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Bei Yin
Researcher at Rice University
Publications - 29
Citations - 1424
Bei Yin is an academic researcher from Rice University. The author has contributed to research in topics: MIMO & 3G MIMO. The author has an hindex of 15, co-authored 29 publications receiving 1277 citations. Previous affiliations of Bei Yin include University of Houston & Samsung.
Papers
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Journal ArticleDOI
Large-Scale MIMO Detection for 3GPP LTE: Algorithms and FPGA Implementations
TL;DR: This work proposes a new approximate matrix inversion algorithm relying on a Neumann series expansion, which substantially reduces the complexity of linear data detection in single-carrier frequency-division multiple access (SC-FDMA)-based large-scale MIMO systems.
Proceedings ArticleDOI
Approximate matrix inversion for high-throughput data detection in the large-scale MIMO uplink
TL;DR: This paper proposes a novel VLSI architecture to efficiently compute the approximate inverse using a systolic array and shows reference FPGA implementation results for various system configurations.
Proceedings ArticleDOI
Conjugate Gradient-based Soft-Output Detection and Precoding in Massive MIMO Systems
TL;DR: In this article, a conjugate gradient (CG) method was proposed to reduce the complexity of data detection and precoding in massive MIMO systems, and a novel way of computing the signal-to-interference-and-noise ratio (SINR) directly within the CG algorithm was proposed.
Proceedings ArticleDOI
Conjugate gradient-based soft-output detection and precoding in massive MIMO systems
TL;DR: The proposed conjugate gradient (CG) methods are able to outperform existing methods for massive MIMO systems with realistic antenna configurations and a novel way of computing the SINR directly within the CG algorithm at low complexity is proposed.
Proceedings ArticleDOI
Connection-oriented multicasting in wormhole-switched networks on chip
Zhonghai Lu,Bei Yin,Axel Jantsch +2 more
TL;DR: A novel multicast scheme in wormhole-switched NoCs improves throughput, and does not exhibit significant impact on unicast performance in a network with mixed unicast and multicast traffic if the network is not saturated.