Linfang Wang

Linfang Wang

Linfang Wang is a 5th year Ph.D. candidate in Communication System Laboratory (CSL), Department of Electrical & Computer Engineering, University of California, Los Angeles

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portfolio

publications

A novel spread slotted ALOHA based on cognitive radio for satellite communications system

M. Jia, L. Wang, Z. Yin, Q. Guo, and X. Gu, "A Novel Spread Slotted ALOHA Based on Cognitive radio for Satellite Communications System", EURASIP Journal on Wireless Communications and Networking, J. Wireless Com. Network 2016, 232.

A Low Complexity Detection Algorithm for Fixed Up-Link SCMA System in Mission Critical Scenario

M. Jia, L. Wang, Q. Guo, X. Gu, and W. Xiang, "A Low Complexity Detection Algorithm for Fixed Up-Link SCMA System in Mission Critical Scenario", IEEE Internet of Things Journal, vol. 5, no. 5, pp. 3289-3297, Oct. 2018, doi: 10.1109/JIOT.2017.2696028.W

Routing Algorithm with Virtual Topology Toward to Huge Numbers of LEO Mobile Satellite Network Based on SDN

M. Jia, S. Zhu, L. Wang, Q. Guo, H. Wang, and Z. Liu, "Routing algorithm with virtual topology toward to huge numbers of LEO mobile satellite network based on SDN", Mobile Networks and Applications, 23(2), pp. 285-300, 2018.

Decoding Rate-Compatible 5G-LDPC Codes With Coarse Quantization Using the Information Bottleneck Method

M. Stark, L. Wang, G. Bauch, and R. D. Wesel, (2020). "Decoding Rate-Compatible 5G-LDPC Codes with Coarse Quantization Using the Information Bottleneck Method", IEEE Open Journal of the Communications Society, vol. 1, pp. 646-660, 2020.

Finite-Support Capacity-Approaching Distributions for AWGN Channels

D. Xiao, L. Wang, D. Song, and R. D. Wesel, "Finite-Support Capacity-Approaching Distributions for AWGN Channels", 2020 IEEE Information Theory Workshop (ITW), pp. 1-5.

Information bottleneck decoding of rate-compatible 5G-LDPC codes

M. Stark, L. Wang, G. Bauch, and R. D. Wesel, "Information bottleneck decoding of rate-compatible 5G-LDPC codes", 2020IEEE International Conference on Communications (ICC), pp. 1-6.

An Efficient Algorithm for Designing Optimal CRCs for Tail-Biting Convolutional Codes

H. Yang, L. Wang, V. Lau, and R. D. Wesel, "An Efficient Algorithm for Designing Optimal CRCs for Tail-Biting Convolutional Codes", 2020 IEEE International Symposium on Information Theory (ISIT), pp. 292-297, Los Angeles, USA, Jun. 22-26, 2020.

Comparison of Integrated and Independent RF/FSO Transceivers on a Fading Optical Channel

J. Nguyen, E. Liang, L. Wang, T. Drullinger, T. Chauvin, and R. D. Wesel, "Comparison of Integrated and Independent RF/FSO Transceivers on a Fading Optical Channel", 2020 Asilomar Conference on Signals, Systems, and Computers, pp. 699-701, Pacific Grove, CA, USA, Nov. 1-5, 2020.

A Reconstruction-Computation-Quantization (RCQ) Approach to Node Operations in LDPC Decoding

L. Wang, R. D. Wesel, M. Stark, and G. Bauch, "A Reconstruction-Computation-Quantization (RCQ) Approach to Node Operations in LDPC Decoding", 2020 IEEE Global Communications Conference (GLOBECOM), pp. 1-6，Taipei, Taiwan, Dec. 8–10, 2020.

FPGA Implementations of Layered MinSum LDPC Decoders Using RCQ Message Passing

Terrill, C., L. Wang, S. Chen, C. Hulse, C. Kuo, R. Wesel, and D. Divsalar, "FPGA Implementations of Layered MinSum LDPC Decoders Using RCQ Message Passing", 2021 IEEE Global Communications Conference (GLOBECOM), pp 1-6, Madrid, Spain, Dec. 7-11, 2021.

Neural-Network-Optimized Degree-Specific Weights for LDPC MinSum Decoding

L. Wang, S. Chen, J. Nguyen, D. Dariush, and R. Wesel, "Neural-Network-Optimized Degree-Specific Weights for LDPC MinSum Decoding", 2021 IEEE 11th International Symposium on Topics in Coding (ISTC), pp. 1-5, Aug.30 – Sept. 3, virtual conference, 2021.

Achieving Short-Blocklength RCU bound via CRC List Decoding of TCM with Probabilistic Shaping

L. Wang, S. Dan, A. Feliepe, and R. D. Wesel. "Achieving Short-Blocklength RCU bound via CRC List Decoding of TCM with Probabilistic Shaping." ICC 2022, Seoul, South Korea, May 16–20, 2022.

Neural Normalized Min-Sum Message-Passing vs. Viterbi Decoding for the CCSDS Line Product Code

J. Nguyen, L. Wang, C. Hulse , S. Dani, A. Antonini , T. Chauvin , D. Dariush, R. Wesel, Neural Normalized Min-Sum Message-Passing vs. Viterbi Decoding for the CCSDS Line Product Code." ICC 2022, Seoul, South Korea, May 16–20, 2022.

Reconstruction-Computation-Quantization (RCQ): A Paradigm for Low Bit Width LDPC Decoding

L. Wang, C. Terrill, M. Stark, Z. Li, S. Chen, C. Hulse, C. Kuo, R. Wesel, G. Bauch, R. Pitchumani, "Reconstruction-Computation-Quantization (RCQ): A Paradigm for Low Bit Width LDPC Decoding," in IEEE Transactions on Communications, vol. 70, no. 4, pp. 2213-2226, April 2022, doi: 10.1109/TCOMM.2022.3149913.

Low-density parity-check (LDCP) decoder of reconstruction-computation-quantization (RCQ) approach for a storage device.

L. Wang, R. Pitchumani, and Z. Li (2022, April 26). Low-density parity-check (LDCP) decoder of reconstruction-computation-quantization (RCQ) approach for a storage device.

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