Adaptive multi-objective Optimization scheme for cognitive radio resource management

Ismail Alqerm, Basem Shihada

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

11 Scopus citations


Cognitive Radio is an intelligent Software Defined Radio that is capable to alter its transmission parameters according to predefined objectives and wireless environment conditions. Cognitive engine is the actuator that performs radio parameters configuration by exploiting optimization and machine learning techniques. In this paper, we propose an Adaptive Multi-objective Optimization Scheme (AMOS) for cognitive radio resource management to improve spectrum operation and network performance. The optimization relies on adapting radio transmission parameters to environment conditions using constrained optimization modeling called fitness functions in an iterative manner. These functions include minimizing power consumption, Bit Error Rate, delay and interference. On the other hand, maximizing throughput and spectral efficiency. Cross-layer optimization is exploited to access environmental parameters from all TCP/IP stack layers. AMOS uses adaptive Genetic Algorithm in terms of its parameters and objective weights as the vehicle of optimization. The proposed scheme has demonstrated quick response and efficiency in three different scenarios compared to other schemes. In addition, it shows its capability to optimize the performance of TCP/IP layers as whole not only the physical layer.
Original languageEnglish (US)
Title of host publication2014 IEEE Global Communications Conference
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages7
ISBN (Print)9781479935123
StatePublished - Dec 2014

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01


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