Spectral decision analysis and evaluation in an experimental environment for cognitive wireless networks

Abstract

Dynamic spectrum allocation is the crucial aspect in Cognitive Radio Networks (CRN) to improve spectral efficiency where the selection of the target frequency channel plays a relevant role in the communication performance of the secondary user. Therefore, the current research work aims to analyze and comparatively evaluate three multi-criteria techniques in spectrum decision within an experimental environment. In order to achieve the above, it is incorporated actual information from licensed users through realistic spectral occupancy data measured in the GSM bands, the performance of the proposed methodology is validated through three multi-criteria decision-making techniques: Multiplicative Exponential Weighting (MEW), Simple Additive Weighting (SAW), and Multi-Criteria Optimization and Compromise Solution (VIKOR). The results obtained show the outstanding performance of the multicriteria algorithms in decision making and their application in cognitive radio networks, highlighting the high performance of the SAW algorithm in contrast to MEW and VIKOR. The contribution of this work is the use of actual spectral occupancy information captured through a spectral measurement campaign in Bogota, the use of three evaluation metrics in terms of handoff rate, bandwidth, and throughput, as well as a detailed analysis of the results obtained.

Keywords

• Characterization licensed users
• Cognitive radio network
• Decision making
• Quality of service
• Spectral handoff
• Spectral mobility