Content-Aware AP Selection With LSTM-Enabled Proactive Caching in Cell-Free Massive MIMO Networks

IF 7.9 2区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY

IEEE Transactions on Network Science and Engineering Pub Date : 2025-06-11 DOI:10.1109/TNSE.2025.3578687

Mahnoor Ajmal;Seri Park;Malik Muhammad Saad;Muhammad Ashar Tariq;Dongkyun Kim

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引用次数: 0

Abstract

Cell-Free massive MIMO (CF-mMIMO) networks face significant challenges in achieving Ultra-Reliable Low-Latency Communication (URLLC) requirements due to inherent delays in content retrieval from central processing units (CPUs). This paper presents an integrated framework that jointly optimizes access point (AP) selection and content caching to minimize latency while maintaining reliability. We develop a novel content-aware user-centric clustering scheme that considers both cached content availability and channel conditions. The scheme features a Content Query Beacon (CQB) mechanism, which verifies content availability prior to connection establishment. To address the dynamic nature of content popularity, we design a novel proactive content caching strategy using Long Short-Term Memory (LSTM) to minimize CPU-dependent data retrieval. Extensive simulations demonstrate that our proposed framework achieves a 75% reduction in content delivery latency, 31.87% improvement in Quality of Experience (QoE), and a 26.8% increase in cache hit rates compared to conventional approaches. This comprehensive solution significantly enhances the capability of CF-mMIMO networks to deliver URLLC services, particularly in densely populated areas with diverse content demands.

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无小区大规模MIMO网络中支持lstm的主动缓存的内容感知AP选择

由于从中央处理器（cpu）检索内容的固有延迟，无蜂窝大规模MIMO （CF-mMIMO）网络在实现超可靠低延迟通信（URLLC）要求方面面临重大挑战。本文提出了一个集成框架，该框架联合优化了接入点（AP）选择和内容缓存，以在保持可靠性的同时最小化延迟。我们开发了一种新颖的内容感知的以用户为中心的集群方案，该方案同时考虑了缓存内容的可用性和通道条件。该方案采用内容查询信标（CQB）机制，在建立连接之前验证内容的可用性。为了解决内容流行的动态性，我们设计了一种新的主动内容缓存策略，使用长短期内存（LSTM）来最小化依赖cpu的数据检索。大量的模拟表明，与传统方法相比，我们提出的框架实现了内容交付延迟减少75%，体验质量（QoE）提高31.87%，缓存命中率提高26.8%。这种全面的解决方案显著增强了CF-mMIMO网络提供URLLC服务的能力，特别是在人口密集的地区，具有多样化的内容需求。

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

IEEE Transactions on Network Science and Engineering Engineering-Control and Systems Engineering

CiteScore

12.60

自引率

9.10%

发文量

393

期刊介绍： The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.