The Simpli ed Wiener LMS Algorithm

A new type of tracking algorithm with time-invariant gain is presented. It can be applied for obtaining prediction, ltering or xed-lag smoothing estimates of time-varying parameters in linear regression models. The algorithm design constitutes a systematic way of introducing a priori information into LMS-like adaptation laws, using the concept of stochastic hypermodelling of the unknown time-varying parameters. The design equations, which provide the structure and adjustment of the tracking algorithms, are derived from a Wiener ltering perspective. The simplest variant of the novel class of algorithms, denoted Simpliied Wiener LMS (SWLMS), is presented here. The SWLMS algorithm is particularly well suited for tracking of parameters of mobile radio channels. The utility of the algorithm will be demonstrated on a mobile radio channel, where channel coeecients are subject to Rayleigh fading. The tracking scenario refers to the DAMPS 1900MHz standard.