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Pilot based Channel Estimation and SCGNN based Equalization for MIMO-OFDM System

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2015
Zeeshan A. Abbasi, Zainul Abdin Jaffery

Zeeshan A Abbasi and Zainul Abdin Jaffery. Article: Pilot based Channel Estimation and SCGNN based Equalization for MIMO-OFDM System. International Journal of Computer Applications 131(3):11-15, December 2015. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

	author = {Zeeshan A. Abbasi and Zainul Abdin Jaffery},
	title = {Article: Pilot based Channel Estimation and SCGNN based Equalization for MIMO-OFDM System},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {131},
	number = {3},
	pages = {11-15},
	month = {December},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}


In this paper a new channel equalization technique is described based on Scaled Conjugate Gradient Neural Network (SCGNN) for Multiple Input Multiple Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM). To estimate the channel in frequency domain, Space Time Block Code (STBC) is used. At the beginning of each transmitted OFDM block the pilot sequence is inserted to estimate the channel. In the transmitter the 16-QAM modulation is used as it is efficient in conserving bandwidth. The performance is evaluated using MATLAB and various results are plotted at different values of SNR. It is observed from the simulation that the proposed channel estimation and equalization method greatly reduced the Symbol Error Rate. We are able to achieve the SER as low as 0.01at a very low value of SNR. The MMSE is also greatly reduced and the system converges very fast.


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Scaled Conjugate Gradient Network, MIMO, OFDM, Equalization