2 citations · 3 across the 4 of their papers we have counts for
6 papers
Neural-Network-Optimized Degree-Specific Weights for LDPC MinSum Decoding
Linfang Wang, Sean Chen, Jonathan Nguyen +2
Neural Normalized MinSum (N-NMS) decoding delivers better frame error rate (FER) performance on linear block codes than conventional normalized MinSum (NMS) by assigning dynamic mu…
FPGA Implementations of Layered MinSum LDPC Decoders Using RCQ Message Passing
Caleb Terrill, Linfang Wang, Sean Chen +4
Non-uniform message quantization techniques such as reconstruction-computation-quantization (RCQ) improve error-correction performance and decrease hardware complexity of low-densi…
Finite-Support Capacity-Approaching Distributions for AWGN Channels
Derek Xiao, Linfang Wang, Richard D. Wesel
In this paper, the Dynamic-Assignment Blahut-Arimoto (DAB) algorithm identifies finite-support probability mass functions (PMFs) with small cardinality that achieve capacity for am…
A Reconstruction-Computation-Quantization (RCQ) Approach to Node Operations in LDPC Decoding
Linfang Wang, Maximilian Stark, Richard D. Wesel +1
In this paper, we propose a finite-precision decoding method that features the three steps of Reconstruction, Computation, and Quantization (RCQ). Unlike Mutual-Information-Maximiz…
An Efficient Algorithm for Designing Optimal CRCs for Tail-Biting Convolutional Codes
Hengjie Yang, Linfang Wang, Vincent Lau +1
Cyclic redundancy check (CRC) codes combined with convolutional codes yield a powerful concatenated code that can be efficiently decoded using list decoding. To help design such sy…
Information Bottleneck Decoding of Rate-Compatible 5G-LDPC Codes
Maximilian Stark, Linfang Wang, Richard D. Wesel +1
The new 5G communications standard increases data rates and supports low-latency communication that places constraints on the computational complexity of channel decoders. 5G low-d…