6 accepted papers
This paper investigates channel-aware decision fusion empowered by massive MIMO systems and reconfigurable intelligent surfaces (RIS). By integrating both, we aim to improve goal-oriented (fusion) performance despite the unique propagation challenges introduced. Specifically, we investigate traditio…
This work addresses the issue of energy efficiency maximization in a multi-user network aided by a reconfigurable intelligent surface (RIS) with global reflection capabilities. Two optimization methods are proposed to optimize the mobile users’ powers, the RIS coefficients, and the linear receive fi…
In this paper, we propose a deep learning based approach to design online power control policies for large EH networks, which are often intractable stochastic control problems. In the proposed approach, for a given EH network, the optimal on-line power control rule is learned by training a deep neur…
This paper investigates the use of a Passive Intelligent Mirrors (PIM) to operate a multi-user MISO downlink communication. The transmit powers and the mirror reflection coefficients are designed for sum-rate maximization subject to individual QoS guarantees to the mobile users. The resulting proble…
We consider the global energy efficiency (GEE) maximization problem for the general non-regenerative MIMO relay network, under the maximum power constraints for each user and each relay. The problem is reformulated through the fractional optimization technique, and the mean square error receiver fil…
State-of-the-art algorithms for energy-efficient power allocation in wireless networks are based on fractional programming theory, and allow to find the global maximum of the energy efficiency only in noise-limited scenarios. In interference-limited scenarios, several sub-optimal solutions have been…