Product Quantization for Limited Feedback MISO and RIS-Aided Wireless Communication Systems

Recently, scalar quantization (SQ) and vector quantization (VQ) have been widely adopted in wireless communication systems. VQ outperforms SQ, making it an attractive choice for low-dimensional channel vectors. Despite the dominance, VQ demands a large storage capacity for codevectors and a fast-searching algorithm. Thus, VQ may not be the most desirable solution in many applications. To address these concerns, we introduce a novel product quantization (PQ) in this letter. Our PQ has applications in reconfigurable intelligent surface (RIS)-aided systems as well as multiple-input single-output antenna systems. It differs from the original PQ, designed for source coding, in three key aspects: (i) the encoded vector is complex-valued and comprises a single feature, (ii) a shared codebook is used for quantization, and (iii) the quantization of one sub-vector is influenced by other previously quantized sub-vectors. By properly adjusting the quantization parameters, the proposed PQ needs significantly less hardware and computational resources compared with VQ. Further, it outperforms SQ with a comparable hardware and computational complexity. The numerical assessments reveal the superiority of the proposed PQ.

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Publication Details

Journal
IEEE Wireless Communications Letters
Published
2024-10-08
DOI
https://doi.org/10.1109/lwc.2024.3476234
Primary Topic
Wireless Communication Networks Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Product Quantization for Limited Feedback MISO and RIS-Aided Wireless Communication Systems

Mojtaba Ahmadi Almasi, Hamid Jafarkhani
IEEE Wireless Communications Letters
Wireless Communication Networks Research
article

Product Quantization for Limited Feedback MISO and RIS-Aided Wireless Communication Systems

Mojtaba Ahmadi Almasi, Hamid Jafarkhani
article en

Abstract

Recently, scalar quantization (SQ) and vector quantization (VQ) have been widely adopted in wireless communication systems. VQ outperforms SQ, making it an attractive choice for low-dimensional channel vectors. Despite the dominance, VQ demands a large storage capacity for codevectors and a fast-searching algorithm. Thus, VQ may not be the most desirable solution in many applications. To address these concerns, we introduce a novel product quantization (PQ) in this letter. Our PQ has applications in reconfigurable intelligent surface (RIS)-aided systems as well as multiple-input single-output antenna systems. It differs from the original PQ, designed for source coding, in three key aspects: (i) the encoded vector is complex-valued and comprises a single feature, (ii) a shared codebook is used for quantization, and (iii) the quantization of one sub-vector is influenced by other previously quantized sub-vectors. By properly adjusting the quantization parameters, the proposed PQ needs significantly less hardware and computational resources compared with VQ. Further, it outperforms SQ with a comparable hardware and computational complexity. The numerical assessments reveal the superiority of the proposed PQ.

IEEE Wireless Communications LettersVol. 13(12)
University of California, Irvine (US)
National Science Foundation
Openalex Percentile: Top 81%
Wireless Communication Networks Research
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