149 citations · 182 across the 19 of their papers we have counts for
26 papers
Machine Learning-Aided Efficient Decoding of Reed-Muller Subcodes
Mohammad Vahid Jamali, Xiyang Liu, Ashok Vardhan Makkuva +3
Reed-Muller (RM) codes achieve the capacity of general binary-input memoryless symmetric channels and are conjectured to have a comparable performance to that of random codes in te…
Low-Complexity Decoding of a Class of Reed-Muller Subcodes for Low-Capacity Channels
Mohammad Vahid Jamali, Mohammad Fereydounian, Hessam Mahdavifar +1
We present a low-complexity and low-latency decoding algorithm for a class of Reed-Muller (RM) subcodes that are defined based on the product of smaller RM codes. More specifically…
ProductAE: Towards Training Larger Channel Codes based on Neural Product Codes
Mohammad Vahid Jamali, Hamid Saber, Homayoon Hatami +1
There have been significant research activities in recent years to automate the design of channel encoders and decoders via deep learning. Due the dimensionality challenge in chann…
KO codes: Inventing Nonlinear Encoding and Decoding for Reliable Wireless Communication via Deep-learning
Ashok Vardhan Makkuva, Xiyang Liu, Mohammad Vahid Jamali +3
Landmark codes underpin reliable physical layer communication, e.g., Reed-Muller, BCH, Convolution, Turbo, LDPC and Polar codes: each is a linear code and represents a mathematical…
Coded Computing via Binary Linear Codes: Designs and Performance Limits
Mahdi Soleymani, Mohammad Vahid Jamali, Hessam Mahdavifar
We consider the problem of coded distributed computing where a large linear computational job, such as a matrix multiplication, is divided into smaller tasks, encoded using an…
Reed-Muller Subcodes: Machine Learning-Aided Design of Efficient Soft Recursive Decoding
Mohammad Vahid Jamali, Xiyang Liu, Ashok Vardhan Makkuva +3
Reed-Muller (RM) codes are conjectured to achieve the capacity of any binary-input memoryless symmetric (BMS) channel, and are observed to have a comparable performance to that of…