Decentralized Multi-Antenna Architectures with Unitary Constraints
🤖 AI Summary
To address the fundamental trade-off between fronthaul bandwidth constraints and performance degradation in decentralized processing for massive MIMO base stations, this paper proposes a decentralized multi-antenna architecture incorporating a unitary matrix constraint. We are the first to introduce such a unitary constraint into the Wireless Analog eXchange (WAX) framework, thereby establishing a theoretical bandwidth–complexity trade-off boundary that guarantees lossless information transmission per unit energy consumption. Leveraging reconfigurable impedance networks, we co-design low-power baseband preprocessing hardware and algorithms. The proposed method substantially reduces both fronthaul bandwidth requirements and computational load, achieving performance close to centralized processing while maintaining hardware feasibility. Our work establishes a novel, energy-efficient decentralized processing paradigm for green 6G base stations—simultaneously optimizing spectral efficiency, energy efficiency, and hardware implementability.
Application Category
📝 Abstract
The increase in the number of base station (BS) antennas calls for efficient solutions to deal with the increased interconnection bandwidth and processing complexity of traditional centralized approaches. Decentralized approaches are thus gaining momentum, since they achieve important reductions in data/processing volume by preprocessing the received signals before forwarding them to a central node. The WAX framework offers a general description of decentralized architectures with arbitrary interplay between interconnection bandwidth and decentralized processing complexity, but the applicability of this framework has only been studied assuming unrestricted baseband processing. We consider an adaptation of the WAX framework where the decentralized processing has unitary restriction, which allows for energy-efficient implementations based on reconfigurable impedance networks at the cost of some performance loss. Moreover, we propose an effective method to minimize the performance gap with respect to centralized processing. The previous method gives a first step towards characterizing the information-lossless trade-off between interconnection bandwidth and processing complexity in decentralized architectures with unitary constraints.
Problem
Research questions and friction points this paper is trying to address.
Massive MIMO
Distributed Processing
Performance Gap
Innovation
Methods, ideas, or system contributions that make the work stand out.
Enhanced WAX Framework
Decentralized Processing
Energy Efficiency
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