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Differential Characteristics Based Iterative Multiuser Detection for Wireless Sensor Networks.
Chen, Xiaoguang; Jiang, Xu; Wu, Zhilu; Zhuang, Shufeng.
Afiliación
  • Chen X; School of Astronautics, Harbin Institute of Technology, Harbin 150001, China. chen_xiaoguang@hotmail.com.
  • Jiang X; China Academy of Space Technology, Beijing 100089, China. chen_xiaoguang@hotmail.com.
  • Wu Z; School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China. jiang520410@126.com.
  • Zhuang S; School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China. wuzhilu@hit.edu.cn.
Sensors (Basel) ; 17(2)2017 Feb 16.
Article en En | MEDLINE | ID: mdl-28212328
High throughput, low latency and reliable communication has always been a hot topic for wireless sensor networks (WSNs) in various applications. Multiuser detection is widely used to suppress the bad effect of multiple access interference in WSNs. In this paper, a novel multiuser detection method based on differential characteristics is proposed to suppress multiple access interference. The proposed iterative receive method consists of three stages. Firstly, a differential characteristics function is presented based on the optimal multiuser detection decision function; then on the basis of differential characteristics, a preliminary threshold detection is utilized to find the potential wrongly received bits; after that an error bit corrector is employed to correct the wrong bits. In order to further lower the bit error ratio (BER), the differential characteristics calculation, threshold detection and error bit correction process described above are iteratively executed. Simulation results show that after only a few iterations the proposed multiuser detection method can achieve satisfactory BER performance. Besides, BER and near far resistance performance are much better than traditional suboptimal multiuser detection methods. Furthermore, the proposed iterative multiuser detection method also has a large system capacity.
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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Sensors (Basel) Año: 2017 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Sensors (Basel) Año: 2017 Tipo del documento: Article País de afiliación: China