A Network of Kalman Filters for MAI and ISI Compensation in a Non-Gaussian Environment

This paper develops a new multiuser detector based on a network of kalman filters (NKF) dealing with multiple access-interference (MAI), intersymbol Interference (ISI), and an impulsive observation noise. The two proposed schemes are based on the modeling of the DS-CDMA system by a discrete-time linear system that has non-Gaussian state and measurement noises. By approximating the non-Gaussian densities of the noises by a weighted sum of Gaussian terms and under the common MMSE estimation criterion, we first derive an NKF detector. This version is further optimized by introducing a feedback exploiting the ISI interference structure. The resulting scheme is an NKF detector based on a likelihood ratio test (LRT). Monte-Carlo simulations have shown that the NKF and the NKF based on LRT detectors significantly improve the efficiency and the performance of the classical Kalman algorithm.

[1]  Guanrong Chen.  Approximate Kalman filtering , 1993 .

[2]  Branka Vucetic,et al.  Spread spectrum CDMA systems for wireless communications , 1997 .

[3]  David Middleton,et al.  Non-Gaussian Noise Models in Signal Processing for Telecommunications: New Methods and Results for Class A and Class B Noise Models , 1999, IEEE Trans. Inf. Theory.

[4]  Ramjee Prasad,et al.  A survey on CDMA: evolution towards wideband CDMA , 1998, 1988 IEEE 5th International Symposium on Spread Spectrum Techniques and Applications - Proceedings. Spread Technology to Africa (Cat. No.98TH8333).

[5]  Monisha Ghosh,et al.  Analysis of the effect of impulse noise on multicarrier and single carrier QAM systems , 1996, IEEE Trans. Commun..

[6]  Rimantas Pupeikis,et al.  On the Optimization of an Adaptive State Estimation of Dynamic Systems in the Presence of Time-varying Outliers , 2002, Informatica.

[7]  Theodore S. Rappaport,et al.  Measurements and simulation of radio frequency impulsive noise in hospitals and clinics , 1997, 1997 IEEE 47th Vehicular Technology Conference. Technology in Motion.

[8]  H. V. Trees.  Detection, Estimation, And Modulation Theory , 2001 .

[9]  D. Middleton,et al.  Man-Made Noise in Urban Environments and Transportation Systems: Models and Measurements , 1973, IEEE Trans. Commun..

[10]  Koeng-Mo Sung,et al.  Robust Kalman Filtering with Variable Forgetting Factor against Impulsive Noise , 2001 .

[11]  Bayan S. Sharif,et al.  Nonlinear decorrelator for multiuser detection in non-Gaussian impulsive environments , 2000 .

[12]  David Middleton,et al.  Statistical-Physical Models of Electromagnetic Interference , 1977, IEEE Transactions on Electromagnetic Compatibility.

[13]  C. Masreliez.  Approximate non-Gaussian filtering with linear state and observation relations , 1975 .

[14]  T. Başar,et al.  A New Approach to Linear Filtering and Prediction Problems , 2001 .

[15]  Sylvie Marcos,et al.  A network of adaptive Kalman filters for data channel equalization , 2000, IEEE Trans. Signal Process..

[16]  Bernard C. Picinbono.  Spherically invariant and compound Gaussian stochastic processes (Corresp.) , 1970, IEEE Trans. Inf. Theory.

[17]  H. Vincent Poor,et al.  Multiuser detection in flat fading non-Gaussian channels , 2002, IEEE Trans. Commun..

[18]  Wei Wei,et al.  Blind adaptive multiuser detection based on Kalman filtering , 2002, IEEE Trans. Signal Process..

[19]  Xiaodong Wang,et al.  Improved robust multiuser detection in non-Gaussian channels , 2001, IEEE Signal Processing Letters.

[20]  H. Vincent Poor,et al.  Joint channel estimation and symbol detection in Rayleigh flat-fading channels with impulsive noise , 1997, IEEE Communications Letters.

