Project Summary


C. 3 Impacts and Contributions in Research and Education



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C. 3 Impacts and Contributions in Research and Education

The LML detectors investigated in this project provide a new means of multiuser detection for CDMA network to increase usable bandwidth and network throughput. The proposed investigation will impact basic research in signal processing for multiuser communications, and is expected to benefit directly applications to fourth-generation wireless mobile communications systems. This project will contribute new knowledge and method to applications to broad areas of wireless communication networks, high-speed data transmission, wireless internet service, digital television, magnetic recording, global positioning systems, and image processing, and to theories of the fields of multiuser detection, hypothesis testing, wireless communications, neural networks, and image processing.



The area of communications in the PI’s Department of Electrical Engineering at the City Collage of New York is currently relatively weak. Only the PI is in the area of physical layer communications. Several communication related courses such as Spread Spectrum and Information Theory and Coding have not been offered for long since a senior faculty member was retired. Several other modern communication courses such as Digital Communications at both undergraduate and graduate levels, and Statistical Signal Estimation and Detection at graduate level have not been included in the curriculum (the faculty meeting of this department just approved PI’s proposal to open Digital Communications I, and II at graduate level in next year). On the other hand, several surveys showed significant student demand on opening communication courses. This department has decided to develop a strong communication program. The hiring process for a new faculty member in telecommunications has been activated. Currently this PI works on a research project in the Collaborative Technology Alliances (CTA) program supported by ARL. This PI directs three Ph.D. students in addition to about five MS projects and reports and five undergraduate students in independent study yearly. The City College of New York is a minority college. Each year several minority students (most are MS and undergraduate students) participated in the research with the PI through assigning them projects and independent study. The support of this proposed project will help set up a strong program in communications in this department and provide new research opportunities for both graduate and undergraduate students, and in particular the minority students. The increased minority students’ research activities in modern communications will strengthen the traditional diversity environment of this collage.

References Cited


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  46. X. Zhang and D. Brady, “Asymptotic multiuser efficiency for decision-directed multiuser detection,” IEEE Trans. Inform. Theory, vol. 44, pp. 502-515, Mar. 1998.

  47. R. M. Beuhrer and S. P. Nicoloso, “ Comments on ‘partial parallel interference cancellation for CDMA’,” IEEE Trans. Commun., vol. 47, no. 5, pp. 658-661, May 1999.

  48. D. R. Brown, M Motani, V. V. Veeravalli, H. V. Poor, and C. R. Johnson, “On the performance of linear parallel interference cancellation,” IEEE Trans. on Infor. Theory, vol. 47, no. 5, pp. 1957-1970, July 2001.

  49. L. B. Nelson and H. V. Poor, “Iterative multiuser receivers for CDMA channels: an EM-based approach,” IEEE Trans. on Commun., vol. 44, no. 12, pp. 1700-1710, Dec. 1996.

  50. D. Raphaeli, “Suboptimal maximum-likelihood multiuser detection of synchronous CDMA on frequency-selective multipath channels,” IEEE Trans. on Commun., vol. 48, no. 5, pp. 875-885, May 2000.

  51. B. Wu and Q. Wang, “New suboptimal multiuser detectors for Synchronous CDMA systems,” IEEE Trans. on Commun., vol. 44, no. 7, pp. 782-785, July 1996.

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  53. J. K. Paik and A. K. Katsaggelos, "Image restoration using a modified Hopfield network," IEEE Trans. on Image Processing, Vol. 1, No. 1, pp. 49-63, Jan. 1992.

  54. Y. Sun and S.-Y. Yu, "A modified Hopfield neural network used in bilevel image restoration and reconstruction," in Proc. Int. Symp. on Inform. Theory Applica., ICCS/ISITA'92, Singapore, Nov. 16-20, 1992, vol. 3, pp. 1412-1414.

