Weighted neuro-fuzzy hybrid algorithm for channel equalisation in time varying channel. (6th April 2020)

• Record Type: Journal Article
• Authors: Abbasi, Zeeshan Ahmad; Jaffery, Zainul Abdin
• Is Part Of: International journal of business intelligence and data mining. Volume 17:Number 2(2020)
• Page Start: 237
• Page End: 257
• Publication Date: 2020-04-06
• Subjects: MIMO-OFDM -- group search optimiser -- GSO -- scaled conjugate gradient -- SCG -- channel estimation; 006.312
• Languages: English
• ISSNs: 1743-8187

Abstract

In MIMO-OFDM communication systems, accurate and specific channel estimation and equalisations are plays a major role. In this paper, we use weighted neuro-fuzzy hybrid (WNFH) channel estimation algorithm for channel equalisation. The pilot is designed based on combination of neural network and fuzzy logic system. Scaled conjugate gradient (SCG) is mutual with group search optimiser (GSO) algorithm along with; the training procedure of neural network is prepared using the hybrid training algorithm. In the transmitter section, the projected system contains quadrature amplitude modulation (QAM) and transmitter. By considering the channel prediction error to recover the performance of symbol detection the minimum mean-square error (MMSE) estimation design is accomplished. To reduce the MMSE of channel estimation and the calculated pilot sequences present great superiority in MIMO-OFDM system. Experimentation outcome shows that the channel assessment is supportive.