collaborators

6 papers

cs.IT2026

Distributed Edge Learning under Imperfect Data Sensing

Mehdi Karbalayghareh, David J. Love, Christopher G. Brinton

Distributed learning systems typically assume that local data is already available at clients with fixed quality, while in practice, data is sensed through imperfect physical proce…

cs.IT2026

AISAC: Closing the Loop Between AI and Integrated Sensing and Communication for 6G

Mehdi Karbalayghareh, Abhishek Rajasekaran, Xiaoyan Ma +2

Integrated sensing and communication (ISAC) and AI-and-communication (AIAC) are identified as separate usage scenarios in the ITU IMT-2030 vision for sixth-generation (6G) networks…

eess.SP2026

Optimal Multi-RIS Placement: Coverage-Guaranteed Sum Rate Maximization Under Inhomogeneous User Distributions

Abhishek Rajasekaran, Mehdi Karbalayghareh, Xiaoyan Ma +3

Reconfigurable Intelligent Surface (RIS) has emerged as a promising next-generation technology that improves the throughput and coverage of a wireless system. The realization of th…

cs.IT2026

Coherence-Aware Over-the-Air Distributed Learning under Heterogeneous Link Impairments

Mehdi Karbalayghareh, David J. Love, Christopher G. Brinton

Distributed machine learning (ML) over wireless networks hinges on accurate channel state information (CSI) and efficient exchange of high-dimensional model updates. These demands…

eess.SP2025

Optimal RIS Placement in Multi-User MISO Systems with User Randomness

Abhishek Rajasekaran, Mehdi Karbalayghareh, Xiaoyan Ma +2

It is well established that the performance of reconfigurable intelligent surface (RIS)-assisted systems critically depends on the optimal placement of the RIS. Previous works cons…

cs.IT2025

Coherence-Aware Distributed Learning under Heterogeneous Downlink Impairments

Mehdi Karbalayghareh, David J. Love, Christopher G. Brinton

The performance of federated learning (FL) over wireless networks critically depends on accurate and timely channel state information (CSI) across distributed devices. This require…