Learning Codes for Interference Channels
Interference Channels A two-user interference channel is a canonical model for multiple one-to-one communications, where two transmitters wish to communicate... Continue
Leveraging Deep Learning for Practical Distributed Source Coding
Distributed Source Coding Distributed source coding (DSC) refers to the task of compressing multiple correlated data sources that are encoded... Continue
Neural Augmented Min-Sum decoders using Model-based ML
In the previous post, we saw how model-based machine learning can help in boosting the performance of Turbo decoders. In... Continue
Turbo Decoding via Model-based ML
The unparalleled success of deep learning in various domains has revolutionized the way we approach problem-solving in areas such as... Continue
Learning-Based Coded Computation Part 2
In the previous post, we provided a background on coded computation and its challenges, described the potential for machine learning... Continue
Learning-Based Coded Computation Part 1
This two-part blog post aims to provide a gentle introduction to recent work showing the efficacy of using machine learning... Continue
Decoding convolutional codes
The Viterbi algorithm exactly computes the Maximum Likelihood (ML) estimate of the transmitted convolutional codeword over an AWGN (additive white... Continue
Introduction and Mission Statement
Reliable digital communication, both wireline (ethernet, cable and DSL modems) and wireless (cellular, Wifi, satellite), is a primary workhorse of... Continue
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