4 papers
Federated Double Deep Q-learning for Joint Delay and Energy Minimization in IoT networks
Sheyda Zarandi, Hina Tabassum
In this paper, we propose a federated deep reinforcement learning framework to solve a multi-objective optimization problem, where we consider minimizing the expected long-term tas…
Delay Minimization in Sliced Multi-Cell Mobile Edge Computing (MEC) Systems
Sheyda Zarandi, Hina Tabassum
We consider the problem of jointly optimizing users' offloading decisions, communication and computing resource allocation in a sliced multi-cell mobile edge computing (MEC) networ…
Multi-Objective Energy Efficient Resource Allocation and User Association for In-band Full Duplex Small-Cells
Sheyda Zarandi, Ata Khalili, Mehdi Rasti +1
In this paper, we develop a framework to maximize the network energy efficiency (EE) by optimizing joint user-base station~(BS) association,~subchannel assignment, and power contro…
Multi-Objective Optimization for Energy-and Spectral-Efficiency Tradeoff in In-band Full-Duplex (IBFD) Communication
Ata Khalili, Sheyda Zarandi, Mehdi Rasti +1
The problem of joint power and sub-channel allocation to maximize energy efficiency (EE) and spectral efficiency (SE) simultaneously in in-band full-duplex (IBFD) orthogonal freque…