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Improving the performance of third-generation wireless communication systems

Part of: Communication, information Limit theorems

Published online by Cambridge University Press:  01 July 2016

Remco van der Hofstad  and
Marten J. Klok
Remco van der Hofstad*
Affiliation:
Delft University of Technology
Marten J. Klok*
Affiliation:
Delft University of Technology
*
∗ Current address: Department of Mathematics and Computer Science, Eindhoven University of Technology, PO Box 513, 5600 MB Eindhoven, The Netherlands. Email address: [email protected]
∗∗ Current address: ORTEC BV, Orlyplein 145c, 1043 DV Amsterdam, The Netherlands. Email address: [email protected]
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Abstract

The third-generation (3G) mobile communication system uses a technique called code division multiple access (CDMA), in which multiple users use the same frequency and time domain. The data signals of the users are distinguished using codes. When there are many users, interference deteriorates the quality of the system. For more efficient use of resources, we wish to allow more users to transmit simultaneously, by using algorithms that utilize the structure of the CDMA system more effectively than the simple matched filter (MF) system used in the proposed 3G systems. In this paper, we investigate an advanced algorithm called hard-decision parallel interference cancellation (HD-PIC), in which estimates of the interfering signals are used to improve the quality of the signal of the desired user. We compare HD-PIC with MF in a simple case, where the only two parameters are the number of users and the length of the coding sequences. We focus on the exponential rate for the probability of a bit-error, explain the relevance of this parameter, and investigate how it scales when the number of users grows large. We also review extensions of our results, proved elsewhere, showing that in HD-PIC, more users can transmit without errors than in the MF system.

Keywords

Large deviation theoryexponential ratecode division multiple accesshard-decision parallel interference cancellation

MSC classification

Primary: 60F10: Large deviations
Secondary: 60F17: Functional limit theorems; invariance principles 94A11: Application of orthogonal and other special functions 94A12: Signal theory (characterization, reconstruction, filtering, etc.)
Type
General Applied Probability
Information
Advances in Applied Probability , Volume 36 , Issue 4 , December 2004 , pp. 1046 - 1084
Copyright
Copyright © Applied Probability Trust 2004 

