Sequential amplitude estimation in multiuser communications

The authors consider the problem of multiuser amplitude estimation, i.e., the problem of estimating the amplitudes of several digital communications signals superimposed in the same channel. This problem is of importance in communications environments such as spread-spectrum radio networks, in which nonorthogonal multiplexing is used. Multiuser amplitude estimation is a critical prerequisite to the optimum demodulation of such signals using, for example, Verdu´s algorithm. Here, a sequential detection-estimation approach to this problem is adopted, and several estimation paradigms are considered, including the method of moments and likelihood-based estimators. The consistency, asymptotic variance, and complexity of these estimators are examined. It is seen that detector-estimators that use these estimators in Verdu´s algorithm result, asymptotically, in (known-amplitude) optimum error probabilities, with little relative increase in complexity per demodulated bit