Abstract
Green spectrum sharing techniques share the spectrum with minimum interference to the primary user with reduced transmit power at secondary. Usually, the green spectrum sharing is achieved by operating the cognitive radio in underlay mode by power control mechanism or MIMO cognitive radio based antenna selection mechanism. But the above approaches will not guarantee the Quality of Service (QoS) requirement of the secondary user. Interference Minimization and meeting the QoS requirement of secondary user is modeled as a multi objectives optimization problem and solved using genetic algorithm (GA) in this paper. MIMO cognitive radio system with the GA based power control, antenna selection, and link adaptation is proposed to share the spectrum with minimum interference to primary receiver and QoS assurance of the secondary user. QoS parameter considered under the works are the secondary user bit error rate, band efficiency, and data rate. The GA optimizes the parameters of antenna selection matrix, transmitter power, modulation type, modulation order, the roll-off factor of pulse shaping filter and symbol rate to achieve target QOS. The earlier convergence of the GA is another issue addressed in this work. The earlier convergence of GA results in a local optimum value of parameters, therefore, this work used the hybrid transform for the fitness of individual chromosome. The proposed work is carried out in real time using software defined radio (SDR) platform 6 GHz Vector Signal Generator 5673 configured as a secondary transmitter, Vector Signal Analyzer 5663 as the secondary receiver and two 2 × 2 MIMO USRP RIO SDR 2943R as a primary transmitter and receiver.

















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Acknowledgments
It is to acknowledge that this work is carried out by utilizing the resources funded under the DST-FIST scheme for Electronics and Communication Engineering department of SRM University, Kattankulathur, and Chennai, India.
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Vijayakumar, P., Malarvihi, S. Green Spectrum Sharing: Genetic Algorithm Based SDR Implementation. Wireless Pers Commun 94, 2303–2324 (2017). https://doi.org/10.1007/s11277-016-3427-1
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DOI: https://doi.org/10.1007/s11277-016-3427-1