Heterogeneous Massive MIMO: A Cost-Efficient Technique for Uniform Service in Cellular Networks

Massive multi-input multi-output (MIMO) has evolved along two tracks: cellular and cell-free, each with unique advantages and limitations. The cellular approach suffers from worse user spectral efficiency at cell edges, whereas the cell-free approach incurs high implementation costs due to a large-scale distributed infrastructure. This paper introduces a novel networking paradigm, termed heterogeneous massive MIMO (HmMIMO), which seamlessly integrates co-located and distributed antennas. Differing from two conventional paradigms, HmMIMO remains a base station with a large antenna array at the center of each cell, aided by distributed antennas deployed at cell edges. Our findings demonstrate that this paradigm achieves a favorable trade-off between performance and implementation complexity.

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Published
2025-08-10
DOI
https://doi.org/10.1109/iccc65529.2025.11148826
Primary Topic
Advanced MIMO Systems Optimization
Type
article
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article

Heterogeneous Massive MIMO: A Cost-Efficient Technique for Uniform Service in Cellular Networks

Hans D. Schotten, Wei Jiang
Advanced MIMO Systems Optimization
article

Heterogeneous Massive MIMO: A Cost-Efficient Technique for Uniform Service in Cellular Networks

Hans D. Schotten, Wei Jiang
article en

Abstract

Massive multi-input multi-output (MIMO) has evolved along two tracks: cellular and cell-free, each with unique advantages and limitations. The cellular approach suffers from worse user spectral efficiency at cell edges, whereas the cell-free approach incurs high implementation costs due to a large-scale distributed infrastructure. This paper introduces a novel networking paradigm, termed heterogeneous massive MIMO (HmMIMO), which seamlessly integrates co-located and distributed antennas. Differing from two conventional paradigms, HmMIMO remains a base station with a large antenna array at the center of each cell, aided by distributed antennas deployed at cell edges. Our findings demonstrate that this paradigm achieves a favorable trade-off between performance and implementation complexity.

University of Kaiserslautern (DE), German Research Centre for Artificial Intelligence (DE)
Openalex Percentile: Top 77%
Advanced MIMO Systems Optimization
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