  55. Y. Sun and S.-Y. Yu, "An eliminating highest error criterion in Hopfield neural network for bilevel image restoration," In Proc. Int. Symp. on Inform. Theory Applicat., ICCS/ISITA'92, Singapore, Nov. 16-20, 1992, vol. 3, pp. 1409-1411.

  56. Y. Sun and S.-Y. Yu, "An eliminating highest error (EHE) criterion in Hopfield neural networks for bilevel image restoration," Pattern Recognition Letters, vol. 14, no. 6, pp. 471-474, June 1993.

  57. H.-J. Liu and Y. Sun, "Blind bilevel image restoration using Hopfield neural networks," in Proc. IEEE Int. Conf. on Neural Networks, ICNN'93, San Francisco, CA, Mar. 28-Apr. 1, 1993, pp. 1656-1661.

  58. Y. Sun, J.-G. Li and S.-Y. Yu, “Improvement on performance of modified Hopfield neural network for image restoration,” IEEE Trans. on Image Processing, vol. 4, no. 5, pp. 688-692, May 1995.

  59. Y. Sun, "Hopfield neural network based algorithms for image restoration and reconstruction - Part I: algorithms and simulations," IEEE Trans. on Signal Processing, vol. 48, no. 7, pp. 2105-2118, July 2000.

  60. Y. Sun, "Hopfield neural network based algorithms for image restoration and reconstruction - Part II: performance analysis," IEEE Trans. on Signal Processing, vol. 48, no. 7, pp. 2119-2131, July 2000.

  61. Y. Sun, "A generalized updating rule for modified Hopfield neural network," in Proc. IEEE Int. Conf. on Neural Networks, ICNN’97, Houston, Texas, June 9-12, 1997, pp. 1227-1230.

  62. Y. Sun, "A generalized updating rule for modified Hopfield neural network for quadratic optimization," Neurocomputing, 19 (1998), pp. 133-143.

  63. Y. Sun, "Eliminating-highest-error and fastest-metric-descent criteria and iterative algorithms for bit-synchronous CDMA multiuser detection," in Proc. IEEE Int. Conf. on Commun., ICC'98, Atlanta, Georgia, June 7-11, 1998, pp. 1576-1580.

  64. Y. Sun, "Search algorithms based on eliminating-highest-error and fastest-metric-descent criteria for bit-synchronous CDMA multiuser detection," in Proc. IEEE Int. Conf. on Commun., ICC'98, Atlanta, Georgia, June 7-11, 1998, pp. 390-394.

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  73. D. N. C. Tse, and S. V. Hanly, “Linear multiuser receivers: effective interference, effective bandwidth and user capacity,” IEEE Trans. on Inform. Theory, vol. 45, no. 2, pp. 641-657, March 1999.

  74. X. Cai, Y. Sun, and A. N. Akansu, "Asymptotic performance of DS-CDMA random access systems with packet combining in fading channels," submitted to IEEE J. on Select. Area in Commun. (revised).

  75. Y. Sun, and X. Cai, "Multiuser detection for packet-switched CDMA networks with retransmission diversity," submitted to IEEE Trans. on Signal Processing.

  76. X. Cai, Y. Sun, and A. N. Akansu, “Performance of slotted CDMA random access systems with packet combining in fading channels,” in Proc. 34th Annual Conference on Information Science and Systems, CISS'2001, The Johns Hopkins University, Baltimore, Maryland, March 21-23, 2001.




Biographical Sketch





Yi Sun
Department of Electrical Engineering

The City College of the City University of New York

Convent Avenue at 138th Street

New York, NY 10031

Phone: (212)650-6621; Fax: (212) 650-8249

E-mail: sun@ccny.cuny.edu



Education
Ph.D., EE, University of Minnesota, Minneapolis, MN, 1997

MSEE, Shanghai Jiao Tong University, Shanghai, P. R. China, 1985

BSEE, Shanghai Jiao Tong University, Shanghai, P. R. China, 1982





Professional Experience
Assistant Professor, City College of City University of New York, New York, NY, Sept. 1998 -

