Dual bound Kalman Filter for Signal Estimation in Multipath Fading for MIMO-OFDM Communication System
G Rajender1, T Anil Kumar2, K Srinivasa Rao3
1G Rajender, Department of ECE, JNTUH/CMRIT/, Hyderabad, India.
2Dr T Anil Kumar, Department of ECE Department, JNTUH/CMRIT, Hyderabad, India.
3Dr K Srinivasa Rao, Department of ECE, JNTUH/Ellenki College of Engineering and Technology, Hyderabad, India.
Manuscript received on 05 May 2019 | Revised Manuscript received on 12 May 2019 | Manuscript published on 30 May 2019 | PP: 690-696 | Volume-8 Issue-7, May 2019 | Retrieval Number: G5570058719/19©BEIESP
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Abstract: In this paper, Signal estimation in MIMO-OFDM communication using enhanced kalman filtration is proposed. Received Signal is passed through estimator unit, where the interference level is estimated and applied over the signal to compensate the error to minimal. Recursive estimators are used for estimation, in the kalman filter model, least mean square (LMS) estimator is used for the error estimation and minimization. In recursive estimation convergence delay is primal factor of estimate and defines the speed of estimation. In the existing process of estimation, errors are propagated in a backward direction to update the weight factor for forward error minimization. However, the error updation in the dynamic channel model is non linear and a backward feed loop in different cases leads to instability and doesn’t converge. This problem is solved by introducing dual bound estimation logic, where a forward weight adaptation in parallel with backward weight is monitored to derive a updating weight factor. The error performance, delay and MSIE parameter is validated for different SNR sand step sizes.
Keyword: Dual bound Coding, Kalman filter, IMO-OFDM Communication system.
Scope of the Article: MIMO Antenna