Core Facility Platform of Computer Science and Communication, SIST, ShanghaiTech University","award":["2024ZD1300700"],"award-info":[{"award-number":["2024ZD1300700"]}]},{"name":"National Science and Technology Major Project\u2014Mobile Information Networks","award":["2024ZD1300700"],"award-info":[{"award-number":["2024ZD1300700"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>This study proposes a separate source-channel coding (SSCC) framework to address semantic communication challenges in MIMO systems, overcoming the limitations of joint source-channel coding (JSCC) in channel adaptation and model reusability. Traditional systems suffer from bit-level redundancy in 6G, while JSCC struggles with complex channel variations. Our solution decouples semantic processing from channel coding through a three-tier architecture: (1) Variational autoencoder (VAE)-based semantic encoder and decoder for source coding, (2) A communication-informed bottleneck attribution (CIBA) mechanism quantifying feature importance for learning tasks, and (3) An importance-aware resource allocation scheme aligning communication objectives with deep learning tasks. Systematic experiments validate CIBA\u2019s effectiveness in deriving importance scores that bridge learning tasks and communication optimization. Comparisons of feature perturbation schemes confirm the necessity of importance-aware resource allocation, with the proposed allocation strategy outperforming conventional methods in task performance metrics. The SSCC design enhances model reusability while maintaining adaptability to diverse MIMO configurations. By integrating interpretable AI with resource management, this work establishes a foundation for SSCC semantic communication systems in resource-constrained environments, prioritizing semantic fidelity and task efficacy over bit-level redundancy. The methodology highlights the critical role of importance awareness in optimizing both communication efficiency and learning task performance.<\/jats:p>","DOI":"10.3390\/e27060605","type":"journal-article","created":{"date-parts":[[2025,6,5]],"date-time":"2025-06-05T09:43:18Z","timestamp":1749116598000},"page":"605","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Importance-Aware Resource Allocations for MIMO Semantic Communication"],"prefix":"10.3390","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-6568-6589","authenticated-orcid":false,"given":"Yue","family":"Cao","sequence":"first","affiliation":[{"name":"School of Information Science and Technology, ShanghaiTech University, Shanghai 201210, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4383-9995","authenticated-orcid":false,"given":"Youlong","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, ShanghaiTech University, Shanghai 201210, China"}]},{"given":"Lixiang","family":"Lian","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, ShanghaiTech University, Shanghai 201210, China"}]},{"given":"Meixia","family":"Tao","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering and the Cooperative Medianet Innovation Center (CMIC), Shanghai Jiao Tong University, Shanghai 200240, China"}]}],"member":"1968","published-online":{"date-parts":[[2025,6,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1109\/MWC.002.2200468","article-title":"Task-Oriented Communications for 6G: Vision, Principles, and Technologies","volume":"30","author":"Shi","year":"2023","journal-title":"IEEE Wirel. 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