Efficient Channel Estimation with Optimization Algorithm-Based Pilot Pattern Design for MIMO-OFDM Wireless Networks
Swetha Rani.L1, Suriya Tarnnum2

1Swetha Rani.L, Department of Electronics and Communication, AMC Engineering College, Bangalore (Karnataka), India.
2Suriya Tarnnum, Department of Electronics and Communication, HKBK College of Engineering, Bangalore (Karnataka), India.
Manuscript received on 21 May 2019 | Revised Manuscript received on 11 June 2019 | Manuscript Published on 27 June 2019 | PP: 117-129 | Volume-8 Issue-1C May 2019 | Retrieval Number: A10220581C19/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) frameworks, the channel state data ought to be known by the beneficiary for acquiring transmitted information. Channel estimation algorithms are utilized to look at the multipath effects of frequency selective Rayleigh blurring channels. It acquires the required channel data ahead of time with the aim of making the piloting code of the transmitter progressively proficient to influence the receiver to detect signals more effectively. In this way, the precision of channel estimation is the most critical in the concerns that determine the overall performance of a MIMO-OFDM system. In this paper, proficient channel estimation with optimization algorithm based pilot pattern design (ECE-OA) is proposed for MIMO-OFDM remote systems. It is utilized to reproduce the signal with improved spectral efficiency and requires transmitting the known pilot information to the receiver for estimating channel data. The ideal pilot patterns selected through reduce the negative effect of pilot pattern design. In ECE-OA, a chaotic social spider optimization (CSSO) algorithm is utilized to co-ordinate the assignment of pilot sequences across all cells to reduce the correlation between the pilots as observed at each base station. The multiple metrics are obtained from the uplink (UL) channel state information (CSI), during every UL period users in each cell transmit known pilot sequences to the base station in their own cells and the BS estimates uplink CSI. The proposed design used to maximize the accuracy of channel estimation and to reduce the computational complexity. The simulation results show that the performance of proposed ECE-OA design is perform better than existing state-of-art techniques in terms of bit error rate (BER) and Mean Square Error (MER).
Keywords: Optimization Algorithm Design Wireless Networks Information Data.
Scope of the Article: Low-power design