Design and Implementation of Singular Value Decomposition for Channel Tracking in mmWave MIMO Systems

• Main Authors: Jian-Lin Li, 李建霖
• Other Authors: Pei-Yun Tsai
• Format: Others
• Language: zh-TW
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/c7453e

碩士 === 國立中央大學 === 電機工程學系 === 107 === Due to the increasing antenna number at the base station and user terminal, higher computational complexity is induced. To reduce the complexity of receiver, there are many precoding techniques are proposed to achieve lower cost, smaller area and lower power. In the multiple input multiple output (MIMO) wireless communication systems, singular value decomposition (SVD) generate precoding, beamforming and decoding matrix at transmitter and receiver [1]. It can enhance the signal concentration and remove interference. In this thesis, hybrid power method (HPM) is used for SVD to track mmWave channel. In the initialization phase, initial singular value is obtained by the self power method (SPM). And then in the tracking phase, self-adjusting is utilized in each iteration by self-adjusting inverse power method (SA-IPM) to track singular value. Compare to SPM and SA-IPM, SA-IPM not only has excellent convergence and low complexity but also gets higher throughput in parallel processing. In SA-IPM hardware design, the core architecture is QR decomposition, which is realized by Coordinate Rotation Digital Computer and systolic array. It can support a matrix size form 2×2 to16×16. To decompose a 16×16 channel matrix, QR decomposition takes 474 clocks, and it needs 616 clocks for a singular value decomposition. Through the TSMC 40nm process, the highest clock operating frequency reaches 143MHz. Throughput is 232K column vector per second without parallel processing and power consumption is 66.4mW. If three QR decomposition is used and parallel processing is considered, throughput can be increased to 904K column vector per second.