Cdma Blind Channel Equalization: a Weighted Subspace Approach

This paper considers the problem of blind demodulation of multiuser information symbols in a direct-sequence code-division multiple access (DSCDMA) environment. Channel estimation and symbol detection in presence of both multiple access interference (MAI) and intersymbol interference (ISI) is carried out with second order statistics methods from the received data. This problem is similar to Direction Of Arrival (DOA) estimation, where many solutions like the MUSIC algorithm or “weighted” techniques (as Deterministic Maximum Likelihood or Weighted Subspace Fitting method) have been developed. In this proposal these techniques are extended to blind DSCDMA channel identification problem in an unified framework known as Subspace Fitting. In this framework the estimated and the received data are “fitting” through the subspaces in a least square sense. Then, in order to achieve a better estimation of the channel, a modified Gauss-Newton type algorithm is suggested. Simulations are carried out comparing the proposed solutions with a classical signal subspacebased blind channel identification scheme.