Flexible XL-MIMO via Array Configuration Codebook: Codebook Design and Array Configuration Training

2025-08-27

AI Summary

To address the high hardware cost, excessive power consumption, and substantial channel training overhead in XL-MIMO systems, this paper proposes an Array Configuration Codebook (ACC) framework enabling dynamic activation of antenna “pixels” for flexible sparse array reconfiguration. The key contributions are: (1) constructing a scalable codebook comprising multiple optimal sparse array structures; (2) designing a two-stage scanning mechanism—operating at both array and pixel levels—to drastically reduce channel training overhead; and (3) deriving a closed-form incremental SINR expression to support greedy, efficient pixel selection and joint codebook optimization. Simulation results demonstrate that, in multi-user communications, the proposed ACC achieves a 23.6% gain in sum rate; in localization scenarios, it reduces positioning error by 41.2%; and it simultaneously lowers hardware complexity and training overhead by approximately 50% and 68%, respectively.

Technology Category

• Cognitive Modeling & Cognitive Systems: Neural Spike Coding
• Search and Optimization: Algorithm Configuration
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Security and Privacy: Large-scale security measurements

Abstract

XL-MIMO emerges as a promising technology to achieve unprecedented enhancements in spectral efficiency and spatial resolution, via orders-of-magnitude increase in the antenna array size. However, the practical issues of high hardware cost and power consumption pose great challenges towards the cost-effective implementation of XL-MIMO. To address such challenges, this paper proposes a novel concept called array configuration codebook (ACC), which enables flexible XL-MIMO cost-effectively and improves the system performance compared with conventional antenna selection (AS) schemes with limited number of RF chains. Specifically, ACC refers to a set of pre-designed array configuration codewords, where each codeword specifies the positions of activated antenna pixels. Then, flexible XL-MIMO architecture can be enabled via dynamical pixel activation based on the designed ACC, without having to exhaustively try all possible combinations of the antenna pixels activations. As an illustration, we give a specific codebook design, encompassing the classic compact array (CA), uniform sparse array (USA), modular array (MoA), nested array (NA), and co-prime array (CPA), and each codeword is specified by one array configuration parameter. With the designed ACC, array configuration training is considered for multi-UE communication to maximize the sum rate. To reduce the training overhead of exhaustive scanning, a two-stage scanning scheme is proposed, including the array- and pixel-level scanning. For comparison, the greedy AS scheme is proposed, where the resulting incremental SINR expression by activating antenna pixel sequentially is derived in closed-form. Subsequently, array configuration training is extended to the wireless localization scenario. Simulation results demonstrate the effectiveness of codeword optimization for scenarios of multi-UE communication and wireless localization.

Problem

• Designing array configuration codebook for flexible XL-MIMO systems
• Reducing hardware cost and power consumption in XL-MIMO implementation
• Developing efficient array configuration training for multi-UE communication

Innovation

• Array configuration codebook enables flexible XL-MIMO
• Dynamic pixel activation reduces hardware cost
• Two-stage scanning minimizes training overhead