Volume 2, Issue 4, August 2014, Page: 55-63
LabVIEW Based Design Implementation of M-PSK Transceiver Using Multiple Forward Error Correction Coding Technique for Software Defined Radio Applications
Nikhil Marriwala, Electronics & Communication Engineering Department, University Institute of Engineering and Technology, Kurukshetra University, Kurukshetra, India
Om Prakash Sahu, Electronics & Communication Engineering Department, National Institute of Technology, Kurukshetra, India
Anil Vohra, Electronics & Science Department, Kurukshetra University, Kurukshetra, India
Received: Oct. 19, 2014;       Accepted: Nov. 6, 2014;       Published: Nov. 14, 2014
DOI: 10.11648/j.jeee.20140204.11      View  4153      Downloads  532
Software-Defined Radio (SDR) is an enabling technology which is useful in a wide range of areas within wireless systems. SDR offers a perfect solution to the problem of spectrum scarcity in wireless communication. With the significant increase in the demand for reliable, high data rate transmission these days, a different number of modulation techniques need to be adopted. The main objective of this paper is to design and analyze an SDR based M-Phase Shift Keying (PSK) transceiver using LabVIEW (Laboratory Virtual Instrumentation Engineering Workbench) and to measure the Bit Error Rate (BER) in the presence of Additive White Gaussian Noise (AWGN) introduced in the channel. Forward Error Correction (FEC) is used as a channel coding scheme in this paper. FEC codes are used where the re-transmission of the data is not feasible, thus redundant bits are added along with the message bits and transmitted through the channel. This paper describes the fundamental concept for the design & development of an SDR -based transceiver simulation model under PSK Scheme & analyses the performance of two Forward Error Correction channel coding algorithms namely the Convolution and the Turbo Codes. In this paper we have shown that how fast and effectively we can build a PSK transceiver for interactive Software Defined Radio. With the help of this design we are able to see and prove that data errors can be minimized using coding techniques, which in turn improves the Signal to noise ratio (SNR).
Software Defined Radio, Bit Error Rate, Additive White Gaussian Noise, Phase Shift Keying, Signal-To-Noise Ratio, Forward Error Correction
To cite this article
Nikhil Marriwala, Om Prakash Sahu, Anil Vohra, LabVIEW Based Design Implementation of M-PSK Transceiver Using Multiple Forward Error Correction Coding Technique for Software Defined Radio Applications, Journal of Electrical and Electronic Engineering. Vol. 2, No. 4, 2014, pp. 55-63. doi: 10.11648/j.jeee.20140204.11
J. Mitola III,”Software Radios –Survey, Critical Evaluation and Future Directions,” in Proc. National Telesystems Conference, 1992, pp. 13/1513/23.
Matthew N. O. Sadiku and Cajetan M. Akujuobi "Software-defined Radio: A brief Overview", IEEE Potentials Journal, October/November 2004, pg. 14-15.
Wipro Technologies Innovative Solutions, Quality Leadership “Software-Defined Radio” White Paper: A Technology Overview, August 2002.
Nikhil Marriwala, O. P. Sahu, Anil Vohra,: “8-QAM Software Defined Radio Based Approach for Channel Encoding and Decoding Using Forward Error Correction”, Wireless Personal Communications, 1st May-2013, Springer US, 10.1007/s11277-013-1191-z.
Nikhil Marriwala, O. P. Sahu, Ritu Khullar and Anil Vohra, “Software Defined Radio (SDR) 4-bit QAM Modem using LabVIEW for Gaussian Channel”CIIT International Journal of Wireless Communication”. March 2011.
C. Berrou, A. Glavieux, and P. Thitimajshima. Near Shannon limit error correcting coding and decoding: Turbo codes. In Proceedings of the IEEE International Conference on Communications, Geneva, Switzerland, May 2003.
W. Tuttlebee, Software Defined Radio: Baseband Technologies for 3G Handsets and Base Stations, John Wiley & Sons, 2004.
Friedrich K. Jondral “Software-Defined Radio—Basics and Evolution to Cognitive Radio” (EURASIP Journal on Wireless Communications and Networking 2005:3, 275–283).
N. KIM, N. KEHTARNAVAZ, and M. TORLAK LabVIEW-Based Software-Defined Radio: 4-QAM Modem Proceedings of ICASSP, vol. 2, 2006, pp. 985-988.
Eric Nicollet and Lee Pucker, “Standardizing Transceiver APIs for Software Defined and Cognitive Radio”, www.rfdesign.com, February 2008,
P. Burns, “Software Defined Radio for 3G”, Artech House, 2002. ISBN 1-58053-347-7.
Amanpreet Singh Saini, “The Automated Systems For Spectrum Occupancy Measurement And Channel Sounding In Ultra-Wideband, Cognitive, Communication, And Networking” Master of Science in Electrical Engineering, August 2009.
RituKhullar, Sippy Kapoor, Naval Dhawan, “Modulation technique For Cognitive Radio, Applications”, International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.com Vol. 2, Issue 3, May-Jun 2012, pp. 123- 125.
Hiroyasu Ishikawa, “Software Defined Radio Technology for Highly Reliable Wireless Communications,” Wireless Personal Communications, 64 (2012), 461–72 dx.doi.org/10.1007/s11277-012-0596-4.
P. Prakasam and M. Madheswaran, “Intelligent Decision Making System for Digital Modulation Scheme Classification in Software Radio Using Wavelet Transform and Higher Order Statistical Moments,” Wireless Personal Communications, 50 (2008), 509–28 ,dx.doi.org/10.1007/s11277-008-9621-z.
Ying Chen and Linda M. Davis, “A Cross-Layer Adaptive Modulation and Coding Scheme for Energy Efficient Software Defined Radio,” Journal of Signal Processing Systems, 69 (2011), 23–30,dx.doi.org/10.1007/s11265-011-0644-4.
Shu-Ming Tseng, Yueh-Teng Hsu and Hong-Kung Lin, “Iterative Channel Decoding for PC-Based Software Radio DVB-T Receiver,” Wireless Personal Communications, 69 (2012), 403–11, dx.doi.org/10.1007/s11277-012-0580-z.
Browse journals by subject