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Mathematical Problems in Engineering
Volume 2016, Article ID 1930541, 9 pages
Research Article

Efficient DS-UWB MUD Algorithm Using Code Mapping and RVM

1China Academy of Space Technology, Xi’an Branch, Xi’an 710100, China
2School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China
3Institute of Telecommunication Satellite, China Academy of Space Technology, Beijing 100000, China

Received 3 March 2015; Revised 14 December 2015; Accepted 21 December 2015

Academic Editor: Marzio Pennisi

Copyright © 2016 Pingyan Shi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A hybrid multiuser detection (MUD) using code mapping and a wrong code recognition based on relevance vector machine (RVM) for direct sequence ultra wide band (DS-UWB) system is developed to cope with the multiple access interference (MAI) and the computational efficiency. A new MAI suppression mechanism is studied in the following steps: firstly, code mapping, an optimal decision function, is constructed and the output candidate code of the matched filter is mapped to a feature space by the function. In the feature space, simulation results show that the error codes caused by MAI and the single user mapped codes can be classified by a threshold which is related to SNR of the receiver. Then, on the base of code mapping, use RVM to distinguish the wrong codes from the right ones and finally correct them. Compared with the traditional MUD approaches, the proposed method can considerably improve the bit error ratio (BER) performance due to its special MAI suppression mechanism. Simulation results also show that the proposed method can approximately achieve the BER performance of optimal multiuser detection (OMD) and the computational complexity approximately equals the matched filter. Moreover, the proposed method is less sensitive to the number of users.