Priority-based reserved spectrum allocation by multi-agent through reinforcement learning in cognitive radio network
نویسندگان
چکیده
منابع مشابه
Spectrum management of cognitive radio using multi-agent reinforcement learning
Wireless cognitive radio (CR) is a newly emerging paradigm that attempts to opportunistically transmit in licensed frequencies, without affecting the pre-assigned users of these bands. To enable this functionality, such a radio must predict its operational parameters, such as transmit power and spectrum. These tasks, collectively called spectrum management, is difficult to achieve in a dynamic ...
متن کاملTlbo Based Spectrum Allocation in Cognitive Radio Network
91 TLBO BASED SPECTRUM ALLOCATION IN COGNITIVE RADIO NETWORK Baldev Swamy*, Srinivas Bachu** & CH. Lavanya*** * M-Tech, VLSI & Embedded System, DRK Institute of Science and Technology, Hyderabad, Telangana, India ** Assistant Professor, Department of ECE, Guru Nanak Institutions Technical Campus Hyderabad, Telangana, India *** Assistant Professor, Department of ECE, DRK Institute of Science and...
متن کاملReinforcement Learning-based Spectrum Sharing for Cognitive Radio
TAO JIANG, Ph.D. THESIS, COMMUNICATIONS RESEARCH GROUP, UNIVERSITY OF YORK 2011 Abstract This thesis investigates how distributed reinforcement learning-based resource assignment algorithms can be used to improve the performance of a cognitive radio system. Decision making in most wireless systems today, including most cognitive radio systems in development, depends purely on instantaneous meas...
متن کاملSpectrum Trading in Cognitive Radio Network: An Agent-based Model
In this paper, we propose an agent-based spectrum trading mechanism, where secondary users (SUs) can access the spectrum through the Secondary Network Operator (SNO). Buying spectrum from primary users(PUs) and reselling them to secondary users(SU), SNO plays an agent-like role in the spectrum trading process. The most significant challenge for SNO is how to make most profitable strategy. We ad...
متن کاملMulti-Objective Reinforcement Learning for Cognitive Radio–Based Satellite Communications
Previous research on cognitive radios has addressed the performance of various machinelearning and optimization techniques for decision making of terrestrial link properties. In this paper, we present our recent investigations with respect to reinforcement learning that potentially can be employed by future cognitive radios installed onboard satellite communications systems specifically tasked ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Automatika
سال: 2019
ISSN: 0005-1144,1848-3380
DOI: 10.1080/00051144.2019.1674512