Learning Beamforming Codebooks for Active Sensing with Reconfigurable Intelligent Surface
–arXiv.org Artificial Intelligence
--This paper explores the design of beamforming codebooks for the base station (BS) and for the reconfigurable intelligent surfaces (RISs) in an active sensing scheme for uplink localization, in which the mobile user transmits a sequence of pilots to the BS through reflection at the RISs, and the BS and the RISs are adaptively configured by carefully choosing BS beamforming codeword and RIS codewords from their respective codebooks in a sequential manner to progressively focus onto the user . Most existing codebook designs for RIS are not tailored for active sensing, by which we mean the choice of the next codeword should depend on the measurements made so far, and the sequence of codewords should dynamically focus reflection toward the user . Moreover, most existing codeword selection methods rely on exhaustive search in beam training to identify the codeword with the highest signal-to-noise ratio (SNR), thus incurring substantial pilot overhead as the size of the codebook scales. This paper proposes a learning-based approach for codebook construction and for codeword selection for active sensing. The proposed learning approach aims to locate a target in the service area by recursively selecting a sequence of BS beamforming codewords and RIS codewords from the respective codebooks as more measurements become available without exhaustive beam training. The codebook design and the codeword selection fuse key ideas from the vector quantized variational autoencoder (VQ-V AE) and the long short-term memory (LSTM) network to learn respectively the discrete function space of the codebook and the temporal dependencies between measurements. The device is typically placed in the reflecting path between the transceivers, with its configuration wirelessly controlled by the transceivers via a control link. Manuscript submitted to IEEE Transactions on Wireless Communications on September 6, 2024, revised on January 12, 2025, accepted on March 5, 2025. Wei Y u is with The Edward S. Rogers Sr. This work is supported by the Natural Sciences and Engineering Research Council of Canada via the Canada Research Chairs program. The materials in this paper have been accepted in part at the IEEE Workshop on Signal Processing Advances in Wireless Communications (SP A WC), Lucca, Italy, September 2024 [1]. Codebook-based limited control link rate protocol can substantially reduce the control overhead [7], [8]. With the RIS codebook stored at the controller and at the RIS, the controller only needs to send the codeword index in order to configure the RIS.
arXiv.org Artificial Intelligence
Mar-31-2025
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- North America > Canada (0.68)
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- Research Report (0.64)
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- Telecommunications (0.68)
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