A low-cost adaptive algorithm for blind equalization without channel order estimation

In this work, we present an improved version of adaptive implementation of our algorithm developed in [12], that equalizes a noisy single input multiple output finite impulse response (SIMO-FIR) systems, relying only on second order statistics, totally independent from the channel order. In the proposed version, we reduce the computational complexity from O(n ³) to O(np), where n is the data vector length and p is the sensor number. This is due, essentially, to the use of : (i) projection approximation, (ii) fast minor subspace trackers, (iii) shift invariance property of the data correlation matrix, and (iv) stochastic gradient technique. In addition, we propose a comparative study of performance of some typical fast minor subspace estimating and tracking algorithms. Simulation results are provided to illustrate the effectiveness of the low-cost adaptive implementation of the proposed algorithm.