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Automatic Analog/Digital Modulation Recognition for SDR Implementation with FPAA

R. Kannan, S. Ravi

Abstract


Automatic modulation recognition for software defined radio (SDR) is a research focused on developing 3G and 4G wireless communications with adaptive modulation capability. The existing automatic modulation recognition technology does not satisfy the seamless demodulation requirement of the SDR. The design of automatic modulation recognition method with reduced computational complexity and fast processing speed is needed. The radio systems are increasingly incorporating dynamically configurable software into software defined radio (SDR) design. The ability to change software after manufacture makes SDR a perfect platform for designing Cognitive Radio (CR). The equipment must handle higher channel densities and must meet a high-availability standard to provide uninterrupted service. In addition, the equipment will be flexible to accommodate various air protocols. The statistical performance of the fast automatic modulation recognition associated with its implementation using the SDR is discussed in this work.

Keywords


ASIC, FPAA, SDR.

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References


W. M. Gardner and C. M. Spooner, “Signal interception: Performance advantages of cycle-feature detectors,” IEEE Trans. on Comm., vol. 40, no.1, Jan. 1992.

D.J. Bem, Wieckowski, T. W., and Zielinski, R., "Broadband Satellite Systems", IEEE Communications Surveys & Tutorials, First quarter, vol. 3, no. 1, 2000.

W. Wei and J. M. Mendel, "Maximum-likelihood classification for digital amplitude-phase modulations," IEEE Transactions on Communications, vol.48, pp.189-193, 2000.

P. Panagiotou, A. Anastasopoulos, and A. Polydoros, "Likelihood ratio tests for modulation classification," Military Communications Conference 2000, MILCOM 2000 IEEE, pp.670-674, vol.2, Los Angeles, CA, Oct. 2000.

Pucker, Lee, "Choosing the Right Signal Processing Devices for a Software Defined Radio Design: DSP, ASIC, or FPGA", Communications Systems Design, June 2001.

W. Su and J. Kosinski, "Comparison and simulation of digital modulation recognition algorithms," International Symposium on Advanced Radio Technologies 2003, ISART 2003 IEEE, Boulder, CO, Mar. 2003.

J. Polson, “Cognitive radio applications in software defined radio,” in Proc of the SDR Forum Conference 2004.

L. Dorie, S. Le Nours, O. Pasquier and J. F. Diouris, "A system level model for software defined radio design," Radio and Wireless Symposium 2006, RWS 2006 IEEE, pp.463-466, San Diego, CA, Oct. 2006.

O. A. Dobre, A. Abdi, Y. Bar-Ness, and W. Su, "Survey of automatic modulation classification techniques: classical approaches and new trends," IET Communications, vol.1, pp.137-156, Apr. 2007.

A. Abidi, "The path to the software-defined radio receiver," IEEE Journal of Solid-State Circuits, vol.42, no.5, pp.954-966, May 2007.

K. Kim, I. A. Akbar, K. K. Bae, J. Um, C. M. Spooner, and J. H. Reed, “Cylostationary approaches to signal detection and classification in cognitive radios,” in Proc. IEEE Dynamic Spectrum Access Nets., pp. 212-215, 2007.

N. Alyaoui, H. B. Hnia, A. Kachouri, and M. Samet, "The modulation recognition approaches for software radio," International Symposium on Signals, Circuits and Systems 2008, ISSCS 2008 IEEE, pp.1-5, 7-9, Seattle, WA, Nov. 2008.

F. Hameed, O. A. Dobre, and D. C. Popescu, "On the likelihood-based approach to modulation classification," IEEE Transactions on Wireless Communications, vol.8, no.12, pp.5884-5892, Dec. 2009.


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