[21]  A. Spaulding,et al.  Optimum Reception in an Impulsive Interference Environment - Part I: Coherent Detection , 1977, IEEE Transactions on Communications.

[22]  Enzo Baccarelli,et al.  A reduced-state soft-statistics-based MAP/DF equalizer for data transmission over long ISI channels , 2000, IEEE Trans. Commun..

[23]  H. Sorenson,et al.  Nonlinear Bayesian estimation using Gaussian sum approximations , 1972 .

[24]  H. Vincent Poor,et al.  Recursive algorithms for identification of impulsive noise channels , 1990, IEEE Trans. Inf. Theory.

[25]  A.M. Zoubir,et al.  Multiuser detection in impulsive noise , 2001, Proceedings of the 11th IEEE Signal Processing Workshop on Statistical Signal Processing (Cat. No.01TH8563).

[26]  H. Vincent Poor,et al.  Robust multiuser detection in non-Gaussian channels , 1999, IEEE Trans. Signal Process..

[27]  Mario Tanda,et al.  An Analysis of Some Multiuser Detectors in Impulsive Noise , 1997 .

[28]  S. Marcos,et al.  A network of Kalman filters based detector for joint MAI and ISI suppression in asynchronous DS-CDMA systems , 2002, IEEE Seventh International Symposium on Spread Spectrum Techniques and Applications,.

[29]  Peter Jung,et al.  Advantages of CDMA and spread spectrum techniques over FDMA and TDMA in cellular mobile radio applications , 1993 .

[30]  A. Gualtierotti.  H. L. Van Trees, Detection, Estimation, and Modulation Theory, , 1976 .

[31]  H. Vincent Poor,et al.  Performance of DS/SSMA Communications in Impulsive Channels - Part I: Linear Correlation Receivers , 1986, IEEE Transactions on Communications.

[32]  C. L. Nikias,et al.  Signal processing with alpha-stable distributions and applications , 1995 .

[33]  Lars K. Rasmussen,et al.  An asynchronous multiuser CDMA detector based on the Kalman filter , 1998, IEEE J. Sel. Areas Commun..

[34]  E. Kamen,et al.  Introduction to Optimal Estimation , 1999 .

[35]  Marco Luise,et al.  Advances in satellite CDMA transmission for mobile and personal communications , 1996 .

[36]  H. Vincent Poor,et al.  Performance of DS/SSMA communications in impulsive channels. II. Hard-limiting correlation receivers , 1988, IEEE Trans. Commun..

[37]  Yao Ma,et al.  The Kalman Filter as the optimal linear minimum mean-squared error multiuser CDMA detector , 2000, IEEE Trans. Inf. Theory.

[38]  Ting Wang,et al.  Blind detection of CDMA signals based on Kalman filter , 2001, Conference Record of Thirty-Fifth Asilomar Conference on Signals, Systems and Computers (Cat.No.01CH37256).

[39]  D. Middleton,et al.  Optimum Reception in an Impulsive Interference Environment - Part II: Incoherent Reception , 1977, IEEE Transactions on Communications.

[40]  C Tidestav.  Designing equalizers based on explicit channel models of direct-sequence code-division multiple access systems , 1996 .

[41]  Bernard Fino,et al.  Multiuser detection: , 1999, Ann. des Télécommunications.

[42]  B. Ripley,et al.  Robust Statistics , 2018, Encyclopedia of Mathematical Geosciences.

[43]  Theodore S. Rappaport,et al.  Measurements and Models of Radio Frequency Impulsive Noise for Indoor Wireless Communications , 1993, IEEE J. Sel. Areas Commun..

[44]  Harry L. Van Trees,et al.  Detection, Estimation, and Modulation Theory: Radar-Sonar Signal Processing and Gaussian Signals in Noise , 1992 .

[45]  J. Thielecke,et al.  A state-space multiuser detector for CDMA systems , 1993, Proceedings of ICC '93 - IEEE International Conference on Communications.