22 citations · 102 across the 45 of their papers we have counts for
7 papers · 1 filter
Coding for the unsourced A-channel with erasures: the linked loop code
William W. Zheng, Jamison R. Ebert, Stefano Rini +1
The A-channel is a noiseless multiple access channel in which users simultaneously transmit Q-ary symbols and the receiver observes the set of transmitted symbols, but not their mu…
Sparse Regression LDPC Codes
Jamison R. Ebert, Jean-Francois Chamberland, Krishna R. Narayanan
This article introduces a novel concatenated coding scheme called sparse regression LDPC (SR-LDPC) codes. An SR-LDPC code consists of an outer non-binary LDPC code and an inner spa…
Transformers are Provably Optimal In-context Estimators for Wireless Communications
Vishnu Teja Kunde, Vicram Rajagopalan, Chandra Shekhara Kaushik Valmeekam +4
Pre-trained transformers exhibit the capability of adapting to new tasks through in-context learning (ICL), where they efficiently utilize a limited set of prompts without explicit…
LLMZip: Lossless Text Compression using Large Language Models
Chandra Shekhara Kaushik Valmeekam, Krishna Narayanan, Dileep Kalathil +2
We provide new estimates of an asymptotic upper bound on the entropy of English using the large language model LLaMA-7B as a predictor for the next token given a window of past tok…
Scalable Cell-Free Massive MIMO Unsourced Random Access System
Michail Gkagkos, Jean-Francois Chamberland, Costas N. Georghiades +1
Cell-Free Massive MIMO systems aim to expand the coverage area of wireless networks by replacing a single high-performance Access Point (AP) with multiple small, distributed APs co…
PolarAir: A Compressed Sensing Scheme for Over-the-Air Federated Learning
Michail Gkagkos, Krishna R. Narayanan, Jean-Francois Chamberland +1
We explore a scheme that enables the training of a deep neural network in a Federated Learning configuration over an additive white Gaussian noise channel. The goal is to create a…
On Sparse Regression LDPC Codes
Jamison R. Ebert, Jean-Francois Chamberland, Krishna R. Narayanan
Belief propagation applied to iterative decoding and sparse recovery through approximate message passing (AMP) are two research areas that have seen monumental progress in recent d…