Interval type-2 fuzzy Kalman filter aided individual channel estimation in MIMO relay systems

摘要

For a multiple input multiple output relay system, the overall system performance is dependent on the effectiveness of the channel estimation technique adopted. In real time, communicating nodes have Doppler offset influences associated with them owing to high mobility that largely affects the characteristics of underlying channels. Thus, for the complete characterisation of the channel under fast time varying fading conditions, the estimation of the Doppler offset influences along with the channel coefficients becomes inevitable. However, the combined estimation of the channel and the Doppler influences renders the overall estimation problem nonlinear. In literature, majority of the channel estimation methods assume that the Doppler offset influences are already known to the receiver node or nodes are assumed to be stationary. In this paper, a novel hybrid interval type-2 fuzzy aided Kalman filter method is proposed for the nonlinear channel estimation problem in one-way two-hop multiple input multiple output relay system. This channel estimation issue is represented as a nonlinear state space model, and the proposed hybrid method that combines the merits offered by the interval type-2 fuzzy interpolation and the Kalman filter approach is applied to address the issue. For type reduction, Nie-Tan method is adopted which is a low computational load extension of the widely used Karnik-Mendel approach. Furthermore, a computational complexity analysis has been performed. The proposed hybrid interval type-2 fuzzy based Kalman filter approach shows good performance-complexity trade off under fast time varying channel conditions for one-way two-hop multiple input multiple output relay system.