Optimization Scheme with Energy Detector Model for Cognitive Radio Networks
Dinokumar Kongkham1, M Sundararajan2
1Dinokumar Kongkham, Research Scholar, Department of ECE, Bharath Institute of Higher Education and Research, Chennai (Tamil Nadu), India.
2M.Sundararajan, Professor, Department of ECE, Bharath Institute of Higher Education and Research, Chennai (Tamil Nadu), India.
Manuscript received on 05 February 2019 | Revised Manuscript received on 13 February 2019 | Manuscript published on 28 February 2019 | PP: 376-381 | Volume-8 Issue-4, February 2019 | Retrieval Number: D2829028419/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Cognitive Radio (CR) is a promising technology in the wireless communication system for resolving the resource utilization problems and spectral clogging problems in the spectrum based applications. It aims to enhance spectrum sharing scheme in Multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) to enable with next generation systems. Efficient utilization of Spectrum sensing and computational complexity is still an unsolved issue in the ultra-wide band (UWB) radio spectrum. Generally, conventional methods include spectrum sensing to identify the primary users and spectrum usage, which helps to make data transmission possible from secondary users. However, they obtain poor throughput, higher transmission power and longer sensing time. In order to resolve this issue, we propose novel hybrid access optimization scheme with energy detector model for achieving the significant compressive spectrum sensing in the MIMO-OFDM, which is based on cognitive ratio network (CRN). The proposed method develops sparsity signal model with the help of orthogonal transform of Fractional Fourier Transformation (FRFT) for reducing the signal to noise ratio (SNR). Furthermore, modulated signals from secondary users are forwarded to DSP (Digital signal Processing). Hence, the proposed system achieves higher accuracy in detecting the false probability, energy detection, optimal sensing time, and higher throughput than efficient compressive sensing method.
Keyword: Spectrum Sensing, Novel Hybrid Access Optimization Scheme, Energy Detector, Sparsity Signal Model and Fractional Fourier Transformation.
Scope of the Article: Cognitive Radio Networks