Our paper “Compressed Training for Dual-Wideband Time-Varying Sub-Terahertz Massive MIMO,” coauthored with my former Ph.D. student Tzu-Hsuan Chou and colleagues at Purdue University, David J. Love and James V. Krogmeier, has been accepted on the IEEE Transactions on Communications! 6G operators may use millimeter wave (mmWave) and sub-terahertz (sub-THz) bands to meet the ever-increasing demand…

Our paper “MAESTRO-X: Distributed Orchestration of Rotary-Wing UAV-Relay Swarms,” co-authored with Ph.D. students Bharath Keshavamurthy (ASU) and Matt Bliss (Purdue Univerisity) has been accepted on the IEEE Transactions on Cognitive Communications and Networking! Congratulations Bharath and Matt! This work details a scalable framework to orchestrate a swarm of rotary-wing UAVs serving as cellular relays to…

Tzu-Hsuan Chou (Purdue University) successfully defended his Ph.D. thesis “Channel Training and Signal Processing for massive MIMO Wireless Communications.” Congratulations Tzu-Hsuan!

Our paper “Finite-Bit Quantization For Distributed Algorithms With Linear Convergence” has been accepted for publication at the IEEE Transactions on Information Theory! Co-authored with Gesualdo Scutari and Chang-Shen Lee. This paper studies distributed algorithms for (strongly convex) composite optimization problems over mesh networks, subject to quantized communications. Instead of focusing on a specific algorithmic design,…

Our paper “Multi-Stage Hybrid Federated Learning Over Large-Scale D2D-Enabled Fog Networks” has been accepted for publication at the IEEE/ACM Transactions on Networking! Authors: Seyyedali Hosseinalipour, Sheikh Shams Azam, Christopher G. Brinton, Nicolò Michelusi, Vaneet Aggarwal, David J. Love, Huaiyu Dai. Federated learning has generated significant interest, with nearly all works focused on a “star” topology…

Our paper “Learning-based Spectrum Sensing in Cognitive Radio Networks via Approximate POMDPs” has been accepted for publication at the IEEE Transactions on Cognitive Communications and Networking! Co-authored by Bharath Keshavamurthy and myself. A novel LEarning-based Spectrum Sensing and Access (LESSA) framework is proposed, wherein a cognitive radio (CR) learns a time-frequency correlation model underlying spectrum…

Our paper “Learning and Adaptation for Millimeter-Wave Beam Tracking and Training: a Dual Timescale Variational Framework ” has been accepted for publication at the IEEE JSAC special issue on Machine Learning in Communications and Networks! Co-authored by Muddassar Hussain and myself. Millimeter-wave vehicular networks incur enormous beam-training overhead to enable narrow-beam communications. This paper proposes a…

Our paper “Semi-Decentralized Federated Learning with Cooperative D2D Local Model Aggregations” has been accepted for publication at the IEEE JSAC special issue on Distributed Learning over Wireless Edge Networks! Co-authored by Frank Po-Chen Lin, Seyyedali Hosseinalipour, Sheikh Shams Azam, Christopher G. Brinton, and myself. Federated learning has emerged as a popular technique for distributing machine learning…