PERFORMANCE EVALUATION OF INDEPENDENT COMPONENT ANALYSIS ALGORITHMS FOR DS-CDMA DETECTION
DOI:
https://doi.org/10.61841/brpaq972Keywords:
Independent Component Analysis, DS-CDMA, Blind Source Separation, Multi-User Detection, Symbol Error RateAbstract
Direct Sequence Code Division Multiple Access (DS-CDMA) systems are inherently limited by multi-user interference, particularly in dense cellular deployments. Independent Component Analysis (ICA) offers a blind preprocessing approach for interference suppression without requiring prior knowledge of spreading codes or channel parameters. This paper presents a quantitative performance evaluation of three widely used ICA algorithms—Cardoso’s Joint Approximate Diagonalization of Eigen-matrices (JADE), Hyvärinen’s FastICA fixed-point algorithm, and Comon’s mutual-information-based algorithm—for symbol detection in DS-CDMA downlink systems. Simulation results are compared against conventional Single User Detection (SUD), standalone ICA detection, and a combined SUD–ICA detection scheme under additive white Gaussian noise (AWGN) and colored (pink) noise conditions. Performance is assessed using symbol error rate (SER), convergence behavior, and robustness across signal-to-noise ratio (SNR). The results demonstrate that ICA-based detection provides measurable SER reductions relative to SUD, with JADE consistently achieving the best performance across all examined scenarios.
Downloads
References
[1] S. Verdu, Multiuser Detection. Cambridge, U.K.: Cambridge Univ. Press, 1998.
[2] T. Rappaport, Wireless Communications: Principles and Practice, 2nd ed. Upper Saddle River, NJ, USA: Prentice Hall, 2002.
[3] P. Comon, “Independent component analysis—A new concept?” Signal Processing, vol. 36, no. 3, pp. 287–314, Apr. 1994.
[4] J.-F. Cardoso and A. Souloumiac, “Blind beamforming for non-Gaussian signals,” IEE Proceedings F (Radar and Signal Processing), vol. 140, no. 6, pp. 362–370, Dec. 1993.
[5] J.-F. Cardoso, “High-order contrasts for independent component analysis,” Neural Computation, vol. 11, no. 1, pp. 157–192, Jan. 1999.
[6] A. Hyvärinen and E. Oja, “A fast fixed-point algorithm for independent component analysis,” Neural Computation, vol. 9, no. 7, pp. 1483–1492, Oct. 1997.
[7] A. Hyvärinen, J. Karhunen, and E. Oja, Independent Component Analysis. New York, NY, USA: Wiley, 2001.
[8] S. Haykin, Adaptive Filter Theory, 4th ed. Upper Saddle River, NJ, USA: Prentice Hall, 2002.
[9] X. Wang and H. V. Poor, “Blind multiuser detection: A subspace approach,” IEEE Transactions on Information Theory, vol. 44, no. 2, pp. 677–690, Mar. 1998.
[10] L. Tong, Y. Inouye, and R. Liu, “Waveform-preserving blind estimation of multiple independent sources,” IEEE Transactions on Signal Processing, vol. 41, no. 7, pp. 2461–2470, Jul. 1993.
[11] M. Honig, U. Madhow, and S. Verdú, “Blind adaptive multiuser detection,” IEEE Transactions on Information Theory, vol. 41, no. 4, pp. 944–960, Jul. 1995.
[12] S. Moshavi, “Multi-user detection for DS-CDMA communications,” IEEE Communications Magazine, vol. 34, no. 10, pp. 124–136, Oct. 1996.
[13] R. Lupas and S. Verdú, “Linear multiuser detectors for synchronous code-division multiple-access channels,” IEEE Transactions on Information Theory, vol. 35, no. 1, pp. 123–136, Jan. 1989.
[14] A. Goldsmith, Wireless Communications. Cambridge, U.K.: Cambridge Univ. Press,
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
