OFDM Receiver Design using Adaptive Modulation and Channel Estimation based on Kalman filter Variations for Underwater Acoustic Communication
Ravi Kumar M G1, Mrinal Sarvagya2
1Ravi Kumar M G, Research Scholar, REVA University, (Karnataka), India.
2Dr. Mrinal Sarvagya, Professor, REVA University, (Karnataka), India.
Manuscript received on 22 April 2019 | Revised Manuscript received on 01 May 2019 | Manuscript Published on 05 May 2019 | PP: 230-236 | Volume-8 Issue-2S2, May 2019 | Retrieval Number: B10490182S219/19©BEIESP
Open Access | Editorial and Publishing 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: This paper deals with enhancement of data rate in OFDM system using Adaptive modulation and Channel estimation for Underwater Acoustic Communication (UAC). The accurate knowledge of the channel aids equalization and symbol detection. Since the Kalman filter is an optimal estimator in nature, which is proposed to address the problem of channel tracking in fading environment. The random data is modulated using DPSK, QPSK and 16-QAM and transmitted over the channel. Pilot bits and cyclic prefix are used for channel estimation and to protect from the Inter symbol interference (ISI) respectively. The channels under consideration in this work are AWGN and Rayleigh. The Kalman filter operates over the data bits to estimate the channel parameters. At the receiver end demodulation and symbol detection is performed and the same model is implemented in MATLAB. The simulation results for OFDM system are compared based on the BER and MMSE for the two mentioned channels. The simulation results shows that Adaptive modulation yields better result compared to individual modulation schemes and the simulation results also prove that the Kalman filter is an excellent estimator and predictor which finds its application in channel estimation in OFDM systems.
Keywords: OFDM, Underwater Acoustic Communication, Adaptive Modulation, Kalman Filter, Channel Estimation.
Scope of the Article: Communication Architectures for Pervasive Computing