Low Complexity Signal Processing and Optimal Joint Detection for Over- Saturated Multiple Access Communications.

摘要

This paper addresses the problem of uncoded multiple access (MA) joint detection for the case in which user signatures are linearly dependent. The linearly dependent scenario would occur when the number of users in a communication system is increased beyond the dimension of the signal space available for transmission. This 'over-saturating' of the signal space can, in principle, be accomplished with minimal impact on system performance, assuming that optimal detection can he implemented. The optimal detector for the general over-saturated case has a complexity that is exponential in the number of users. To find a joint detector for the MA communication of K > N users in N dimensional signal space, the authors impose a hierarchical cross-correlation structure on the user signature waveforms. This paper develops a tree processing procedure that takes advantage of this structure to give the optimal estimate with an extremely low computational complexity. The authors show this complexity to be (in typical cases) a low-order-polynomial in the number of users. This is an enormous savings in computations over the O(2 sup K) computations needed if the signatures did not exhibit any structure.