Capacity-achieving guessing random additive noise decoding
We introduce a new algorithm for realizing maximum likelihood (ML) decoding for arbitrary
codebooks in discrete channels with or without memory, in which the receiver rank-orders …
codebooks in discrete channels with or without memory, in which the receiver rank-orders …
Guessing random additive noise decoding with soft detection symbol reliability information-SGRAND
We recently introduced a noise-centric algorithm, Guessing Random Additive Noise
Decoding (GRAND), that identifies a Maximum Likelihood (ML) decoding for arbitrary code …
Decoding (GRAND), that identifies a Maximum Likelihood (ML) decoding for arbitrary code …
Guessing random additive noise decoding with symbol reliability information (SRGRAND)
The design and implementation of error correcting codes has long been informed by two
fundamental results: Shannon's 1948 capacity theorem, which established that long codes …
fundamental results: Shannon's 1948 capacity theorem, which established that long codes …
Linear MMSE-optimal turbo equalization using context trees
K Kim, N Kalantarova, SS Kozat… - IEEE Transactions on …, 2013 - ieeexplore.ieee.org
Formulations of the turbo equalization approach to iterative equalization and decoding vary
greatly when channel knowledge is either partially or completely unknown. Maximum …
greatly when channel knowledge is either partially or completely unknown. Maximum …
[PDF][PDF] Capacity-achieving guessing random additive noise decoding (GRAND),”
We introduce a new algorithm for realizing Maximum Likelihood (ML) decoding in discrete
channels with or without memory. In it, the receiver rank orders noise sequences from most …
channels with or without memory. In it, the receiver rank orders noise sequences from most …
基于线性MMSE 的Volterra 信道Turbo 均衡算法
郭业才， 马伟伟， 张珊， 周润之 - 系统仿真学报, 2016 - china-simulation.com
非线性码间干扰是影响卫星通信的重要因素之一, 需要有效消除或降低这种影响. 在用Volterra
级数分解表示非线性信道基础上, 提出了基于线性MMSE (Minimum Mean Square Error) …
级数分解表示非线性信道基础上, 提出了基于线性MMSE (Minimum Mean Square Error) …
Low complexity turbo equalizations and lower bounds on information rate for intersymbol interference channels.
S Jeong - 2011 - conservancy.umn.edu
In this research, low complexity turbo equalization algorithms are examined as an
alternatives to the optimal, but, much more complex, Bahl-Cocke-Jelinek-Raviv (BCJR) …
alternatives to the optimal, but, much more complex, Bahl-Cocke-Jelinek-Raviv (BCJR) …
On Linear MMSE Based Turbo-equalization of Nonlinear Volterra Channels
Y Guo, W Ma, Z Shan, R Zhou - Journal of …, 2020 - dc-china-simulation …
Nonlinear intersymbol interference is one of the important factors affecting the satellite
channel, and it is very necessary to eliminate and reduce the effect. On the basis of using the …
channel, and it is very necessary to eliminate and reduce the effect. On the basis of using the …
Capacity-Achieving Guessing Random Additive Noise Decoding
J Li - 2019 - dspace.mit.edu
We introduce a new algorithm for realizing maximum likelihood (ML) decoding for arbitrary
codebooks in discrete channels with or without memory, in which the receiver rank-orders …
codebooks in discrete channels with or without memory, in which the receiver rank-orders …
Linear MMSE-Optimal Turbo Equalization Using Context Trees
Formulations of the turbo equalization approach to iterative equalization and decoding vary
greatly when channel knowledge is either partially or completely unknown. Maximum …
greatly when channel knowledge is either partially or completely unknown. Maximum …