This paper proposes a genetic-algorithm (GA)-based subcarrier allocation in orthogonal frequency division multiplexing (OFDM)-based hybrid beamforming multi-user massive multiple-input multiple-output (MU-mMIMO) systems. Our goal is to maximize the system sum-rate capacity under the total transmit power constraint through optimally selecting Kmax users out of K available users to be served over each sub-carrier. Considering the energy-efficient hybrid beamforming architecture deployed at the base station (BS), the non-convex optimization problem is solved in four steps: (i) designing a radio frequency (RF) beamformer using slow time-varying angle-of-departure (AoD) information of users to generate the beams for all subcarriers, (ii) designing a baseband (BB) precoder for each subcarrier using the corresponding low-dimensional effective channel state information (CSI) seen from the BB stage based on regularized zero-forcing (RZF) technique, (iii) optimizing subcarrier allocation using GA with equal power allocation (EQ-PA) among users (iv) performing GA-based power allocation over each subcarrier to further improve the system sum-rate. Illustrative results indicate that the proposed algorithm performs significantly better than the random and greedy subcarrier allocation schemes in terms of the achieved sum-rate.


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    Title :

    Intelligent Subcarrier Allocation in Hybrid Beamforming Multi-User mMIMO-OFDM Systems


    Contributors:
    Bishe, Farhan (author) / Koc, Asil (author) / Le-Ngoc, Tho (author)


    Publication date :

    2023-06-01


    Size :

    2837746 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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