Performance Analysis and Channel Estimation Based on K-Means based Correlation
Rishi Choubey1, V.B. Reddy2
1Rishi Choubey, Research Scholar, Department of Electronics and Communication, Swami Vivekanand University, Sagar (Madhya Pradesh), India.
2V.B. Reddy, Associate Professor, Department of Electrical and Electronics, Swami Vivekanand University, Sagar (Madhya Pradesh), India.
Manuscript received on 24 September 2018 | Revised Manuscript received on 30 September 2018 | Manuscript published on 30 November 2018 | PP: 34-39 | Volume-7 Issue-4, November 2018 | Retrieval Number: D1793097418©BEIESP
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© 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 this paper an efficient k-means based approach has been used for channel estimation and performance analysis. For experimentation 2×2, 3×3, 4×4, 5×5 systems (MIMO−OFDM) have been used. The parameter considered are subcarriers, spreading code length, timing jitters, channel variations and temperature correlation. The system is considered with the correlated timing jitters. First the subcarrier is considered according to the system with the variable spreading length along with the variable timing jitters. For finding the nearer subcarriers in the related frequency k-means algorithm have been applied. It is helpful in finding the related correlation. Additive white Gaussian noise (AWGN) and Rayleigh fading channel have been considered. The results clearly indicate that the improved performance has been obtained in case of increasing the systems or the subcarriers after the related similarity correlation through our approach. It is also found better in terms of different parametric variations.
Keywords: AWGN, Rayleigh Channel, Channel Estimation, K-Means
Scope of the Article: Music Modelling and Analysis