Related papers: Multi-Agent Reinforcement Learning for Adaptive Us…
Resilience is defined as the ability of a network to resist, adapt, and quickly recover from disruptions, and to continue to maintain an acceptable level of services from users' perspective. With the advent of future radio networks,…
The fifth generation (5G) mobile networks are envisioned to support the deluge of data traffic with reduced energy consumption and improved quality of service (QoS) provision. To this end, the key enabling technologies, such as…
This paper presents a method for optimizing wireless networks by adjusting cell parameters that affect both the performance of the cell being optimized and the surrounding cells. The method uses multiple reinforcement learning agents that…
Ultra network densification and Massive MIMO are considered major 5G enablers since they promise huge capacity gains by exploiting proximity, spectral and spatial reuse benefits. Both approaches rely on increasing the number of access…
With the proliferation of mobile terminals and the continuous upgrading of services, 4G LTE networks are showing signs of weakness. To enhance the capacity of wireless networks, millimeter waves are introduced to drive the evolution of…
Future generations of mobile networks are expected to contain more and more antennas with growing complexity and more parameters. Optimizing these parameters is necessary for ensuring the good performance of the network. The scale of mobile…
The fifth generation of wireless communications (5G) promises massive increases in traffic volume and data rates, as well as improved reliability in voice calls. Jointly optimizing beamforming, power control, and interference coordination…
User association is necessary in dense millimeter wave (mmWave) networks to determine which base station a user connects to in order to balance base station loads and maximize throughput. Given that mmWave connections are highly directional…
We study the problem of user association, namely finding the optimal assignment of user equipment to base stations to achieve a targeted network performance. In this paper, we focus on the knowledge transferability of association policies.…
To integrate high amounts of renewable energy resources, electrical power grids must be able to cope with high amplitude, fast timescale variations in power generation. Frequency regulation through demand response has the potential to…
We consider a dynamic millimeter-wave network with integrated access and backhaul, where mobile relay nodes move to auto-reconfigure the wireless backhaul. Specifically, we focus on in-band relaying networks, which conduct access and…
Traditional radio systems are strictly co-designed on the lower levels of the OSI stack for compatibility and efficiency. Although this has enabled the success of radio communications, it has also introduced lengthy standardization…
Commonly considered user association frameworks in millimeter-wave communications are based on the sum rate maximization, and they essentially neglect user specific rate and service requirements. Furthermore, new features of millimeter-wave…
Multi-agent reinforcement learning systems aim to provide interacting agents with the ability to collaboratively learn and adapt to the behaviour of other agents. In many real-world applications, the agents can only acquire a partial view…
We propose a mechanism for distributed resource management and interference mitigation in wireless networks using multi-agent deep reinforcement learning (RL). We equip each transmitter in the network with a deep RL agent that receives…
Effective solutions for intelligent data collection in terrestrial cellular networks are crucial, especially in the context of Internet of Things applications. The limited spectrum and coverage area of terrestrial base stations pose…
This work investigates the use of deep learning to perform user cell association for sum-rate maximization in Massive MIMO networks. It is shown how a deep neural network can be trained to approach the optimal association rule with a much…
The dynamic and evolutionary nature of service requirements in wireless networks has motivated the telecom industry to consider intelligent self-adapting Reinforcement Learning (RL) agents for controlling the growing portfolio of network…
Envisioned for fifth generation (5G) systems, millimeter-wave (mmWave) communications are under very active research worldwide. Although pencil beams with accurate beamtracking may boost the throughput of mmWave systems, this poses great…
With the development of the 5G and Internet of Things, amounts of wireless devices need to share the limited spectrum resources. Dynamic spectrum access (DSA) is a promising paradigm to remedy the problem of inefficient spectrum utilization…