Cross-Layer Based Asymmetric Resource Allocation in Relay-Aided Cognitive Radio Networks

Cross-Layer Based Asymmetric Resource Allocation in Relay-Aided Cognitive Radio Networks Cross-layer based asymmetric resource allocation in relay-aided cognitive radio networks (CRN) is proposed in this paper. Existing cross-layer schemes on relay-aided CRN are based on symmetric resource allocation (RA) where the transmission duration is assumed to be symmetric between secondary base station (BS) to relay station (RS) and RS to mobile station (MS) links. This may not be realistic and hence our proposed model considers asymmetric resource allocation (ARA) in which the transmission durations are asymmetric. Very little work has been done in ARA for relay-aided networks and most of them considered only power allocation. The queue stability and quality of service (QOS) requirements are other considerations that have a significant impact on RA and hence are considered in this work. The QOS requirements can be brought in terms of the maximum delay threshold and the minimum throughput requirements. The interference threshold is evaluated from the QOS of the primary radio network. Based on the queue state information, channel state information and QOS, resources are allocated to the secondary radio network. Our proposed ARA differs from existing ARA schemes in terms of additionally considering the subcarrier pairing for resource allocation. This work evolves an optimal cross-layer based ARA considering the above mentioned factors into account. The proposed ARA includes subcarrier allocation, subcarrier pairing and power allocation. Simulation results show that the proposed ARA scheme increases the system throughput and serves the edge users satisfactorily. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Wireless Personal Communications Springer Journals

Cross-Layer Based Asymmetric Resource Allocation in Relay-Aided Cognitive Radio Networks

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Publisher
Springer US
Copyright
Copyright © 2017 by Springer Science+Business Media, LLC
Subject
Engineering; Communications Engineering, Networks; Signal,Image and Speech Processing; Computer Communication Networks
ISSN
0929-6212
eISSN
1572-834X
D.O.I.
10.1007/s11277-017-4794-y
Publisher site
See Article on Publisher Site

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