Near-Optimal Multiuser Detection in Synchronous CDMA Using Probabilistic Data

[project topics]

Near-Optimal Multiuser Detection in Synchronous CDMA Using Probabilistic Data Association

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Presented By:
J. Luo, Student Member, IEEE, K. R. Pattipati, Fellow, IEEE, P. K. Willett, Senior Member, IEEE, and F. Hasegawa, Member, IEEE

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Abstract
A Probabilistic Data Association (PDA) method is proposed in this letter for multiuser detection over synchronous code-division multiple-access (CDMA) communication channels. PDA models the undecided user signals as binary random variables. By approximating the inter-user interference (IUI) as Gaussian noise with an appropriately elevated covariance matrix, the probability associated with each user signal is iteratively updated. Computer simulations show that the system usually converges within three to four iterations, and the resulting probability of error is very close to that of the optimal maximum-likelihood (ML) detector. Further modifications are also presented to significantly reduce the computational cost.


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http://engr.colostate.edu/~rockey/Papers/PDAJournal.pdf