Low Complexity MIMO Channel Estimation with Enhanced Tracking Performance using M - BEACON Algorithm

In this paper, a modified Bounding Ellipsoidal Adaptive CONstrained least-squares (M-BEACON) algorithm is introduced that provides fast convergence performance by using short training sequences in stationary and quasi stationary environments. The fast convergence performance of the modified algorithm depends on the selection of forgetting factor and scaling parameter depends upon the Doppler rate and the set membership constraint, respectively. Simulation results show that M-BEACON algorithm provides fast convergence than the conventional BEACON and RLS algorithms. Moreover, the update rate of the modified algorithm is much lesser than that of BEACON algorithm which makes the critical impact on the computational cost.