Related papers: Risk-Sensitive Reinforcement Learning for URLLC Tr…
This paper presents a machine learning strategy that tackles a distributed optimization task in a wireless network with an arbitrary number of randomly interconnected nodes. Individual nodes decide their optimal states with distributed…
In this paper, we study how to solve resource allocation problems in ultra-reliable and low-latency communications by unsupervised deep learning, which often yield functional optimization problems with quality-of-service (QoS) constraints.…
One fundamental challenge in 5G URLLC is how to optimize massive MIMO systems for achieving low latency and high reliability. A natural design choice to maximize reliability and minimize retransmission is to select the lowest allowed target…
In visible light communication (VLC) diverse types of traffic are supported while the number of optical channels is limited. In this paper we propose a dynamic channel reservation scheme for higher priority calls that does not reduce the…
The use of Reconfigurable Intelligent Surfaces (RIS) technology to extend coverage and allow for better control of the wireless environment has been proposed in several use cases, including Ultra-Reliable Low-Latency Communications (URLLC),…
Distributed Opportunistic Scheduling (DOS) techniques have been recently proposed to improve the throughput performance of wireless networks. With DOS, each station contends for the channel with a certain access probability. If a contention…
This paper investigates a smart spectrum-sharing framework for reconfigurable intelligent surface (RIS)-aided local high-quality wireless networks (LHQWNs) within a mobile network operator (MNO) ecosystem. Although RISs are often considered…
Unmanned Aerial Vehicles need an online path planning capability to move in high-risk missions in unknown and complex environments to complete them safely. However, many algorithms reported in the literature may not return reliable…
This paper is about optimally controlling skill-based queueing systems such as data centers, cloud computing networks, and service systems. By means of a case study using a real-world data set, we investigate the practical implementation of…
Ultra-reliable, low latency communications (URLLC) are currently attracting significant attention due to the emergence of mission-critical applications and device-centric communication. URLLC will entail a fundamental paradigm shift from…
Power consumption is one of the major issues in massive MIMO (multiple input multiple output) systems, causing increased long-term operational cost and overheating issues. In this paper, we consider per-antenna power allocation with a given…
We present a method that addresses the pain point of long lead-time required to deploy cell-level parameter optimisation policies to new wireless network sites. Given a sequence of action spaces represented by overlapping subsets of…
Modern navigation algorithms based on deep reinforcement learning (RL) show promising efficiency and robustness. However, most deep RL algorithms operate in a risk-neutral manner, making no special attempt to shield users from relatively…
The application of reinforcement learning (RL) to dynamic resource allocation in optical networks has been the focus of intense research activity in recent years, with almost 100 peer-reviewed papers. We present a review of progress in the…
This paper studies robust resource allocation algorithm design for a multiuser multiple-input single-output (MISO) cognitive radio (CR) downlink communication network. We focus on a secondary system which provides unicast secure wireless…
This paper introduces an efficient reactive routing protocol considering the mobility and the reliability of a node in Cognitive Radio Sensor Networks (CRSNs). The proposed protocol accommodates the dynamic behavior of the spectrum…
In wireless ad-hoc networks, forwarding data through intermediate relays extends the coverage area and enhances the network throughput. We consider a general wireless multiuser multihop transmission, where each data flow is subject to a…
We consider optimal sensor scheduling with unknown communication channel statistics. We formulate two types of scheduling problems with the communication rate being a soft or hard constraint, respectively. We first present some structural…
Visible light communication (VLC) is a promising solution to satisfy the extreme demands of emerging applications. VLC offers bandwidth that is orders of magnitude higher than what is offered by the radio spectrum, hence making best use of…
Diffusion models are vastly used in generative AI, leveraging their capability to capture complex data distributions. However, their potential remains largely unexplored in the field of resource allocation in wireless networks. This paper…