We found a match
Your institution may have rights to this item. Sign in to continue.
- Title
State Space Model Based Channel Estimation using Extended Kalman Filter for Superposition Coded Modulation OFDM System.
- Authors
Rashmi N.; Sarvagya, Mrinal
- Abstract
In this work Extended Kalman Filter(EKF)is implemented for Orthogonal Frequency Division Multiplexing- Superposition Coded Modulation(SCM) scheme. Due to time varying nature of Rayleigh fast fading channel which vitiates the performance of data detection which in turn degrades the performance of OFDM system. An efficient channel estimation technique is necessary. An Extended Kalman filtering algorithm is proposed which is low in computational complexity. The Jakes process is modeled as Autoregressive model and approximated to Rayleigh fading channel. This estimator algorithm is bandwidth efficient and requires less computation contrast to data-based only estimators. The results obtained prove that the proposed algorithm can be used to obtain the channel estimation with low computational. complexity at the receiver.
- Subjects
MODULATION coding; KALMAN filtering; RAYLEIGH model; AUTOREGRESSIVE models; CHANNEL estimation
- Publication
BVICAM's International Journal of Information Technology, 2016, Vol 8, Issue 2, p1017
- ISSN
0973-5658
- Publication type
Article