Résumé: The decorrelating decision-feedback (DDF) multiuser detector based on Cholesky factorization has been shown to alleviate the performance degradation of the users in the detection process, especially for relatively low cross-correlation values between user signals. A new detection concept for multiple users described in this paper employs two triangular matrices (upper and lower) and soft output information to improve the data estimates. Simulation results show that significant performance gains can be achieved over the DDF. Also, the users tend to have their bit error probabilities clustered. Thus, the performance of a given user is less dependent on its position in the detection process than for the DDF detector.

Langue: Anglais