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References

[1] Buehrer, R. M. and Woerner, B. D. (1996). Analysis of adaptive multistage interference cancellation for CDMA using an improved Gaussian approximation. IEEE Trans. Commun. 44, 1308–1329.Google Scholar
[2] Buehrer, R. M., Nicoloso, S. P. and Gollamudi, S. (1999). Linear versus non-linear interference cancellation. J. Commun. Networks 1, 118–133.CrossRefGoogle Scholar
[3] Buehrer, R. M., Kaul, A., Striglis, S. and Woerner, B. D. (1996). Analysis of DS-CDMA parallel interference cancellation with phase and timing errors. IEEE J. Selected Areas Commun. 14, 1522–1535.Google Scholar
[4] Dembo, A. and Zeitouni, O. (1992). Large Deviations Techniques and Applications. Jones and Barlett, Boston, MA.Google Scholar
[5] Den Hollander, F. (2000). Large Deviations (Fields Inst. Monogr. 14). American Mathematical Society, Providence, RI.Google Scholar
[6] Fey-den Boer, A. C., van der Hofstad, R. and Klok, M. J. (2003). Linear interference cancellation in CDMA systems and large deviations of the correlation matrix eigenvalues. In Proc. Symp. IEEE Benelux Chapter Commun. Veh. Tech. (Eindhoven, 2003).Google Scholar
[7] Fey-den Boer, A. C., van der Hofstad, R. and Klok, M. J. (2004). Large deviations for eigenvalues of correlation matrices. Submitted.Google Scholar
[8] Gold, R. (1967). Optimum binary sequences for spread spectrum multiplexing. IEEE Trans. Inf. Theory 13, 619–621.CrossRefGoogle Scholar
[9] Grimmett, G. R. and Stirzaker, D. R. (1992). Probability and Random Processes, 2nd edn. Oxford University Press.Google Scholar
[10] Holtzman, J. M. (1992). A simple, accurate method to calculate spread spectrum multiple-access error probabilities. IEEE Trans. Commun. 40, 461–464.CrossRefGoogle Scholar
[11] Johansson, J.-L. (1998). Successive interference cancellation in DS-CDMA systems. , Chalmers University of Technology.Google Scholar
[12] Juntti, M. (1998). Multiuser demodulation for DS-CDMA systems in fading channels. , University of Oulu.Google Scholar
[13] Kasami, T. (1966). Weight distribution formula for some class of cyclic codes. Tech. Rep. R-285, Coordinated Science Laboratory, University of Illinois, Urbana.CrossRefGoogle Scholar
[14] Klok, M. J. (2001). Asymptotic error rates in third generation wireless systems. Submitted.Google Scholar
[15] Klok, M. J. (2001). Performance analysis of advanced third generation receivers. , Delft University of Technology.Google Scholar
[16] Klok, M. J., Hooghiemstra, G., Ojanperä, T. and Prasad, R. (1999). A novel technique for DS-CDMA system performance evaluation. In Proc. IEEE 49th Vehicular Tech. Conf. (Houston, TX, May 1999), Vol. 2, pp. 958–962.Google Scholar
[17] Latva-Aho, M. (1999). Advanced receivers for wideband CDMA systems. , University of Oulu.Google Scholar
[18] Lehnert, J. S. and Pursley, M. B. (1987). Error probabilities for binary direct-sequence spread-spectrum communications with random signature sequences. IEEE Trans. Commun. 35, 87–98.CrossRefGoogle Scholar
[19] Morrow, R. K. and Lehnert, J. S. (1989). Bit-to-bit-error dependence in slotted DS/SSMA packet systems with random signature sequences. IEEE Trans. Commun. 37, 1052–1061.Google Scholar
[20] Moshavi, S. (1996). Multi-user detection for DS-CDMA communications. IEEE Commun. Mag. Oct. 1996, pp. 124–136.Google Scholar
[21] Patel, P. and Holtzman, J. (1994). Analysis of a simple successive interference cancellation scheme in a DS/CDMA system. IEEE J. Selected Areas Commun. 12, 796–807.CrossRefGoogle Scholar
[22] Pickholtz, R. L., Schilling, D. L. and Milstein, L. B. (1982). Theory of spread-spectrum communications—a tutorial. IEEE Trans. Commun. 30, 855–884 CrossRefGoogle Scholar
[23] Prasad, R. (1996). CDMA for Wireless Personal Communications. Artech House, Boston, MA.Google Scholar
[24] Prasad, R., Mohr, W. and Konhäuser, W. (2000). Third Generation Mobile Communication Systems. Artech House, Boston, MA.Google Scholar
[25] Rasmussen, L. K., Lim, T. J. and Johansson, A.-L. (2000). A matrix-algebraic approach to successive interference cancellation in CDMA. IEEE Trans. Commun. 48, 145–151.Google Scholar
[26] Sadowski, J. S. and Bahr, R. K. (1991). Direct-sequence spread-spectrum multiple-access communications with random signature sequences: a large deviations analysis. IEEE Trans. Inf. Theory 37, 514–527.Google Scholar
[27] Sunay, M. O. and McLane, P. J. (1996). Calculating error probabilities for DS CDMA systems: when not to use the Gaussian approximation. In Proc. IEEE Globecom (London, November 1996), Vol. 3, pp. 1744–1749.Google Scholar
[28] Tong, L. (1995). Blind sequence estimation. IEEE Trans. Commun. 43, 2986–2994.Google Scholar
[29] Van der Hofstad, R. and Klok, M. J. (2002). Optimal performance for DS-CDMA systems with hard decision parallel interference cancellation. IEEE Trans. Inf. Theory 25, 2918–2940.Google Scholar
[30] Van der Hofstad, R., Hooghiemstra, G. and Klok, M. J. (2002). Large deviations for code division multiple access systems. SIAM J. Appl. Math. 62, 1044–1065.Google Scholar
[31] Van der Hofstad, R., Löwe, M. and Vermet, F. (2004). Absence and existence of bit-errors in CDMA with and without interference cancellation. Submitted.Google Scholar
[32] Varanasi, M. K. and Aazhang, B. (1990). Multistage detection in asynchronous code-division multiple access communications. IEEE Trans. Commun. 38, 509–519.Google Scholar
[33] Verdu, S. (1986). Minimum probability of error for asynchronous Gaussian multiple access channels. IEEE Trans. Inf. Theory 32, 85–96.Google Scholar