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Advisor: Shahin Mukalel Abdulla
Chair: Anandhu Balachandran
Advisor: Asma Mohammadi
Chair: Mohammed Nizar Javeed
Advisor: Reenu George
Chair: Navya Prasad
Advisor: Sharath Chandra Inguva
Chair: Bhanusree Venkata Nallamothu
Advisor: Subramanyam V. Makam
Chair: Bindhu Madhavi Pavalla
Section: Events
Date: 29 March 2023
Time: 3:00 PM ET (New York Time)
Speaker(s): Dr. Gerald Matz
Section: Events
Date: 27-29 September 2023
Location: Poitiers, France
Section: Publications & Resources
Publication: IEEE Journal of Selected Topics in Signal Processing
The papers in this special section focus on distributed signal processing for edge learning (EL). EL is a new and promising technology for implementing artificial intelligence (AI) algorithms at edge devices over wireless networks.
Section: Publications & Resources
Publication: IEEE Journal of Selected Topics in Signal Processing
To process and transfer large amounts of data in emerging wireless services, it has become increasingly appealing to exploit distributed data communication and learning. Specifically, edge learning (EL) enables local model training on geographically disperse edge nodes and minimizes the need for frequent data exchange.
Section: Publications & Resources
Publication: IEEE Journal of Selected Topics in Signal Processing
The explosive growth of dynamic and heterogeneous data traffic brings great challenges for 5G and beyond mobile networks. To enhance the network capacity and reliability, we propose a learning-based dynamic time-frequency division duplexing (D-TFDD) scheme that adaptively allocates the uplink and downlink time-frequency resources of base stations (BSs) to meet the asymmetric and heterogeneous traffic demands while alleviating the inter-cell interference.
