Effective capacity optimization for cognitive radio networks under primary QoS provisioning
Funding Number
NPRP 09-1168-2-455
Author's Department
Electronics & Communications Engineering Department
Find in your Library
https://ieeexplore.ieee.org/document/7707360
Document Type
Research Article
Publication Title
IEEE Transactions on Communications
Publication Date
12-31-2019
doi
10.1109/TCOMM.2016.2621744
Abstract
Cognitive radios have emerged as a key enabler for opportunistic spectrum access, in order to tackle the wireless spectrum scarcity and under utilization problems over the past two decades. In this paper, we aim to enhance the secondary user (SU) performance while maintaining the desired average packet delay for the primary user (PU). In particular, we investigate the trade-off between delay-constrained primary and secondary users in cog- nitive radio systems. In the first part of this work, we use the hard-sensing scheme to make a decision on the PU activity and maximize the SU effective capacity subject to an average PU delay constraint. Second, we propose a soft-sensing scheme by dividing the PU energy interval where the PU is decided to be idle into multiple decision. We also maximize the SU effective capacity subject to an average primary user delay constraint; then, we present three modifications for the proposed soft-sensing scheme to allow for low complexity implementation that is comparable to the complexity of the hard-sensing scheme, but with better performance. The numerical results reveal interesting insights comparing our soft sensing to the hard-sensing models in terms of the optimal performance obtained from our optimization solution compared to the unconstrained PU delay baseline system studied earlier in the literature. For instance, the hard sensing system in Akin and Gursoy (IEEE Trans Wirel Commun 9(11):3354–3364, 2010) and Abdel-Malek et al. (CrownCom 156:30–42, 2015) yields a SU effective capacity of only 50 % of the ideal, perfect sensing system. On the other hand, we show that the soft sensing system yields almost 87 % of the perfect sensing performance (at a primary user arrival rate of λp= 0.1), which further increases for a larger number of decision sub-intervals.
First Page
1451
Last Page
1463
Recommended Citation
APA Citation
Seddik, K. G.
(2019). Effective capacity optimization for cognitive radio networks under primary QoS provisioning. IEEE Transactions on Communications, 65(4), 1451–1463.
10.1109/TCOMM.2016.2621744
https://fount.aucegypt.edu/faculty_journal_articles/185
MLA Citation
Seddik, Karim Gomaa
"Effective capacity optimization for cognitive radio networks under primary QoS provisioning." IEEE Transactions on Communications, vol. 65,no. 4, 2019, pp. 1451–1463.
https://fount.aucegypt.edu/faculty_journal_articles/185