This paper extends the paradigm of “mobile edge learning (MEL)” by designing an energy-
aware optimal task allocation scheme for training a machine learning (ML) model in a semi …

We consider the problem of maximizing the minimum user achievable rate for downlink
massive MIMO multi-user systems. The max-min formulation promotes fairness such that all …

In order to construct the digital twin (DT) of the manufacturing process in industrial IoT (IIoT)
systems, multiple sensors and IIoT equipments (IIEs) are deployed for process monitoring …

This paper investigates the scalability ability of Graph Neural Network (GNN) for solving
resource allocation problems in wireless networks. Although GNNs are able to work on …

Over-the-air computation (AirComp) has recently been recognized as a promising scheme
for a fusion center to achieve fast distributed data aggregation in wireless networks via …

The heavy reliance on hardware hinders the innovation in information systems ranging from
the most front-end devices to the most back-end servers. It has been shown as a compelling …

The problem of weighted sum-rate maximisation in a multi-cell multi-user downlink system is
NP-hard and complicated to solve even for Multiple Input Single Output scheme (MISO). In …

Multi-group multicast beamforming in wireless systems with large antenna arrays and
massive audience is investigated in this paper. Multicast beamforming design is a well …

A portfolio optimization problem is a convex optimization problem that involves a linear
objective function with quadratic constraints. One method for solving portfolio optimization …

The use of massive multiple-input multiple-output (MIMO) base stations in heterogeneous
networks (HetNets) offers an increase in throughput without increasing the bandwidth, but …