基于CBAM-VAE的NR 5G兼容系统CSI反馈

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

Physical Communication Pub Date : 2025-08-26 DOI:10.1016/j.phycom.2025.102816

Anusaya Swain , Shrishail M. Hiremath , Sarat Kumar Patra , Shivashankar Hiremath

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引用次数: 0

摘要

大规模多输入多输出（M-MIMO）的性能提升依赖于基站（BS）中准确的下行信道状态信息（CSI）。在频分双工（FDD）系统中，由于缺乏互易原理，用户设备（UE）必须将估计的下行CSI矩阵精确地馈送给基站。然而，M-MIMO系统有大量的天线，这导致了大量的CSI数据。将所有这些数据发送回BS会产生瓶颈，消耗有限的可用带宽资源的很大一部分。本文提出了一种符合3GPP规范的新型深度学习（DL）框架CBAM-VAE，以有效分析CSI反馈的目标。该模型旨在将卷积块注意模块（CBAM）的关键特征与变分自编码器（VAE）相结合，因此称为CBAM-VAE。实验结果表明，与使用余弦相似度（ρ）和归一化均方误差（NMSE）作为四种不同码字长度（Ns）的关键性能指标的基线网络相比，所设计的架构具有优越的性能。此外，CBAM-VAE还具有较少的计算开销，使其可用于实时场景。

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CBAM-VAE based CSI feedback for NR 5G compliant system

The promising performance gains of massive multiple-input and multiple-output (M-MIMO) rely on the accurate downlink channel state information (CSI) at the base station (BS). In the case of frequency division duplex (FDD) systems, the user equipment (UE) has to feed the estimated downlink CSI matrix to the BS precisely due to the absence of the principle of reciprocity. However, M-MIMO systems have a large number of antennas which leads to a significant amount of CSI data. Sending all this data back to the BS creates a bottleneck, consuming a large portion of the limited bandwidth resources available. In this paper, CBAM-VAE, a novel deep learning (DL) framework that complies with the 3GPP specifications is proposed to effectively analyze the objective of CSI feedback. The model is designed to incorporate the key features of the convolutional block attention module (CBAM) integrated with the variational autoencoder (VAE) hence, termed CBAM-VAE. The experimental outcomes show the superior performance of the designed architecture in comparison to the baseline networks using cosine similarity (

ρ

) and normalized mean square error (NMSE) as the key performance indicators for four distinct lengths of codeword

(N_{s})

. In addition, CBAM-VAE also has less computational overhead making it acceptable for real-time scenarios.

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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.