Multiuser Detection in Asynchronous CDMA using PDA

The Probabilistic Data Association (PDA) method is extended to multiuser detection over asynchronous Code-Division Multiple Access (CDMA) communication channels. PDA models the undecided user signals as binary random variables. By approximating the Multiple Access Interference (MAI) as Gaussian noise with an appropriately evaluated covariance matrix, PDA updates the probabilities associated with user signals iteratively. A sliding window processing is used during the updates in order to avoid considering the entire data. Computer simulations show that the probability of group detection error of the proposed PDA method is very close to the performance lower bound. The computational complexity of the PDA detector is O((2h + 1)K) per time frame where K is the number of users and 2h+1 is the width of the processing window. Relations between the proposed PDA detector and the PDA detector for synchronous CDMA is also shown.