Analysis of an adaptive decorrelating detector for synchronous CDNA channels

Multiuser detection allows for the efficient use of bandwidth in code-division multiple-access (CDNA) channels through mitigation of near-far effects and multiple-access noise limitations. The decorrelating detector developed by Lupas and Verdu is a linear multiuser detector that is asymptotically optimal in terms of near-far resistance when certain communication parameters are completely known to the detector. In this paper a simple adaptive decorrelating detector is developed by placing constraints on the set of spreading codes to be used by the active users. This adaptive detector has two modules: it first decorrelates the existing users and then it determines the spreading code of a new user entering the network with or without the use of a training sequence. Maximum likelihood detection is proposed for determining the new user's spreading code. The performance of this algorithm is studied by investigating the probability of making an error in determining the new user's spreading code as a function of the number of samples used to make the determination the number of users transmitting and the signal to noise ratio of the new user with respect to the ambient Gaussian noise.