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Non-Overlapping Allocation MAC for Collision Avoidance in Distributed Cognitive Radio Networks
  • Nguyen, Tuan Manh
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Affiliation
아주대학교 일반대학원
Department
일반대학원 컴퓨터공학과
Publication Year
2012-08
Publisher
The Graduate School, Ajou University
Keyword
Cognitive RadioMAC
Description
학위논문(석사)아주대학교 일반대학원 :컴퓨터공학과,2012. 8
Alternative Abstract
Recently, the rapid growth of wireless services has made the demand for wireless spectrum more enormous than ever. A study by Federal Communication Commission (FCC) shows that spectrum was not efficiently used due to the fixed spectrum assignment policy. Cognitive Radio is a new technology that is proposed to tackle such problem. Cognitive Radio (CR) enables secondary users (SUs) to temporarily use the spectrum whenever it is unused by primary users (PUs). By dynamically assigned the use of spectrum between PUs and SUs, the spectrum is much more efficiently used. In this thesis, a Non-Overlapping Allocation MAC protocol (NOA-MAC) has been proposed to facilitate the coexisting of SUs and PUs in decentralized CR networks. In NOA-MAC, PU activity is modeled as two-state Continuous Time Markov Chain, which allows SUs to perform spectrum sensing to detect spectrum opportunities in which they can opportunistically transmit data. Then, spectrum opportunities are share among SUs by a non-overlapping slots allocation scheme, which coordinates SUs to exchange spectrum information on a common control channel and schedule their transmissions independent of each other. Since spectrum access in NOA-MAC is done in a slotted structure and slots allocation scheme assigns non-overlapping slots to SUs competing for the same spectrum band, collision is avoided. As a result, throughput can be improved, which is the main objective of NOA-MAC. Simulation is done in OPNET Modeler with various scenarios from multi-user access scenario with normal to high collision condition to evaluate performance of NOA-MAC in both throughput and end-to-end delay.
Language
eng
URI
https://dspace.ajou.ac.kr/handle/2018.oak/8429
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Type
Thesis
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