## 1 Introduction
Besides these, the multiuser detection (MUD) technique that caneliminate or weaken the negative effects of MAI is studied in [34; 35; 36; 37; 38; 39; 40; 41; 42; 43]. [PERSON] proposed the optimum multiuser detector (OMD) for code division multiple access (CDMA) systems [34], and it can achieve the optimal bit error rate (BER) performance [35] and the perfect near-far effect (NFE) resistant ability [36]. To DS-UWB systems, this OMD method was introduced by [PERSON] and [PERSON] [20]. However, the computational complexity of OMD growing exponentially with the number of active users makes it impractical to use [37]. Consequently, in order to make the tradeoff between performance and complexity, various sub-optimal MUD algorithms have been studied in literatures. In [38], a Reduced Complexity Maximum Likelihood (RCML) algorithm was proposed, but its practical use seems still impossible. In [39], a multiuser frequency-domain (FD) turbo detector combing FD turbo equalization schemes with soft interference cancelation was presented, whereas its BER performance is unsatisfactory. A multiuser detection method using a novel genetic algorithm base on complementary error function mutation (CEFM) was discussed for UWB systems in [40] and other swarm intelligence based MUD algorithms were studied in [41; 42; 43]. However, it is clear that a single multiuser detector cannot always be well suited for a particular occasion, particularly when the multipath or shadow fading happens. In [44; 45], distributed signal detection was extended to the multiuser problem, then the jointly optimum criterion and the individually optimum criterion were proposed for cooperating receivers. Essentially, the performance gain obtained by this overall procedure is due to its inherent diversity. However, this distributed MUD scheme is still of high computational complexity, as well as OMD. Besides, more antennas and more communication loads are involved in this procedure. In this paper, motivated by the concepts of decision-level fusion and distributed signal detection in [41; 45], we firstly apply the decision-level fusion techniques into the field of MUD. Then two novel MUD algorithms, that is the chairman arbitrating decision-level fusion criterion (CA-DFC) based MUD algorithm and the veto logic decision-level fusion criterion (VL-DFC) based MUD algorithm, are proposed for DS-UWB systems. In both of these methods, a set of sub-optimal detectors (including the minimum mean square error (MMSE) detector, the decorrelating (DEC) detector and the successive interference cancellation (SIC) detector) are used, and the preliminary decisions from these detectors will be merged together by CA-DFC or VL-DFC in the fusion center. The numerical results demonstrate that these two proposed MUD algorithms both have the much better BER performance and NFE resistant ability than other sub-optimal MUD algorithms, and even close to OMD. Meanwhile, the computational complexity of these novel methods is significantly lower than that of OMD. Compared with CA-DFC, VL-DFC based MUD method can achieve a little superior performance at the expense of its higher complexity. So these two proposed algorithms have their different application ranges. The remainder of this paper is organized as follows. In Section 2, some typical sub-optimal MUD algorithms are reviewed and the decision-level fusion based MUD system model is constructed for DS-UWB systems. In Section 3, the optimal decision-level fusion criterion (O-DFC) and its simplified form, which is the majority voting decision-level fusion criterion (MV-DFC), are discussed. On the problem analysis of O-DFC and MV-DFC, two novel MUD algorithms based on CA-DFC and VL-DFC are proposed respectively, in Section 4. In Section 5, simulation experiments that compare the performance of different MUD algorithms are made. Conclusions are in Section 6.