Browse > Article
http://dx.doi.org/10.5515/KJKIEES.2011.22.3.282

Adaptive Modulation System Using SNR Estimation Method Based on Correlation of Decision Feedback Signal  

Kim, Seon-Ae (Department of Electronic Engineering, Chungbuk National University)
Ryu, Heung-Gyoon (Department of Electronic Engineering, Chungbuk National University)
Publication Information
The Journal of Korean Institute of Electromagnetic Engineering and Science / v.22, no.3, 2011 , pp. 282-291 More about this Journal
Abstract
Adaptive modulation(AM) is an important technique to increase the system efficiency, in which transmitter selects the most suitable modulation mode adaptively according to channel state in the temporary and spatially varying communication environment. Fixed modulation on channels with varying signal-to-noise ratio(SNR) is that the bit-errorrate(BER) probability performance is changing with the channel quality. An adaptive modulation scheme can be designed to have a BER which is constant for all channel SNRs. The correct as well as fast and simple SNR estimation is required essentially for this adaptive modulation. In order to operate adaptive modulation system effectively, in this paper, we analyze the effect of SNR estimation performance to it through the average BER and data throughput. Applying SNR estimation based on auto-correlation of decision feedback signal and others to adaptive modulation system, we also confirm performance degradation or improvement of its which is decided by SNR estimation error at each transition point of modulation level. Since SNR estimation based on auto-correlation of decision feedback signal shows stable estimation performance for various quadrature amplitude modulation(QAM) comparatively, this can be reduced degradation than others at each transition point of modulation level.
Keywords
Adaptive Modulation; SNR Estimation; Decision Feedback; BER; Throughput;
Citations & Related Records
연도 인용수 순위
  • Reference
1 M. Alvarez-Diaz, R. Lopez-Valcarce, and C. Mosquera, "SNR estimation for multilevel constellations using higher-order moments", IEEE Transactions on Signal Processing, vol. 58, no. 3, Part 2, pp. 1515-1526, Mar. 2010.   DOI
2 A. Stephenne, F. Bellili, and S. Affes, "Momentbased SNR estimation over linearly-modulated wireless SIMO channels", IEEE Transactions on Wireless Communications, vol. 9, no. 2, pp. 714-722, Feb. 2010.   DOI
3 W. Gappmair, R. Lopez-Valcarce, and C. Mosquera, "Cramer-Rao lower bound and EM algorithm for envelope-based SNR estimation of nonconstant modulus constellations", IEEE Transactions on Commun., vol. 57, no. 6, pp. 1622-1627, Jun. 2009.   DOI
4 H. Hayes, Statistical Digital Signal Processing and Modeling, John Wiley, 1996.
5 H. Van Trees, Detection, Estimation, and Modulation Theory, vol. 1, New York, Wiley, 1968.
6 R. van Nee, R. Prasad. OFDM for Wireless Multimedia Communications. Norwood, MA: Artech House, 2000.
7 S. Falahari, A. Svensson, T. Ekman, and M. Sternad, "Adaptive modulation systems for predicted wireless channels", IEEE Transactions on Commun., vol. 52, no. 2, pp. 307-316, Feb. 2004.   DOI
8 G. Albertazzi, S. Cioni, G. Corazza, M. Neri, R. Pedone, P. Salmi, A. Vanelli-Coralli, and M. Villanti, "On the adaptive DVB-S2 physical layer: Design and performance", IEEE Wireless Commun. Mag., vol. 12, no. 6, pp. 62-68, Dec. 2005.   DOI
9 A. Svensson, "An introduction to adaptive QAM modulation schemes for known and predicted channels", Proceedings of the IEEE, vol. 95, no. 12, pp. 2322-2336, Dec. 2007.   DOI
10 K. M. Kamath, D. L. Goeckel, "Adaptive-modulation schemes for minimum outage probability in wireless systems", IEEE Transactions on Commun., vol. 52, no. 10, pp. 1632-1635, Oct. 2004.   DOI
11 D. R. Pauluzzi, N. C. Beaulieu, "A comparison of SNR estimation techniques for the AWGN channel", IEEE Transactions on Commun., vol. 48, no. 10, pp. 1680-1691, Oct. 2000.   DOI
12 R. Lopez-Valcarce, C. Mosquera, "Sixth-order statistics-based nondata-aided SNR estimation", IEEE Commun. Lett., vol. 11, no. 4, pp. 351-353, Apr. 2007.   DOI