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A Test-Bed Evaluation of Cognitive Hybrid Functionality for Future Hyper-Dense Networks

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This paper proposes a cognitive hybrid function mechanism to intelligently select reliable network and efficiently adjust transmission power while maintaining good quality of service. This combination defines our proposed hybrid functionality. It can be applied to an access point that has multiple choices of network and transmission power modification. By employing such mechanism in closed-proximity network, we observe performances in terms of optimized speed and throughput of the user device. Results were obtained from several empirical laboratory studies by incorporating this mechanism into a hardware in contrast to many studies that just adhered to computer simulations. It was found that selecting reliable network had shown a better optimized speed performance up to 37% improvement as compared without such function. In terms of power adjustment, our evaluation of this mechanism can maintain the same level of throughput at reduced power of about 5 dB than the previous higher transmit power.
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Keywords: 5G; Cognitive Hybrid Functionality; Cognitive Radio; Hyper Dense Nets

Document Type: Research Article

Affiliations: 1: College of Information Technology, Universiti Tenaga Nasional, 47000 Kajang, Malaysia 2: Department of Comm. Engineering, International Islamic University, 50728 Gombak, Malaysia 3: Wireless Communication, MIMOS Berhad, 57000 Kuala Lumpur, Malaysia

Publication date: October 1, 2016

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  • ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
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