Postdoctoral Research Associate, University of Connecticut, Storrs, CT, Oct. 1997-Aug. 1998

Postdoctoral Research Fellow, University of Utah, Salt Lake City, Utah, March-Sept. 1997

Research intern, Northern Telecom, Eagan, MN, summer 1996 - Jan. 1997

Research intern, ADC Telecommunications, Minnetonka, MN, summer 1995

Research and Teaching Assistants, University of Minnesota, Minneapolis, MN, 1993 - 1996

Visiting Scientist, Concordia University, Montreal, Canada, summer 1993

Lecturer, Shanghai Jiao Tong University, Shanghai, P. R. China, 1985-1993



Publications Related to Proposed Project
[1] Y. Sun, “Local maximum likelihood multiuser detection,” in Proc. 34th Annual Conference on Information Science and Systems, CISS'2001, pp. 7-12, The Johns Hopkins University, Baltimore, Maryland, March 21-23, 2001.

[2] Y. Sun, “A family of linear complexity likelihood ascent search multiuser detectors for CDMA communications,” in Proc. 34th Asilomar Conference on Signals, Systems, and Computers, vol. 2, pp. 1163 -1167, Pacific Grove, CA, Oct. 29 - Nov. 1, 2000.

[3] Y. Sun, "Hopfield neural network based algorithms for image restoration and reconstruction - Part I: algorithms and simulations," IEEE Trans. on Signal Processing, vol. 48, no. 7, pp. 2105-2118, July 2000.

[4] Y. Sun, "Hopfield neural network based algorithms for image restoration and reconstruction - Part II: performance analysis," IEEE Trans. on Signal Processing, vol. 48, no. 7, pp. 2119-2131, July 2000.

[5] Y. Sun, "A generalized updating rule for modified Hopfield neural network for quadratic optimization," Neurocomputing, pp.133-143, 19 (1998). 


Other Significant Publications
[1] Y. Sun, "Bandwidth-efficient wireless OFDM," IEEE J. on Select. Area in Commun., vol. 19, no. 11, pp. 2267-2278, Nov. 2001.

[2] Y. Sun and D. Parker, "Small vessel enhancement for MRA images using local maximum mean processing," IEEE Trans. on Image Processing, vol. 10, no. 11, pp. 1687-1699, Nov. 2001.

[3] Y. Sun and D. Parker, "Performance analysis of maximum intensity projection algorithm for display of MRA images," IEEE Trans. on Medical Imaging, vol. 18, no. 12, pp. 1154-1169, Dec. 1999.

[4] Y. Sun, "Stochastic iterative algorithms for signal set design for Gaussian channels and optimality of the L2 signal set," IEEE Trans. on Information Theory, vol. 43, pp. 1574-1587, Sept. 1997.

[5] Y. Sun, J.-G. Li and S.-Y. Yu, “Improvement on performance of modified Hopfield neural network for image restoration,” IEEE Trans. on Image Processing, Vol. 4, No. 5, pp. 688-692, May 1995.



List of Collaborators
Prof. Myung Lee City College of New York

Prof. Terak Saadawi City College of New York

Prof. Dennis Parker University of Utah

(applicant’s postdoctoral advisor, 20 graduates, 3 postdoctors)

Prof. Lang Tong Cornell University

(applicant’s postdoctoral advisor, 10 graduates, 4 postdoctors)

Prof. John Kieffer University of Minnesota

(applicant’s Ph.D. advisor)

Dr. Laurie Nelson IDA Center for Communications Research

(applicant’s Ph.D. co-advisor)






1 In this proposal, the optimum detector is called the GML detector in contrast with the proposed LML detectors.

2 As will be addressed in the next subsection, this applicant developed a family of modified Hopfield neural network based algorithms which can update any number of bits per step with guaranteed convergence. When applied to multiuser detection, these algorithms perform likelihood ascent search and form the family of LAS detectors.


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