149 citations · 539 across the 71 of their papers we have counts for
80 papers
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…
On the Advantages of Asynchrony in the Unsourced MAC
Alexander Fengler, Alejandro Lancho, Krishna Narayanan +1
In this work we demonstrate how a lack of synchronization can in fact be advantageous in the problem of random access. Specifically, we consider a multiple-access problem over a fr…
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…
HashBeam: Enabling Feedback Through Downlink Beamforming in Unsourced Random Access
Jamison R. Ebert, Krishna R. Narayanan, Jean-Francois Chamberland
Unsourced random access (URA) has emerged as a candidate paradigm for massive machine-type communication (MTC) in next-generation wireless networks. While many excellent uplink sch…