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March 3, 2026Scientific Reports2 citationsOpen Access

Improving spectral efficiency in distributed massive MIMO in multi-user downlink millimeter wave

RRR. RajaganapathiSSS. SenthilkumarEAEatedal Alabdulkreem

Key Points

  • Spectral efficiency is maximized using analog and digital precoding techniques in this system.
  • The design achieves better performance in sum rate while maintaining lower complexity compared to digital methods.
  • A two-stage iterative algorithm is introduced to optimize both analog and digital beamforming matrices efficiently.
  • This method supports advanced data transfer in multi-user environments, highlighting significant improvements over existing designs.

Abstract

Analog and digital precoding are used in distributed massive multiple-input multiple-output (MIMO) at millimeter wave (mmWave) frequencies to efficiently manage data transfer across several antennas and base stations (BSs) situated at different locations. This method enhances spectral efficiency(SE) in spite of having a smaller amount complexity and cost compared fully digital systems. This paper presents a fully connected hybrid precoding design for a downlink mmWave dispensed or distributed massive multi-user MIMO. The objective function for the optimization problem is the SE of the proposed system, subject to constraints on analog radio frequency (RF) precoding and power budget. The main aim is to maximize SE. Due to the nonconvex nature of the problem, a two-stage iterative algorithm is proposed to conclude the optimal analog and digital beamforming matrices and sum rate. The 1st stage obtains the optimal digital matrix assuming the analog RF precoder matrix is known, followed by acquiring the optimal analog RF precoder matrix in the next step. The Karush-Kuhn-Tucker (KKT) condition for each maximization problem are compute and examine to derive the solving algorithms for each stage. The simulation results display that the proposed design outperforms current methods in sum rate and approaches the performance of fully digital systems with reduced complexity compared to other alternatives.

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Cite This Study

Rajaganapathi et al. (2026) studied this question.

synapsesocial.com/papers/69a75b18c6e9836116a21c54https://doi.org/10.1038/s41598-026-37016-w
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