Linear Predictor and Interpolator
As mentioned before, linear or nonlinear predictive NBI
suppression methods are based on the following idea. Since the spread-spectrum
signal has a nearly flat spectrum, it cannot be predicted accurately from its
past values without explicit use of knowledge of the spreading code. On the
other hand, the interfering signal, being narrowband, can be predicted
accurately. These methods essentially form a replica of the NBI, which can be
subtracted from the received signal to enhance the wideband components. The
linear methods have involved primarily the use of linear transversal prediction
or interpolation filters to create the NBI replica. Such a filter forms a linear
prediction of the received signal based on a fixed number of previous samples,
or a linear interpolation based on a fixed number of past and future samples.
This estimate is subtracted from the appropriately timed received signal to
obtain the error signal to be used as input to the SS user signature sequence
correlator.
Let Si(w) denote the power spectral density of the NBI
signal. The following output SINR upper bounds
for the linear prediction/interpolation methods can be found in [310, 311]:
Equation 7.122
Equation 7.123
Sections
