Myburgh, HCOlivier, JC2010-01-082010-01-082009-05Myburgh, HC and Olivier, JC. 2009. Low complexity iterative MLSE equalization of M-QAM signals in extremely long rayleigh fading channels. IEEE EUROCON 2009 Saint-Petersburg, Russia 18-23 May 2009, pp 1632-1637978-1-4244-3861-7http://hdl.handle.net/10204/3862Copyright: 2009 Institute of Electrical and Electronics Engineering (IEEE). Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.This work proposes a neural network based iterative Maximum Likelihood Sequence Estimation (MLSE) equalizer, able to equalize signals in M-arry Quadrature Amplitude Modulation (M-QAM) modulated systems in a mobile fading environment with extremely long channels. Its computational complexity is linear in the data block length and approximately independent of the channel memory length, whereas conventional equalization algorithms have computational complexity linear in the data block length but exponential in the channel memory length. Its performance is compared to the Viterbi MLSE equalizer for short channels and it is shown that the proposed equalizer has the ability to equalize M-QAM signals in systems with hundreds of memory elements, achieving matched filter bound performance with perfect channel state information (CSI) knowledge in uncoded systems. The proposed equalizer is evaluated in a frequency selective Rayleigh fading environment.enComputational complexityNeural networkM-arry quadrature amplitude modulationM-QAMMaximum likelihood sequence estimationMLSERayleigh fading channelsIEEE EUROCON 2009Conference PresentationMyburgh, H., & Olivier, J. (2009). Low complexity iterative MLSE equalization of M-QAM signals in extremely long rayleigh fading channels. Institute of Electrical and Electronics Engineering (IEEE). http://hdl.handle.net/10204/3862Myburgh, HC, and JC Olivier. "Low complexity iterative MLSE equalization of M-QAM signals in extremely long rayleigh fading channels." (2009): http://hdl.handle.net/10204/3862Myburgh H, Olivier J, Low complexity iterative MLSE equalization of M-QAM signals in extremely long rayleigh fading channels; Institute of Electrical and Electronics Engineering (IEEE); 2009. http://hdl.handle.net/10204/3862 .TY - Conference Presentation AU - Myburgh, HC AU - Olivier, JC AB - This work proposes a neural network based iterative Maximum Likelihood Sequence Estimation (MLSE) equalizer, able to equalize signals in M-arry Quadrature Amplitude Modulation (M-QAM) modulated systems in a mobile fading environment with extremely long channels. Its computational complexity is linear in the data block length and approximately independent of the channel memory length, whereas conventional equalization algorithms have computational complexity linear in the data block length but exponential in the channel memory length. Its performance is compared to the Viterbi MLSE equalizer for short channels and it is shown that the proposed equalizer has the ability to equalize M-QAM signals in systems with hundreds of memory elements, achieving matched filter bound performance with perfect channel state information (CSI) knowledge in uncoded systems. The proposed equalizer is evaluated in a frequency selective Rayleigh fading environment. DA - 2009-05 DB - ResearchSpace DP - CSIR KW - Computational complexity KW - Neural network KW - M-arry quadrature amplitude modulation KW - M-QAM KW - Maximum likelihood sequence estimation KW - MLSE KW - Rayleigh fading channels KW - IEEE EUROCON 2009 LK - https://researchspace.csir.co.za PY - 2009 SM - 978-1-4244-3861-7 T1 - Low complexity iterative MLSE equalization of M-QAM signals in extremely long rayleigh fading channels TI - Low complexity iterative MLSE equalization of M-QAM signals in extremely long rayleigh fading channels UR - http://hdl.handle.net/10204/3862 ER -