Regularized adaptive algorithms based-time domain iterative channel estimation for MC-IDMA systems

The importance of near to optimum channel estimation scheme cannot be over-emphasized in wireless communication systems, especially in a Multicarrier-Interleave Division Multiple Access (MC-IDMA)-based wireless communication systems. Availability of accurate estimate of channel state information (CSI) at the receiver end of the system remains an essential factor for its optimum performance. In this paper, two families of regularized recursive least square algorithm, namely, Regularized Rounding square Error based variable forgetting factor-recursive least square (ℓ₁-REVFF-RLS)-based channel impulse response (CIR) Estimator and Regularized Mean square error Gradient-based variable forgetting factor-recursive least square (ℓ₁-MGVFF-RLS)-based CIR Estimator are developed and proposed for implementation of time domain iterative channel estimation for MC-IDMA systems. The performances of the proposed regularized adaptive algorithms based-time domain iterative channel estimators are validated in comparison with the least mean square (LMS)-based channel estimator and combined channel transfer function (CTF)-estimator and CIR predictor that were earlier proposed in literature for MC-IDMA systems.