Volume 6, Issue 2, June 2018, Page: 37-46
Analysis on Multichannel Filter Banks-Based Tree-Structured Design for Communication System
Aye Than Mon, Department of Electronic Engineering, Technological University (Pathein), Pathein, Myanmar
Su Mon Aye, Department of Electronic Engineering, Technological University (Pathein), Pathein, Myanmar
Hla Myo Tun, Department of Electronic Engineering, Yangon Technological University, Yangon, Myanmar
Zaw Min Naing, Department of Electronic Engineering, Yangon Technological University, Yangon, Myanmar
Win Khaing Moe, Department of Electronic Engineering, Yangon Technological University, Yangon, Myanmar
Received: Jun. 23, 2018;       Accepted: Jul. 5, 2018;       Published: Aug. 2, 2018
DOI: 10.11648/j.se.20180602.12      View  425      Downloads  24
Abstract
This research aims to design and implement of tree-structured multichannel filter banks using MATLAB. The multichannel filter banks analysis are evaluated by the Digital Signal Processing (DSP) techniques. The multi rate analysis is suitable for sampling rate reduction and sampling rate increase on the digital filter design. When increasing sampling rate, filtering follows the up-sampling operation. The role of the filter is to attenuate unwanted periodic spectra which appear in the new baseband. The performance evaluation for tree-structured multichannel filter banks design is described in this research work. The experimental results for implemented design are implemented in this paper. The use of an appropriate filter enables one to convert a digital signal of a specified sampling rate into another signal with a target sampling rate without destroying the signal components of interest. The performance of multirate filtering for implemented design is evaluated by using MATLAB.
Keywords
DSP, Tree-Structured Multichannel Filter Banks, MATLAB, Digital Filter Design, Multirate Techniques
To cite this article
Aye Than Mon, Su Mon Aye, Hla Myo Tun, Zaw Min Naing, Win Khaing Moe, Analysis on Multichannel Filter Banks-Based Tree-Structured Design for Communication System, Software Engineering. Vol. 6, No. 2, 2018, pp. 37-46. doi: 10.11648/j.se.20180602.12
Copyright
Copyright © 2018 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Reference
[1]
Lutovac, M. D., & Tošić, D. V., & Evans, B. L. (2000). Filter design for signal processing using MATLAB and Mathematica. Upper Saddle River, N J: Prentice Hall.
[2]
Milić, L. D., & Lutovac, M. D. (2002). Efficient multirate filtering. In Gordana Jovanović-Doleček, (ed.), Multirate Systems: Design & Applications. Hershey, PA: Idea Group Publishing, 105-142.
[3]
Milić, L. D., & Lutovac, M. D. (2003). Efficient algorithm for the design of high-speed elliptic IIR filters. AEÜ Int. J. Electron. Commun, 57(4), 255-262.
[4]
Ansari, R., & Liu, B., (1993). Multirate signal processing. In Sanjit. K. Mitra and James F. Kaiser (ed.), Handbook for Digital Signal Processing. New York: John Wiley-Interscience, 981-1084.
[5]
Filter design toolbox for use with MATLAB. User’s guide. Version 6. (2006). Natick: MathWorks.
[6]
Fliege, N. J. (1994). Multirate digital signal processing. New York, NY: John Wiley.
[7]
Johnston, J. D. (March 1980). A filter family designed for use in quadrature mirror filter banks. Proceedings of the IEEE International Conference Acoustics, Speech, and Signal Processing, 291–294.
[8]
Mitra, S. K. (2006). Digital signal processing: A computer based approach. 3rd edition. New York, NY: The McGraw-Hill Companies, Inc.
[9]
Saramäki, T. Multirate Signal Processing. (2001). Lecture notes for a graduate course, the Institute of Signal Processing, Tampere University of Technology, Finland.
[10]
Saramäki, T., & Bregovic, R. (2002). Multirate systems and filter banks. In Gordana Jovanović-Doleček, (ed.), Multirate Systems: Design & Applications. Hershey, PA: Idea Group Publishing, 27-85.
[11]
Signal processing toolbox for use with MATLAB. User’s guide. Version 6. (2006). Natick: Math-Works.
[12]
Strang, G., & Nguyen, T. (1996). Wavelets and Filter Banks. Wellesley, MA: Wellesley-Cambridge Press.
[13]
Vaidyanathan, P. P. (1987). Quadrature mirror filter banks, M-band extensions and perfect-reconstruction techniques. IEEE ASSP Magazine, 4(3), 4-20.
[14]
Vaidyanathan, P. P. (1993). Multirate systems and filter banks. Englewood Cliffs, NJ: Prentice Hall.
[15]
Wavelet toolbox for use with MATLAB. User’s guide. Version 3. (2006). Natick: MathWorks.
[16]
Vetterli, M., & Kovačević, J.(1995). Wavelets and Subband Codding. Englewood Cliffs, N. J.: Prentice Hall.
[17]
Yue-Dar Jou. (May 2007). Design of two-channel linear-phase quadrature mirror filter banks based on neural networks. Signal Processing, 87(5), 1031-1044.
[18]
S. Dimitrov, “Non-linear distortion noise cancellation for satellite forward links,” in Proc. 8th Advanced Satellite Multimedia Systems Conference (ASMS2016), Palma de Mallorca, Spain, Sep. 5-7 2016.
[19]
S. Dimitrov, “Iterative cancellation of non-linear distortion noise in digital communication systems,” IEEE Trans. Commun., vol. 63, no. 6, pp. 2325–2336, Jun. 2015.
[20]
Implementation Guidelines for the Second Generation System for Broadcasting, Interactive Services, News Gathering and Other Broadband Satellite Applications; Part II: S2-Extensions (DVB-S2X), Digital Video Broadcasting (DVB) Std. ETSI TR 102 376-2, Mar. 2015.
Browse journals by subject