%0 Journal Article %1 m2018efficient %A M, VijayaLakshmi %A and K Rama Linga Reddy, %D 2018 %E Meghanathan, Natarajan %J International Journal of Computer Networks & Communications (IJCNC) %K computing, networking, networks, security, %N 3 %P 45-53 %R 10.5121/ijcnc.2018.10304 %T Efficient PAPR Reduction Approach for Selective Mapping in a STBC MIMO-OFDM System %U http://airccse.org/journal/ijc2018.html %V 10 %X The demand for wireless communication increases every day. MIMO system increases the channel capacity without increasing the bandwidth. OFDM eliminates inter-symbol interference very effectively. By combining both these technologies ,the resultant data rates are increased and also robustness to multi path fading effects. But the main drawback of MIMO-OFDM system is its high PAPR. Selective mapping(SLM) is one of the popular distortion less technique for reducing high PAPR but the computational complexity for searching optimum phase factors is high. Many evolutionary algorithms like particle swarm optimisation, artificial bee colony optimization algorithm, cuckoo search algorithm are proposed for searching optimum phase factors. In this paper two new optimization algorithms social spider optimization(SSO), adaptive artificial bee colony algorithm are proposed for SLM and Simulation results shows that compared to adaptive artifctial bee colony algorithm, social spider optimization algorithm(SSO) gives best phase factors for lower PAPR with fewer number of iterations and also reduces the computational complexity of SLM technique very efficiently.

@article{m2018efficient, abstract = {The demand for wireless communication increases every day. MIMO system increases the channel capacity without increasing the bandwidth. OFDM eliminates inter-symbol interference very effectively. By combining both these technologies ,the resultant data rates are increased and also robustness to multi path fading effects. But the main drawback of MIMO-OFDM system is its high PAPR. Selective mapping(SLM) is one of the popular distortion less technique for reducing high PAPR but the computational complexity for searching optimum phase factors is high. Many evolutionary algorithms like particle swarm optimisation, artificial bee colony optimization algorithm, cuckoo search algorithm are proposed for searching optimum phase factors. In this paper two new optimization algorithms social spider optimization(SSO), adaptive artificial bee colony algorithm are proposed for SLM and Simulation results shows that compared to adaptive artifctial bee colony algorithm, social spider optimization algorithm(SSO) gives best phase factors for lower PAPR with fewer number of iterations and also reduces the computational complexity of SLM technique very efficiently.}, added-at = {2018-07-10T06:36:20.000+0200}, author = {M, VijayaLakshmi and and K Rama Linga Reddy}, biburl = {https://www.bibsonomy.org/bibtex/28f6bce35d2c7f11ac397e37ccc572771/laimbee}, doi = {10.5121/ijcnc.2018.10304}, editor = {Meghanathan, Natarajan}, interhash = {be7c6fdc971839a58265a16fd7af8233}, intrahash = {8f6bce35d2c7f11ac397e37ccc572771}, issn = {09749322}, journal = {International Journal of Computer Networks & Communications (IJCNC) }, keywords = {computing, networking, networks, security,}, language = {English}, month = may, number = 3, pages = {45-53}, timestamp = {2018-07-10T06:36:20.000+0200}, title = {Efficient PAPR Reduction Approach for Selective Mapping in a STBC MIMO-OFDM System}, url = {http://airccse.org/journal/ijc2018.html}, volume = 10, year = 2018 }