Equalization of DS-UWB Systems using Genetic Algorithm with Adaptive Parameters

We use adaptive generation along with some other parameters to investigate their effects on the performance of Genetic Algorithm (GA) in comparison to a previous work, where the output of a RAKE receiver is utilized as the input to a GA so as to reduce the inter-symbol interference (ISI) due to the frequency selectivity of UWB channels because of the very high rate of transmission. The effects of two different scaling methods and two mutation types, on the performance of a GA when used with a receiver for the equalization of the channel of a direct sequence ultra wideband (DS-UWB) wireless communications system are presented. The results show that fitness scaling has effects on GA based optimization while mutation prevents local convergence.

[1]  Asoke K. Nandi,et al.  Genetic Algorithm Based Equalization for Direct Sequence Ultra-Wideband Communications Systems , 2009, 2009 IEEE Wireless Communications and Networking Conference.

[2]  J. Foerster,et al.  Channel modeling sub-committee report final , 2002 .

[3]  Yao Jing,et al.  Multiuser Detection Employing a Novel Genetic Algorithm for UWB Communications , 2011 .

[4]  S. Roy,et al.  Design challenges for very high data rate UWB systems , 2002, Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers, 2002..

[5]  Liang Zhong,et al.  Differential multiuser detection using a novel genetic algorithm for ultra-wideband systems in lognormal fading channel , 2011, Journal of Zhejiang University SCIENCE C.

[6]  Colm O'Riordan,et al.  Analysing the effects of combining fitness scaling and inversion in genetic algorithms , 2004, 16th IEEE International Conference on Tools with Artificial Intelligence.

[7]  Trevor P Martin,et al.  Intelligent Data Engineering and Automated Learning , 2004 .

[8]  O. Fuentes,et al.  Generic algorithms: what fitness scaling is optimal? , 1993 .

[10]  Korany R. Mahmoud,et al.  DESIGN BLUETOOTH AND NOTCHED-UWB E-SHAPE ANTENNA USING OPTIMIZATION TECHNIQUES , 2013 .

[11]  Hiroyuki Sato,et al.  Computational Complexity and Performance of RAKE Receivers with Channel Estimation for DS-UWB , 2005, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

[12]  Farzad Sadjadi,et al.  Comparison of fitness scaling functions in genetic algorithms with applications to optical processing , 2004, SPIE Optics + Photonics.

[13]  Asoke K. Nandi,et al.  Effects of fitness scaling and adaptive parameters on genetic algorithm based equalization for DS-UWB systems , 2009, 2009 4th International Conference on Computers and Devices for Communication (CODEC).

[14]  Adrian A. Hopgood,et al.  Transform Ranking: a New Method of Fitness Scaling in Genetic Algorithms , 2008, SGAI Conf..

[15]  Zhiqiang Wu,et al.  Direct sequence spreading UWB systems: frequency domain processing for enhanced performance and throughput , 2003, IEEE International Conference on Communications, 2003. ICC '03..

[16]  H. Vincent Poor,et al.  A genetic algorithm based finger selection scheme for UWB MMSE rake receivers , 2005, 2005 IEEE International Conference on Ultra-Wideband.

[17]  Sam Kwong,et al.  Genetic Algorithms : Concepts and Designs , 1998 .

[18]  Shuyuan Yang,et al.  A GA-based UWB pulse waveform design method , 2008, Digit. Signal Process..