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arXiv · 2510.00342

Site-Specific Beam Learning for Full-Duplex Massive MIMO Wireless Systems

Samuel Li·Ian P. Roberts
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Abstract

Existing beamforming-based full-duplex solutions for multi-antenna wireless systems often rely on explicit estimation of the self-interference channel. The pilot overhead of such estimation, however, can be prohibitively high in millimeter-wave and massive MIMO systems, thus limiting the practicality of existing solutions, especially in fast-fading conditions. In this work, we present a novel beam learning framework that bypasses explicit self-interference channel estimation by designing beam codebooks to efficiently obtain implicit channel knowledge that can then be processed by a deep learning network to synthesize transmit and receive beams for full-duplex operation. Simulation results using ray-tracing illustrate that our proposed technique can allow a full-duplex base station to craft serving beams that couple low self-interference while delivering high SNR, with 75-97% fewer measurements than would be required for explicit estimation of the self-interference channel.

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BibTeXRIS

Samuel Li, Ian P. Roberts. 2025-09-30. Site-Specific Beam Learning for Full-Duplex Massive MIMO Wireless Systems. https://doi.org/10.1109/milcom64451.2025.11310545

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