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Applications of Hybrid Intelligent Systems in Adaptive Communication

Applications of Hybrid Intelligent Systems in Adaptive Communication

Atta ur Rahman
Copyright: © 2018 |Pages: 35
ISBN13: 9781522528579|ISBN10: 1522528571|EISBN13: 9781522528586
DOI: 10.4018/978-1-5225-2857-9.ch010
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MLA

Rahman, Atta ur. "Applications of Hybrid Intelligent Systems in Adaptive Communication." Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms, edited by Sujata Dash, et al., IGI Global, 2018, pp. 183-217. https://doi.org/10.4018/978-1-5225-2857-9.ch010

APA

Rahman, A. U. (2018). Applications of Hybrid Intelligent Systems in Adaptive Communication. In S. Dash, B. Tripathy, & A. Rahman (Eds.), Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms (pp. 183-217). IGI Global. https://doi.org/10.4018/978-1-5225-2857-9.ch010

Chicago

Rahman, Atta ur. "Applications of Hybrid Intelligent Systems in Adaptive Communication." In Handbook of Research on Modeling, Analysis, and Application of Nature-Inspired Metaheuristic Algorithms, edited by Sujata Dash, B.K. Tripathy, and Atta ur Rahman, 183-217. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-2857-9.ch010

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Abstract

Dynamic allocation of the resources for optimum utilization and throughput maximization is one of the most important fields of research nowadays. In this process the available resources are allocated in such a way that they are maximally utilized to enhance the overall system throughput. In this chapter a similar problem is approached which is found in Orthogonal Frequency Division Multiplexing (OFDM) environment, in which the transmission parameters namely the code rate, modulation scheme and power are adapted in such a way that overall system's data rate is maximized with a constrained bit error rate and transmit power. A Fuzzy Rule Base System (FRBS) is proposed for adapting the code rate and modulation scheme while Genetic Algorithm (GA) and Differential Evolution (DE) algorithm are used for adaptive power allocation. The proposed scheme is compared with other schemes in the literature including the famous Water-filling technique which is considered as a benchmark in the adaptive loading paradigm. Supremacy of the proposed technique is shown through computer simulations.

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