UKF Based Iterative Joint Channel Estimation for Uplink Two Dimensional Block Spread Wireless Networks

Abstract

Applications for future broadband wireless network should work effectively under highly dynamic wireless channel environment, where strong frequency-selective and time-selective fading and severe multi-path channels will exist. Though some advantage techniques, such as 2-dimensional (2D) block spread, frequency domain equalization (FDE) and antenna diversity techniques, can be applied to the code division multiple access (CDMA) networks to improve the bit error rate (BER) performance, they all require an accurate estimation of the channel. Conventional channel estimation method such as the minimum mean square errors (MMSE) based channel estimation scheme may not be applicable because its performance degrades significantly when the channel dynamics become severe. Therefore, in this paper, we propose an unscented Kalman filter (UKF) based iterative channel estimation method, which is jointly used with the MMSE channel estimation scheme, to track the channel dynamics in both time domain and frequency domain. Hence, better estimation accuracy of the fast fading channels can be achieved. Furthermore, we utilize cyclic iteration to ensure UKF converge to the stable result accurately and quickly, and the iteration count can be adjusted according to the Doppler effects. Our performance analysis demonstrates that the proposed joint estimation method can achieve good BER performance under both low and high dynamic channel conditions. It is much better than the pure MMSE based channel estimation method, and is very close to results from an ideal channel estimator.