Performance evaluation of AI-based CSI feedback schemes compliant with 3GPP standards

IF 2.2 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Physical Communication Pub Date : 2025-08-10 DOI:10.1016/j.phycom.2025.102803

Rahul Pal , Vikram Singh , Vijaya Mareedu

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引用次数: 0

Abstract

This paper addresses the limitations of traditional CSI feedback schemes in 5G massive MIMO-OFDM systems, particularly the challenges of high feedback overhead and computational complexity. To overcome these issues, this paper proposes and presents an in-depth evaluation of “M-CsiNet”, an AI-based feedback channel state information compression and reconstruction model adhering to 3GPP standards using the “CDL-C”MIMO channel model. The innovation of “M-CsiNet” lies in the extension of CsiNet to “M-CsiNet” and conducting an in-depth evaluation. Unlike legacy methods such as Type-II and Enhanced Type-II codebook-based schemes, “M-CsiNet” demonstrates significant improvements. Experimental results demonstrate that “M-CsiNet” achieves up to 10–15 dB SNR gain in link-level block error rate (BLER) and throughput performance while reducing feedback overhead by two orders and with reduced complexity. These advantages make “M-CsiNet” a promising solution for practical deployment in capacity-constrained 5G and future wireless systems across both rank-1 and rank-2 transmission scenarios.

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基于ai的符合3GPP标准的CSI反馈方案的性能评价

本文讨论了传统CSI反馈方案在5G大规模MIMO-OFDM系统中的局限性，特别是高反馈开销和计算复杂性的挑战。为了克服这些问题，本文提出并深入评估了“M-CsiNet”，这是一种基于人工智能的反馈信道状态信息压缩和重构模型，采用“CDL-C”MIMO信道模型，符合3GPP标准。“M-CsiNet”的创新在于将CsiNet延伸到“M-CsiNet”，并进行深入的评估。与传统方法（如ii型和增强ii型基于码本的方案）不同，“M-CsiNet”显示出显著的改进。实验结果表明，“M-CsiNet”在链路级块错误率（BLER）和吞吐量性能方面实现了高达10-15 dB的信噪比增益，同时将反馈开销降低了两个数量级，并降低了复杂度。这些优势使“M-CsiNet”成为在容量受限的5G和未来无线系统中跨一级和二级传输场景进行实际部署的有希望的解决方案。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Physical Communication ENGINEERING, ELECTRICAL & ELECTRONICTELECO-TELECOMMUNICATIONS

CiteScore

5.00

自引率

9.10%

发文量

212

审稿时长

55 days

期刊介绍： PHYCOM: Physical Communication is an international and archival journal providing complete coverage of all topics of interest to those involved in all aspects of physical layer communications. Theoretical research contributions presenting new techniques, concepts or analyses, applied contributions reporting on experiences and experiments, and tutorials are published. Topics of interest include but are not limited to: Physical layer issues of Wireless Local Area Networks, WiMAX, Wireless Mesh Networks, Sensor and Ad Hoc Networks, PCS Systems; Radio access protocols and algorithms for the physical layer; Spread Spectrum Communications; Channel Modeling; Detection and Estimation; Modulation and Coding; Multiplexing and Carrier Techniques; Broadband Wireless Communications; Wireless Personal Communications; Multi-user Detection; Signal Separation and Interference rejection: Multimedia Communications over Wireless; DSP Applications to Wireless Systems; Experimental and Prototype Results; Multiple Access Techniques; Space-time Processing; Synchronization Techniques; Error Control Techniques; Cryptography; Software Radios; Tracking; Resource Allocation and Inference Management; Multi-rate and Multi-carrier Communications; Cross layer Design and Optimization; Propagation and Channel Characterization; OFDM Systems; MIMO Systems; Ultra-Wideband Communications; Cognitive Radio System Architectures; Platforms and Hardware Implementations for the Support of Cognitive, Radio Systems; Cognitive Radio Resource Management and Dynamic Spectrum Sharing.