Wireless digital demodulation system via hierarchical multiresolution empirical mode decomposition approach

Kuang, Weichao, Ling, Bingo, Yang, Zhijing and Woo, Wai Lok (2016) Wireless digital demodulation system via hierarchical multiresolution empirical mode decomposition approach. In: 2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA). IEEE, pp. 1166-1170. ISBN 978-9-8814-7680-7

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1109/APSIPA.2015.7415455


This paper proposes a hierarchical multiresolution based empirical mode decomposition approach for performing a wireless digital demodulation. The waveform corresponding to each digital symbol is represented as the sum of the intrinsic mode functions. Each obtained intrinsic mode function of each symbol is further decomposed via a discrete cosine transform approach. First, zeros are inserted in each intrinsic mode function in the discrete cosine transform domain. Then, the next level empirical mode decomposition is performed in the time domain. The discrete cosine transform coefficients of the next level intrinsic mode functions where the zeros are added are removed in the discrete cosine transform domain. This step is repeated and the obtained intrinsic mode functions in each level form a dictionary. The received signals corrupted by the additive noises with unknown distributions and distorted by nonlinear channels are represented by both the weight vectors and the residue vectors based on the dictionary at each level of decomposition. The decoding scheme is to find the corresponding symbol such that the sum of the residue vectors in various levels of the decomposition is minimized. Experimental results show that the decoding accuracy is higher than that of the conventional matched filter approach.

Item Type: Book Section
Subjects: G900 Others in Mathematical and Computing Sciences
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Becky Skoyles
Date Deposited: 11 Apr 2019 10:20
Last Modified: 10 Oct 2019 20:05
URI: http://nrl.northumbria.ac.uk/id/eprint/38932

Actions (login required)

View Item View Item


Downloads per month over past year

View more statistics