Optimizing Spectral Efficiency in Downlink Millimeter Wave Distributed Massive Multi-User MIMO: A Fully Connected Two-Stage Iterative Hybrid Precoding Approach

Distributed massive multiple-input multiple-output (MIMO) at millimeter wave (mmWave) frequencies utilizes a combination of analog and digital precoding to effectively handle data transmission among various antennas and base stations (BSs) located at different sites. This method enhances spectral ef...

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Veröffentlicht in:Wireless personal communications Jg. 142; H. 3-4; S. 355 - 386
Hauptverfasser: Gholami, Elahe, Meghdadi, Hamid, Shahzadi, Ali
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.06.2025
Springer Nature B.V
Schlagworte:
Algorithms
Antennas
Beamforming
Communication
Communications Engineering
Complexity
Computer Communication Networks
Data transmission
Design
Digital systems
Downlinking
Energy efficiency
Engineering
Iterative algorithms
Kuhn-Tucker method
Lagrange multiplier
Millimeter waves
MIMO communication
Networks
Optimization
Radio frequency
Signal processing
Signal,Image and Speech Processing
Downlink
Multi-user
Hybrid precoding
Distributed massive MIMO
Fully connected
Optimization
ISSN:0929-6212, 1572-834X
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Zusammenfassung:Distributed massive multiple-input multiple-output (MIMO) at millimeter wave (mmWave) frequencies utilizes a combination of analog and digital precoding to effectively handle data transmission among various antennas and base stations (BSs) located at different sites. This method enhances spectral efficiency despite having less complexity and cost compared to fully digital systems. This paper presents a fully connected hybrid precoding design for a downlink mmWave distributed massive multi-user MIMO. The objective function for the optimization problem is the spectral efficiency of the proposed system, subject to constraints on analog radio frequency (RF) precoding and power budget. The main aim is to maximize spectral efficiency. Due to the nonconvex nature of the problem, a two-stage iterative algorithm is proposed to determine the optimal analog and digital beamforming matrices and sum rate. The first 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 Lagrange multipliers and Karush–Kuhn–Tucker (KKT) conditions for each maximization problem are computed and examined to derive the solving algorithms for each stage. The problem is then simplified, and the proposed algorithms are formulated. The simulation results demonstrate 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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ISSN:0929-6212
1572-834X
DOI:10.1007/s11277-025-11810-7