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    ARTICLE

    Deep Learning-Based Decoding and AP Selection for Radio Stripe Network

    Aman Kumar Mishra, Vijayakumar Ponnusamy*

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 131-148, 2022, DOI:10.32604/iasc.2022.021017 - 26 October 2021

    Abstract

    Cell-Free massive MIMO (mMIMO) offers promising features such as higher spectral efficiency, higher energy efficiency and superior spatial diversity, which makes it suitable to be adopted in beyond 5G (B5G) networks. However, the original form of Cell-Free massive MIMO requires each AP to be connected to CPU via front haul (front-haul constraints) resulting in huge economic costs and network synchronization issues. Radio Stripe architecture of cell-free mMIMO is one such architecture of cell-free mMIMO which is suitable for practical deployment. In this paper, we propose DNN Based Parallel Decoding in Radio Stripe (DNNBPDRS) to decode

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