RL-IoT: Reinforcement learning-based routing approach for cognitive radio-enabled IoT communications
Internet of Things (IoT) devices are widely being used in various smart applications and
being equipped with cognitive radio (CR) capabilities for dynamic spectrum allocation. Our …
being equipped with cognitive radio (CR) capabilities for dynamic spectrum allocation. Our …
Energy aware cluster based routing protocol over distributed cognitive radio sensor network
Cognitive radio sensor network (CRSN) is a combination of wireless sensor network (WSN)
and opportunistic spectrum access technology. It involves the issues related to energy and …
and opportunistic spectrum access technology. It involves the issues related to energy and …
A survey and performance evaluation of reinforcement learning based spectrum aware routing in cognitive radio ad hoc networks
Cognitive radio technology is an assuring solution for under-utilization of licensed spectrum
bands and overcrowding of unlicensed spectrum bands, in which secondary user is …
bands and overcrowding of unlicensed spectrum bands, in which secondary user is …
A cross-layer routing protocol based on quasi-cooperative multi-agent learning for multi-hop cognitive radio networks
Y Du, C Chen, P Ma, L Xue - Sensors, 2019 - mdpi.com
Transmission latency minimization and energy efficiency improvement are two main
challenges in multi-hop Cognitive Radio Networks (CRN), where the knowledge of topology …
challenges in multi-hop Cognitive Radio Networks (CRN), where the knowledge of topology …
Recent Advances on artificial intelligence in cognitive radio networks
B Benmammar - International Journal of Wireless Networks and …, 2020 - igi-global.com
Cognitive radio is a form of wireless communication that makes decisions about allocating
and managing radio resources after detecting its environment and analyzing the parameters …
and managing radio resources after detecting its environment and analyzing the parameters …
Obstacle avoidance of hexapod robots using fuzzy Q-learning
Safe and autonomous obstacle avoidance plays an important role in the navigation control
of hexapod robots. In this paper, we combine the method of reinforcement learning with …
of hexapod robots. In this paper, we combine the method of reinforcement learning with …
An enhanced routing technique to improve the network lifetime of cognitive sensor network
V Jyothi, MV Subramanyam - Wireless Personal Communications, 2022 - Springer
In terms of using the technology of Cognitive Radio, a Cognitive Sensor Network (CSN) is
varied from the conventional Wireless Sensor Networks (WSNs). According to the interaction …
varied from the conventional Wireless Sensor Networks (WSNs). According to the interaction …
An energy-efficient cross-layer routing protocol for cognitive radio networks using apprenticeship deep reinforcement learning
Y Du, Y Xu, L Xue, L Wang, F Zhang - Energies, 2019 - mdpi.com
Deep reinforcement learning (DRL) has been successfully used for the joint routing and
resource management in large-scale cognitive radio networks. However, it needs lots of …
resource management in large-scale cognitive radio networks. However, it needs lots of …
Cooperative reinforcement learning based throughput optimization in energy harvesting wireless sensor networks
Y Wu, K Yang - 2018 27th Wireless and optical communication …, 2018 - ieeexplore.ieee.org
Energy Harvesting-Wireless Sensor Network (EH-WSN) has got increasing attention in
recent years. During its actual deployment, we find that the energy which can be harvested …
recent years. During its actual deployment, we find that the energy which can be harvested …
Spectrum-aware outage minimizing cooperative routing in cognitive radio sensor networks
This paper investigates the optimal path selection problem for end-to-end (e2e) outage
probability minimization in clustered cognitive radio sensor networks. In order to improve …
probability minimization in clustered cognitive radio sensor networks. In order to improve …