The Multivariable Decision Feedback Equalizer – Multiuser Detection and Interference Rejection

The multivariable decision feedback equalizer is investigated as a tool for multiuser detection and interference rejection. Three different DFE structures are introduced. The first DFE has a non-causal feedforward filter and a causal feedback filter. We show how its parameters can be tuned to give a minimum mean-square error. The second DFE is derived under the constraint of realizability. The explicit structure and design equations for an optimum realizable minimum mean-square error DFE are obtained. The zero-forcing criterion is also considered, and conditions for the existence of a zero-forcing solution are derived. We then consider a DFE where both feedforward and feedback filters are FIR filters of predetermined degrees. We discuss the tuning procedure for obtaining the parameters of a minimum mean-square error DFE and present the conditions for the existence of a zero-forcing solution. Two specific applications are considered next. In the first scenario, an antenna array is used at the receiver in a cellular system to accomplish spatial division multiple access. We compare two DFEs, operating as multiuser detectors and interference cancellers, respectively, and it is demonstrated that the difference in performance is small when few users are active in the system. We also show that the parameter estimation problem is more complicated for interference rejection. The second application is multiuser detection in DS-CDMA. A family of minimum mean-square error detectors with different amounts of decision feedback is designed, based on a possibly rapidly time-varying linear model. The linear model includes effects of the multipath channel, pulse shaping filters and the spreading. We also show that near-far resistance of the minimum mean-square error detectors can be guaranteed if and only if the parameters of the detector can be tuned so that the zero-forcing condition is fulfilled.