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From Centralized RAN to Open RAN: A Survey on the Evolution of Distributed Antenna Systems

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arxiv 2411.12166 v1 pith:QNQ34BPT submitted 2024-11-19 eess.SP cs.ET

From Centralized RAN to Open RAN: A Survey on the Evolution of Distributed Antenna Systems

classification eess.SP cs.ET
keywords networkmassivenetworksradio-accessaccessarchitecturescommunicationradio
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Next-generation mobile networks require evolved radio access network (RAN) architectures to meet the demands of high capacity, massive connectivity, reduced costs, and energy efficiency, and to realize communication with ultra-low latency and ultra-high reliability. {Meeting such} requirements for both mobile users and vertical industries in the next decade {requires novel solutions. One of the potential solutions that attracted significant research attention in the past 15 years} is to redesign the radio access network (RAN). In this survey, we present a comprehensive survey on distributed antenna system (DAS) architectures that address these challenges and improve network performance. We cover the transition from traditional decentralized RAN to DAS, including cloud radio-access networks (C-RAN), fog radio-access networks (F-RAN), virtualized radio-access networks (V-RAN), cell-free massive multiple-input multiple-output (CF-mMIMO), and {the most recent advances manifested in} open radio-access network (O-RAN). In the process, we discuss the benefits and limitations of these architectures, including the impact of limited-capacity fronthaul links, various cooperative uplink and downlink coding strategies, cross-layer optimization, and techniques to optimize the performance of DAS. Moreover, we review key enabling technologies for next-generation RAN systems, such as multi-access edge computing, network function virtualization, software-defined networking, and network slicing; in addition to some crucial radio access technologies, such as millimeter wave, massive multi-input multi-output, device-to-device communication, and massive machine-type communication. Last but not least, we discuss the major research challenges in DAS and identify several possible directions for future research.

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Cited by 2 Pith papers

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  1. AI-RAN on NPUs: Baseband Processing Without Baseband Chips

    eess.SP 2026-07 accept novelty 7.0

    A complete OFDM transceiver runs end-to-end over the air on a commercial edge NPU by remapping baseband operators onto dense matrix and vector engines.

  2. ACCoRD: Actor-Critic Conflict Resolution with Deep learning for O-RAN xApps

    cs.MA 2026-05 unverdicted novelty 5.0

    ACCoRD trains an ANN with PPO-Clip reinforcement learning to select conflict resolution actions in O-RAN, reducing negative network events versus rule-based methods in medium and high traffic simulations.