Multiuser Detections Based on Global Optimality Necessary Conditions for Binary Quadratic Programming

In this paper, we present a novel multiuser detection method using the global optimality necessary conditions for the binary quadratic programming. The proposed method is separated into two steps. In step 1, based on the necessary conditions, we give a rule that can decide the user information sequences directly. By this rule, most of user information sequences can be decided with a low computational complexity. Moreover, the decision results can be shown to be optimal. Therefore, we can take advantage of these results in the original quadratic programming and obtain a smaller-scaled binary quadratic programming problem for the undecided users in step 1. Then in step 2, we can use some existing multiuser detection methods to solve this reduced problem. The overall computation complexity of the proposed method becomes less, and the BER is lower.