MP5b.1

A Memory-Based Reinforcement Learning Approach to Integrated Sensing and Communication

Homa Nikbakht, Princeton University, United States; Michèle Wigger, Télécom Paris, France; Shlomo Shamai (Shitz), Technion, Israel; H. Vincent Poor, Princeton University, United States
Session:
MP5b: Machine Learning for Integrated Sensing and Communications Lecture
Track:
Array Processing and Multisensor Systems
Location:
Toyon
Presentation Time:
Mon, 28 Oct, 15:30 - 15:55 PT (UTC -7)
Presentation
Discussion
Resources
No resources available.
Session MP5b
MP5b.1: A Memory-Based Reinforcement Learning Approach to Integrated Sensing and Communication
Homa Nikbakht, Princeton University, United States; Michèle Wigger, Télécom Paris, France; Shlomo Shamai (Shitz), Technion, Israel; H. Vincent Poor, Princeton University, United States
MP5b.2: GFlowNet-Based Antenna Selection for ISAC Systems under the Presence of Eavesdroppers
Spilios Evmorfos, Athina Petropulu, Rutgers University, United States
MP5b.3: Beamspace and Frequency Domain ISAC Resource Allocation using Reinforcement Learning
Majdoddin Esfandiari, Petteri Pulkkinen, Visa Koivunen, Aalto university, Finland
MP5b.4: SPARSE NEURAL PRECODERS FOR DISTRIBUTED ISAC
Soumyadeep Chatterjee, R.S. Prasobh Sankar, Sundeep Prabhakar Chepuri, Indian Institute of Science Bengaluru, India
Contacts