Efficient use of spectral and energy resources is critical in wireless networks and has been
extensively studied in recent years. In particular, dynamic spectrum access and power …

Optimal resource allocation is a fundamental challenge for dense and heterogeneous
wireless networks with massive wireless connections. Because of the non-convex nature of …

Multicell power control for sum rate maximization (SRM) is a widely-studied non-convex
resource allocation problem in wireless communication systems. Due to the high complexity …

We consider the problem of downlink power control in wireless networks, consisting of
multiple transmitter-receiver pairs communicating with each other over a single shared …

The power control is a significant technique for suppressing co-channel interference that
severely limits the capacity and connectivity of multi-cell communication systems. In this …

In current research, reinforcement learning (RL) is widely applied to resource management
of wireless communication networks. However, many optimization problems have high …

Many of the existing optimization-based transmit power control algorithms suffer from high
computational complexity and require instantaneous global channel state information (CSI) …

We consider the problem of power control in wireless networks, consisting of multiple
transmitter-receiver pairs communicating with each other over a single shared wireless …

With the increasing number of base stations (BSs) and network densification in 5G,
interference management using link scheduling and power control are vital for better …

Deep reinforcement learning offers a model-free alternative to supervised deep learning and
classical optimization for solving the transmit power control problem in wireless networks …