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Tracking Performance of Robust RLS Algorithm for MIMO Channel Estimation


A robust recursive least square (RRLS) algorithm that has been designed for SISO communications by Bhotto and Antoniou (IEEE Signal Process Lett 18(3):185–188, 2011) is unable to work for MIMO system because of single error constraint. In this paper, a modified version of RRLS algorithm with the application of MIMO channel estimation is introduced. An RRLS algorithm is modified in such a way that it can provide much faster convergence rate in MIMO channel estimation than that of RLS and variable forgetting factor RLS (VFF-RLS) algorithms. Moreover, the optimum forgetting factor is derived for MIMO RRLS in order to minimize the error function. Simulation results show that the MIMO RRLS provides fast convergence performance as compared to RLS and VFF-RLS algorithms without additional multiplication complexity, however, an additional linear term of N in the addition complexity of modified MIMO RRLS does not enhance its computational complexity and keeps it almost equivalent to those of RLS and VFF-RLS algorithms. Moreover, it is observed that the optimum forgetting factor is highly dependent on RRLS scaling parameter, \(E_b/N_o\), doppler shift and number of antennas.

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Correspondence to Hasan Raza.

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Raza, H., Khan, N.M. Tracking Performance of Robust RLS Algorithm for MIMO Channel Estimation. Wireless Pers Commun 111, 395–409 (2020).

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  • MIMO channel estimation
  • Robustness
  • Forgetting factor optimization