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

机译:基于全局最优性必要条件的二进制二次规划多用户检测

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摘要

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.
机译:在本文中,我们提出了一种新颖的多用户检测方法,该方法使用了全局最优性二进制二阶规划的必要条件。所提出的方法分为两个步骤。在第1步中,根据必要条件,我们给出了可以直接确定用户信息序列的规则。通过该规则,可以以较低的计算复杂度来确定大多数用户信息序列。此外,决策结果可以显示为最佳。因此,我们可以在原始二次规划中利用这些结果,并在步骤1中为不确定的用户获得较小比例的二进制二次规划问题。然后,在步骤2中,我们可以使用一些现有的多用户检测方法来解决此简化的问题。 。所提出的方法的整体计算复杂度变小,并且BER降低。

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