RNN based MIMO channel prediction

Signal Processing

Volumn 90, Issue 2, 2010, Pages 440-450

  Potter, Chris ^b   Venayagamoorthy, Ganesh K ^a,b   Kosbar, Kurt ^b  

^a MISSOURI UNIVERSITY OF SCIENCE AND TECHNOLOGY   (United States)

^b Architectural and Environmental Engineering   (United States)

Author keywords

Beam forming; Evolutionary algorithm (EA); Multiple input multiple output (MIMO); Particle swarm optimization (PSO); Recurrent neural networks (RNN)

Indexed keywords

ARRAY GAIN; AVERAGE PROBABILITY OF ERROR; CHANNEL PREDICTION; CODING GAINS; CORRELATED SYSTEMS; DIFFERENTIAL EVOLUTION; DIVERSITY GAIN; GAUSSIANS; HYBRID PSO; LINEAR PREDICTORS; MIMO CHANNEL; MULTIPLE-INPUT MULTIPLE-OUTPUT (MIMO); MULTIPLE-INPUT MULTIPLE-OUTPUT CHANNELS; NON-SATURATION; PREDICTION ERRORS;

ACOUSTIC INTENSITY; ALGORITHMS; GAUSSIAN BEAMS; MULTIPLEXING; OPTICAL COMMUNICATION; RECURRENT NEURAL NETWORKS; REINFORCEMENT LEARNING; SIGNAL TO NOISE RATIO;

PARTICLE SWARM OPTIMIZATION (PSO);

EID: 70349299826     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sigpro.2009.07.013     Document Type: Article

References (36)

1. E. Telatar, Capacity of multi-antenna gaussian channels, AT & T Bell Laboratories Internal Technical Memorandum, June 1995.
2. Papoulis A., and Pillai S. Probability Random Variables, and Stochastic Processes (1990), McGraw-Hill Science, New York
3. J. Huang, J. Winters, Sinusoidal modeling and prediction of fast fading processes, in: Global Tel. Conference, November 1998, pp. 892-897.
4. J. Andersen, J. Jensen, S. Jensen, F. Frederiksen, Prediction of future fading based on past measurements, in: IEEE Vehicular Technology Conference, September 1999, pp. 151-155.
5. Duel-Hallen A., Hu S., and Hallen H. Long range prediction of fading signals: enabling adaptive transmission for mobile radio channels. IEEE Signal Process. Mag. 17 (May 2000) 62-75
6. W. Liu, L.-L. Yang, L. Hanzo, Recurrent neural network based narrowband channel prediction, in: IEEE Vehicular Technology Conference, vol. 5, May 2006, pp. 2173-2177.
7. B. Visweswaran, T. Kiran, Channel prediction based power control in W CDMA systems, in: First International Conference on 3G Mobile Communication Technology, March 2000, pp. 41-45.
8. X. Gao, J. Tanskanen, S. Ovaska, Comparison of linear and neural network-based power prediction schemes for DS/CDMA systems, in: IEEE Vehicular Technology Conference, April 1996, pp. 61-65.
9. Gao X., Tanskanen J., and Ovaska S. Power prediction in mobile communication systems using an optimal neural network structure. IEEE Trans. Neural Networks 8 (November 1997) 1446-1455
10. Cai X., Zhang N., Venayagamoorthy G.K., and Wunsch D.C. Time series prediction with recurrent neural networks trained by a hybrid PSO-EA algorithm. J. Neurocomput. 70 (August 2007) 2342-2353
11. Proakis J. Digital Communications (1995), McGraw-Hill, New York, NY
12. Rappaport T.S. Wireless Communications: Principles and Practice (2002), Prentice-Hall, Upper Saddle River, NJ
13. Rice S. Statistical properties of a sine wave plus random noise. Bell Syst. Tech. J. 27 (1948) 109-157
14. A. Sampath, J. Holtzman, Estimation of maximum doppler frequency for handoff decisions, in: Proceedings of the IEEE VTC, May 1993, pp. 859-862.
15. Y. Bitran, Broadband data video, voice, and mobile convergence-extending the triple play, Texas Inst. White Paper 2004.
16. Zheng Y., and Xiao C. Improved models for the generation of multiple uncorrelated Rayleigh fading waveforms. IEEE Commun. Lett. 6 6 (2002)
17. Shiu D., Goschini G., Gans M., and Kahn J. Fading correlation and its effect on the capacity of multielement antenna systems. IEEE Trans. Commun. 48 3 (2000) 502-513
18. A. van Zelst, J. Hammerschmidt, A single coefficient spatial correlation model for multiple-input multiple-output (MIMO) radio channels, in: Proceedings of General Assembly of the International Union of Radio Science, August 2002.
19. Ortega J.M. Matrix Theory-A Second Course (1987), Plenum, New York, NY
20. Yoo T., and Goldsmith A. Capacity of fading mimo channels with channel estimation error. IEEE Commun. Soc. (2004) 808-813
21. Yoo T., and Goldsmith A. Capacity and power allocation for fading mimo channels with channel estimation error. IEEE Trans. Inform. Theory 52 5 (May 2006) 2203-2214
22. T. Yoo, E. Yoon, A. Goldsmith, Mimo capacity with channel uncertainty: Does feedback help? Proceedings of IEEE GlobeCom, 2004, pp. 96-100.
23. J. Kennedy, R. Eberhart, Particle swarm optimization, in: IEEE International Conference on Neural Networks, vol. 4, December 1995, pp. 1942-1948.
24. Valle Y., et al. Particle swarm optimization: basic concepts,variants and applications in power systems. IEEE Trans. Evol. Comput. 12 2 (April 2008) 171-195
25. Xu R., Venayagamoorthy G.K., and Wunsch D.C. Modeling of gene regulatory networks with hybrid differential evolution and particle swarm optimization. J. Neural Networks 21 (October 2007) 917-927
26. Jakes W. Microwave Mobile Communications (1993), IEEE Press, New York
27. Choi J., Bouchard M., and Yeap T. Decision feedback recurrent neural equalization with fast convergence rate. IEEE Trans. Neural Networks 16 3 (May 2005) 699-708
28. C. Potter, G.K. Venayagamoorthy, K. Kosbar, Mimo beam-forming with neural network channel prediction trained by a novel PSO-EADEPSO algorithm, in: IEEE World Congress on Computer Intelligence, 2008.
29. Jacson L. Digital Filters and Signal Processing (1989), Kluwer Academic Publishers, Dordrecht
30. A. Paulraj, R. Nabar, D. Gore, Introduction to Space-Time Wireless Communications, Cambridge University.
31. Bain L., and Engelhardt M. Introduction to Probability and Mathematical Statistics (1992), Brooks/Cole, Pacific Grove, CA
32. Lee W. Mobile Communication Engineering (1982), McGraw-Hill, New York
33. Fu J., Taniguchi T., and Karasawa Y. The largest eigenvalue characteristics for MIMO channel with spatial correlation. J. Global Optim. 6 (1995) 109-133
34. Goldsmith A. Wireless Communications (2005), Cambridge University Press, New York
35. Karagiannidis G., and Lioumpas A. An improved approximation for the Gaussian Q function. IEEE Commun. Lett. 11 8 (August 2007) 644-646
36. S. Gradshteyn, I. Ryzhik, A. Jeffrey, Table of Integrals, Series, and Products, fifth ed., Academic, San Diego, CA.