Enhanced cognitive Radio Resource Management for LTE systems

Ismail Alqerm, Basem Shihada, Kang G. Shin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations


The explosive growth in mobile Internet and related services has increased the need for more bandwidth in cellular networks. The Long-Term Evolution (LTE) technology is an attractive solution for operators and subscribers to meet such need since it provides high data rates and scalable bandwidth. Radio Resource Management (RRM) is essential for LTE to provide better communication quality and meet the application QoS requirements. Cognitive resource management is a promising solution for LTE RRM as it improves network efficiency by exploiting radio environment information, intelligent optimization algorithms to configure transmission parameters, and mitigate interference. In this paper, we propose a cognitive resource management scheme to adapt LTE network parameters to the environment conditions. The scheme optimizes resource blocks assignment, modulation selection and bandwidth selection to maximize throughput and minimize interference. The scheme uses constrained optimization for throughput maximization and interference control. It is also enhanced by learning mechanism to reduce the optimization complexity and improve the decision-making quality. Our evaluation results show that our scheme achieved significant improvements in throughput and LTE system capacity. Results also show the improvement in the user satisfaction over other techniques in LTE RRM.
Original languageEnglish (US)
Title of host publication2013 IEEE 9th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages6
ISBN (Print)9781479904280
StatePublished - Oct 2013

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01


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