Cooperation among multiple base stations (BSs) improves both communication and sensing in integrated sensing and communication (ISAC) networks. However, it requires deciding which BSs serve each communication user (CU) and each target, and how each BS beamforms. In this work, we consider joint BS-CU and BS-target assoc...
Abhishek Rajasekaran, Mehdi Karbalayghareh, Xiao-Yan Ma et al.· 0 citations
Most federated learning (FL) studies implicitly assume that training data is readily available at participating edge devices. In practice, this data must first be acquired through heterogeneous sensors with potentially different measurement modalities, and the quality and cost of this acquisition process can directly a...
Mehdi Karbalayghareh, D. J. Love, Christopher G. Brinton· 0 citations
The AISAC landscape is presented, why imperfect sensing changes the learning problem, the closed-loop architecture and its three-way sensing-communication-learning tension are developed, and a vehicular edge-intelligence use case is outlined together with open problems for theory, implementation, and standardization.
Mehdi Karbalayghareh, A. Rajasekaran, Xiao-Yan Ma et al.· arXiv.org· 1 citation
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