Earticle

초록

영어

This paper deals with the ambiguity problem of blind source separation (BSS) in the case where continuously received mixture signals are split in time and processed block by block. Due to the inherent permutation and scaling ambiguities of BSS, tying the separated components at each adjacent time blocks doesn’t recover the original source signals correctly in general. Inspired by the Permutation Method of reconstructing source signal blocks in time domain, a new ambiguity elimination approach is proposed in this paper. This method aims to concatenate the separated components in adjacent blocks by artificially setting contrast blocks for each adjacent time blocks. The core idea of this method is to utilize the associativity between components recovered from contrast blocks and corresponding adjacent blocks. Compared with Permutation Method, the main advantage of this new method consists in the fact that it is much more efficient in terms of separation quality and computational speed. Besides, a tradeoff can be adjusted between separation quality and computational speed by choosing different length of contrast blocks. Real-life experiments are performed to validate the performance of this method on the wireless communication system with two transmitting and receiving antennas.

목차

Abstract
 1. Introduction
 2. System Model and Assumptions
  2.1. System Model
  2.2. Assumptions on the Model
 3. New Ambiguity Elimination Method
  3.1. Permutation and scaling ambiguities
  3.2. Contrast Blocks
  3.3. Procedure of New Ambiguity Elimination Method
 4. Experimental Results and Analysis
  4.1. Performance Validity
  4.2. Performance Analysis
 5. Conclusion
 Reference

키워드

저자

• Wei Zhao [ College of Communication Engineering, PLA University of Science and Technology, No. 1 Haifuxiang Road, Qinhuai District, Nanjing Jiangsu 210007, China ]
• Fengshan Wang [ College of Field Engineering, PLA University of Science and Technology, Nanjing Jiangsu 210007, China ] Corresponding Author
• Yuehong Shen [ College of Communication Engineering, PLA University of Science and Technology, No. 1 Haifuxiang Road, Qinhuai District, Nanjing Jiangsu 210007, China ]
• Yuanyuan Wu [ College of Communication Engineering, PLA University of Science and Technology, No. 1 Haifuxiang Road, Qinhuai District, Nanjing Jiangsu 210007, China ]
• Zhigang Yuan [ College of Communication Engineering, PLA University of Science and Technology, No. 1 Haifuxiang Road, Qinhuai District, Nanjing Jiangsu 210007, China ]
• Pengcheng Xu [ College of Communication Engineering, PLA University of Science and Technology, No. 1 Haifuxiang Road, Qinhuai District, Nanjing Jiangsu 210007, China ]
• Pengcheng Xu [ College of Communication Engineering, PLA University of Science and Technology, No. 1 Haifuxiang Road, Qinhuai District, Nanjing Jiangsu 210007, China ]
• Yimin Wei [ College of Communication Engineering, PLA University of Science and Technology, No. 1 Haifuxiang Road, Qinhuai District, Nanjing Jiangsu 210007, China ]
• Wei Jian [ College of Communication Engineering, PLA University of Science and Technology, No. 1 Haifuxiang Road, Qinhuai District, Nanjing Jiangsu 210007, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605