scholarly journals Reverberation suppression in cochlear implants using a blind channel-selection strategy

2013 ◽  
Vol 133 (6) ◽  
pp. 4188-4196 ◽  
Author(s):  
Oldooz Hazrati ◽  
Philipos C. Loizou
Keyword(s):  
Cochlear Implants ◽  
Channel Selection ◽  
Selection Strategy ◽  
Blind Channel

scholarly journals A Dynamic Channel Selection Strategy for Dense-Array ERP Classification

2009 ◽  
Vol 56 (4) ◽  
pp. 1040-1051 ◽  
Author(s):  
Srinivas Kota ◽  
Lalit Gupta ◽  
Dennis L. Molfese ◽  
Ravi Vaidyanathan
Keyword(s):  
Channel Selection ◽  
Selection Strategy ◽  
Dense Array ◽  
Dynamic Channel

scholarly journals Analysis and Implementation  of Reinforcement Learning  on a GNU Radio Cognitive  Radio Platform

2021 ◽  
Author(s):  
◽  
Yu Ren
Keyword(s):  
Cognitive Radio ◽  
Success Rate ◽  
Large Scale ◽  
Channel Selection ◽  
Packet Transmission ◽  
Selection Strategy ◽  
Gnu Radio ◽  
Selection Scheme ◽  
Q Learning ◽  
Transmission Success

<p>Spectrum today is regulated based on fixed licensees. In the past radio operators have been allocated a frequency band for exclusive use. This has become problem for new users and the modern explosion in wireless services that, having arrived late find there is a scarcity in the remaining available spectrum. Cognitive radio (CR) presents a solution. CRs combine intelligence, spectrum sensing and software reconfigurable radio capabilities. This allows them to opportunistically transmit among several licensed bands for seamless communications, switching to another channel when a licensee is sensed in the original band without causing interference. Enabling this is an intelligent dynamic channel selection strategy capable of finding the best quality channel to transmit on that suffers from the least licensee interruption. This thesis evaluates a Q-learning channel selection scheme using an experimental approach. A cognitive radio deploying the scheme is implemented on GNU Radio and its performance is measured among channels with different utilizations in terms of its packet transmission success rate, goodput and interference caused. We derive similar analytical expressions in the general case of large-scale networks. Our results show that using the Q-learning scheme for channel selection significantly improves the goodput and packet transmission success rate of the system.</p>

A delay-aware spectrum handoff scheme for prioritized time-critical industrial applications with channel selection strategy

2019 ◽  
Vol 144 ◽  
pp. 112-123
Author(s):  
Stephen S. Oyewobi ◽  
Gerhard P. Hancke ◽  
Adnan M. Abu-Mahfouz ◽  
Adeiza J. Onumanyi
Keyword(s):  
Channel Selection ◽  
Industrial Applications ◽  
Selection Strategy ◽  
Spectrum Handoff ◽  
Time Critical

Deep learning approach on channel selection strategy for minimizing co-channel interference in unlicensed channels

2020 ◽  
Vol 105 ◽  
pp. 113558
Author(s):  
Lei Yen ◽  
Abebe Belay Adege ◽  
Hsin-Piao Lin ◽  
Ching-Huai Ho ◽  
Ken Lever
Keyword(s):  
Deep Learning ◽  
Channel Selection ◽  
Selection Strategy ◽  
Learning Approach ◽  
Channel Interference

An Optimal Channel Selection Strategy via Cognitive Radio Nodes

2012 ◽  
Vol 10 (8) ◽  
pp. 1682-1689
Author(s):  
R. Kaniezhil ◽  
C. Chandrasekar
Keyword(s):  
Cognitive Radio ◽  
Channel Selection ◽  
Selection Strategy
Sign in / Sign up

Export Citation Format

Share Document