New Channel Estimation Method Using Singular Spectrum Analysis for OFDM Systems

• Published in: Wireless personal communications Vol. 101; no. 4; pp. 2193 - 2207
• Main Authors: Hari Krishna, E., Sivani, K., Ashoka Reddy, K.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.08.2018; Springer Nature B.V
• Subjects: Bit error rate; Communications Engineering; Computer Communication Networks; Computer simulation; Correlation analysis; Correlation coefficients; Empirical analysis; Engineering; Networks; Noise reduction; Orthogonal functions; Signal,Image and Speech Processing; Spectrum analysis; Singular spectrum analysis; Multi carrier communications; OFDM; Channel estimation; BER; MSE; Singular value decomposition
• ISSN: 0929-6212; 1572-834X
• DOI: 10.1007/s11277-018-5811-5

This paper presents a new method for OFDM channel estimation (CE) using singular spectrum analysis (SSA). In this method, the conventional LMMSE procedure is used for CE and then SSA based optimum low rank approximation is performed on channel correlation matrix. Detailed simulations for bit error rate and mean square error have shown good performance for this algorithm compared to the well-known LSE, MMSE, and SVD based CE methods. In the proposed method, the SSA is also employed for denoising the signal aimed at further improvement in the performance of CE. SSA decomposes the received OFDM symbol into empirical orthogonal functions (EOFs). A de-noised signal is reconstructed using selective EOFs based on Pearson correlation coefficients. The proposed method has outperformed LSE and MMSE based methods and shown an average 2 dB improvements over SVD based method.