6 papers
Towards Robust Semantic Video Transmission over Block Erasure Channels
Nargis Fayaz, Homa Esfahanizadeh, Matin Mortaheb +2
This paper investigates semantic-aware neural joint source-channel coding (JSCC) for robust video transmission over block erasure channels. We propose a neural video compression fr…
Finite-Blocklength Lossy Joint Source-Channel Coding over Unknown Channels
Adeel Mahmood, Harish Viswanathan, Jinfeng Du
We analyze the finite-blocklength performance of lossy joint source-channel codes (JSCC) in an unknown-channel framework, where the true channel is unknown but the source distribut…
Block Erasure-Aware Semantic Multimedia Compression via JSCC Autoencoder
Homa Esfahanizadeh, Nargis Fayaz, Jinfeng Du +1
We present an AI-based framework for semantic transmission of multimedia data over band-limited, time-varying channels. The method targets scenarios where large content is split in…
Demonstrating Interoperable Channel State Feedback Compression with Machine Learning
Dani Korpi, Rachel Wang, Jerry Wang +20
Neural network-based compression and decompression of channel state feedback has been one of the most widely studied applications of machine learning (ML) in wireless networks. Var…
Beamforming with hybrid reconfigurable parasitic antenna arrays
Nitish Vikas Deshpande, Miguel Rodrigo Castellanos, Saeed R. Khosravirad +3
A parasitic reconfigurable antenna array is a low-power approach for beamforming using passive tunable elements. Prior work on reconfigurable antennas in communication theory is ba…
Energy-Efficient Flat Precoding for MIMO Systems
Foad Sohrabi, Carl Nuzman, Jinfeng Du +2
This paper addresses the suboptimal energy efficiency of conventional digital precoding schemes in multiple-input multiple-output (MIMO) systems. Through an analysis of the power a…