Bit-level Optimized Neural Network for Multi-antenna Channel Quantization

Lu, Chao, Xu, Wei, Jin, Shi and Wang, Kezhi (2019) Bit-level Optimized Neural Network for Multi-antenna Channel Quantization. IEEE Wireless Communications Letters. ISSN 2162-2337 (In Press)

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Official URL: https://doi.org/10.1109/lwc.2019.2942908

Abstract

Quantized channel state information (CSI) plays a critical role in precoding design which helps reap the merits of multiple-input multiple-output (MIMO) technology. In order to reduce the overhead of CSI feedback, we propose a deep learning based CSI quantization method by developing a joint convolutional residual network (JC-ResNet) which benefits MIMO channel feature extraction and recovery from the perspective of bit-level quantization performance. Experiments show that our proposed method substantially improves the performance.

Item Type: Article
Uncontrolled Keywords: Channel state information (CSI), quantization, neural network (NN), multiple-input multiple-output (MIMO).
Subjects: G400 Computer Science
G500 Information Systems
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Elena Carlaw
Date Deposited: 23 Sep 2019 08:38
Last Modified: 11 Oct 2019 13:18
URI: http://nrl.northumbria.ac.uk/id/eprint/40801

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