Correcting the Bias of Subtractive Interference Cancellation in CDMA: Advanced Mean Field Theory

In this paper we introduce an advanced mean field method to correct the inherent bias of conventional subtractive interference cancellation in Code Division Multiple Access (CDMA). In simulations, we get a performance quite close to that of the individual optimal exponential complexity detector and significant improvements over current state-of-the-art subtractive interference cancellation in all setups tested, for example in one case doubling the number of user at a bit error rate of ¢ ¡ ¤ £ ¦ ¥. To obtain such a good performance for finite size systems, where the performance is normally degraded by the presence of suboptimal fix-point solutions, it is crucial to use the method in conjunction with mean field annealing, i.e. solving the fixed point equations at decreasing temperatures (noise levels). In the limit of infinite large system size, the new subtractive interference cancellation scheme is expected to be identical to the individual optimal detector. The computational complexity is cubic in the number of users whereas conventional (naive mean field) subtractive interference cancellation is quadratic. We also present a quadratic complexity approximation to our new method that also gives performance improvements , but in addition requires knowledge of the spreading code statistics. The proposed methodology is quite general and is expected to be applicable to other digital communication problems.