Multiuser Detection via Robust Regression
4.2.1 System Model
For the sake of simplicity, we start the discussion in this
chapter by focusing on a real-valued discrete-time synchronous CDMA signal
model. At any time instant (until needed in Section 4.5, we will
suppress the symbol index i), the received signal
is the superposition of K users' signals, plus
the ambient noise, given by (see Section 2.2.1)
Equation 4.1
Equation 4.2
where, as before, 
, cj,k 
{+1, –1}, is the normalized signature waveform of the kth user; N is the
processing gain; bk {+1, –1} and Ak are, respectively, the data bit and the
amplitude of the kth user; 
; 
is a vector of independent and identically distributed (i.i.d.) ambient noise
samples. As noted above, we adopt the commonly used two-term Gaussian mixture
model for the additive noise samples {nj}. The marginal probability density function
(pdf) of this noise model has the form
Equation 4.3
with n
> 0, 0 
< and k
> 1. Here the N (0, n2) term represents
the nominal background noise, and the N (0, kn2) term represents the impulsive
component, with representing the probability that impulses occur. It is usually
of interest to study the effects of variation in the shape of a distribution on
the performance of the system, by varying the parameters and k with fixed total noise
variance
Equation 4.4
This model serves as an approximation to the more fundamental
Middleton class A noise model [321, 600] and has been used extensively to
model physical noise arising in radar, acoustic, and radio channels. In what
follows we discuss some robust techniques for multiuser detection in
non-Gaussian ambient noise CDMA channels, which are essentially robustified
versions of the linear decorrelating multiuser detector.
Sections
