A survey on radio resource allocation in cognitive radio sensor networks
Wireless sensor networks (WSNs) use the unlicensed industrial, scientific, and medical
(ISM) band for transmissions. However, with the increasing usage and demand of these …
(ISM) band for transmissions. However, with the increasing usage and demand of these …
Survey on Q-learning-based position-aware routing protocols in flying ad hoc networks
A flying ad hoc network (FANETs), also known as a swarm of unmanned aerial vehicles
(UAVs), can be deployed in a wide range of applications including surveillance, monitoring …
(UAVs), can be deployed in a wide range of applications including surveillance, monitoring …
Q-FANET: Improved Q-learning based routing protocol for FANETs
Abstract Flying Ad-Hoc Networks (FANETs) introduce ad-hoc networking into the context of
flying nodes, allowing real-time communication between these nodes and ground control …
flying nodes, allowing real-time communication between these nodes and ground control …
Top-push video-based person re-identification
Most existing person re-identification (re-id) models focus on matching still person images
across disjoint camera views using the setting of either single-shot or multi-shot. Since …
across disjoint camera views using the setting of either single-shot or multi-shot. Since …
A survey of dynamic spectrum allocation based on reinforcement learning algorithms in cognitive radio networks
Y Wang, Z Ye, P Wan, J Zhao - Artificial intelligence review, 2019 - Springer
Cognitive radio is an emerging technology that is considered to be an evolution for software
device radio in which cognition and decision-making components are included. The main …
device radio in which cognition and decision-making components are included. The main …
A comprehensive survey of machine learning applied to radar signal processing
P Lang, X Fu, M Martorella, J Dong, R Qin… - arxiv preprint arxiv …, 2020 - arxiv.org
Modern radar systems have high requirements in terms of accuracy, robustness and real-
time capability when operating on increasingly complex electromagnetic environments …
time capability when operating on increasingly complex electromagnetic environments …
Decentralized automotive radar spectrum allocation to avoid mutual interference using reinforcement learning
Nowadays, mutual interference among automotive radars has become a problem of wide
concern. In this article, a decentralized spectrum allocation approach is presented to avoid …
concern. In this article, a decentralized spectrum allocation approach is presented to avoid …
A survey on machine learning algorithms for applications in cognitive radio networks
In this paper, we present a survey on the utility of machine learning (ML) algorithms for
applications in cognitive radio networks (CRN). We start with a high-level overview of some …
applications in cognitive radio networks (CRN). We start with a high-level overview of some …
An effective spectrum handoff based on reinforcement learning for target channel selection in the industrial Internet of Things
The overcrowding of the wireless space has triggered a strict competition for scare network
resources. Therefore, there is a need for a dynamic spectrum access (DSA) technique that …
resources. Therefore, there is a need for a dynamic spectrum access (DSA) technique that …
Distributed learning-based resource allocation for self-organizing c-v2x communication in cellular networks
In this paper, we investigate a resource allocation problem for a Cellular Vehicle to
Everything (C-V2X) network to improve energy efficiency of the system. To address this …
Everything (C-V2X) network to improve energy efficiency of the system. To address this …