Polynomial predictive filters : implementation and applications
No Thumbnail Available
URL
Journal Title
Journal ISSN
Volume Title
Doctoral thesis (article-based)
Checking the digitized thesis and permission for publishing
Instructions for the author
Instructions for the author
Unless otherwise stated, all rights belong to the author. You may download, display and print this publication for Your own personal use. Commercial use is prohibited.
Authors
Date
2000-12-15
Major/Subject
Mcode
Degree programme
Language
en
Pages
45, [70]
Series
Institute of Intelligent Power Electronics publications, 5
Abstract
In this thesis, smoothness of sampled real-world signals is exploited through the application of polynomial predictive filters. The principal reason for employing the polynomial signal model is principally twofold: firstly, assuming that the sampling rate is adequate, all real-world signals exhibit piecewise polynomial-like behavior, and secondly, polynomial-based signal processing is computationally efficient. By definition, polynomial predictive filters provide estimates of future values of polynomial-like signals. Thus, the potential applications of this research include a vast number of different delay sensitive operations on measurements like temperature, position, velocity, or power, especially in control engineering field. The polynomial-based predictive signal processing is a well-known technique, but polynomial-predictive filters have had severe drawbacks, which have hindered their application; their white noise attenuation is generally low, or they exhibit considerable passband gain peaks, rendering them unattractive for most applications. It has been possible to design IIR polynomial predictors, which exhibit applicable magnitude response properties, but the severe problem with them, as well as with the FIR polynomial predictors, has been that they have generally not been implementable in low-precision fixed-point environments because of their coefficient quantization sensitivity. In this thesis, coefficient quantization error-free designs of both FIR and IIR polynomial predictors are presented, thus providing methods for overcoming the above drawbacks and design problems. Polynomial differentiators are closely related to polynomial predictors; they are derived in a similar fashion, have design problems of a similar nature, and have applications in the control field. Both of these two filter types are discussed in this thesis; the proposed design methods are applicable to both of them. The implementation aspects of polynomial predictors and differentiators investigated here are also connected to the practical requirements of the application, namely delay alleviation in closed loop transmitter power control of multiuser mobile communications systems. Particularly, if predictive received power level estimation is implemented in handheld mobile terminals, this application specifies the implementation criteria as requirements on low imposed computational burden, low power consumption, and compact hardware size. All these criteria are met by providing the desired functionality using a small number of fixed-point arithmetic operations. Taking into account the results presented in this thesis, polynomial prediction fulfills these criteria. In this thesis, digital filter design methodologies are advanced by first-time introduction of exact low-degree polynomial prediction and discrete time differentiation in low-precision fixed-point computing environments, with, for example, 8 or 16 bits. Polynomial prediction is shown advantageous in the closed loop transmitter power control system application, and in comparisons with more complex and flexible predictors, it is shown to be a highly efficient method for this particular application. This thesis is seen as contributing to advances in practical polynomial predictor and differentiator design methods, and thereafter studies the application of polynomial predictors in mobile communications system transmitter power control. This research will be of interest to signal processing, control, and communications engineers and researchers alike.Description
Keywords
polynomial prediction, polynomial differentiation, predictor, differentiator, CDMA power control, mobile power control, closed loop control, fixed-point filter design, quantization error feedback
Other note
Parts
- Additional errata file available.
- J. M. A. Tanskanen and S. J. Ovaska, Coefficient sensitivity of polynomial-predictive FIR differentiators: Analysis, in Proc. 42nd IEEE Midwest Symposium on Circuits and Systems, Las Cruces, NM, USA, Aug. 1999, pp. 405-408. [article1.pdf] © 1999 IEEE. By permission.
- J. M. A. Tanskanen and S. J. Ovaska, Coefficient sensitivity of polynomial-predictive FIR differentiators: Design for short word length, in Proc. 42nd IEEE Midwest Symposium on Circuits and Systems, Las Cruces, NM, USA, Aug. 1999, pp. 520-523. [article2.pdf] © 1999 IEEE. By permission.
- J. M. A. Tanskanen and V. S. Dimitrov, Round-off Error Free Fixed-Point Design of Polynomial FIR Predictors and Predictive FIR Differentiators, Institute of Intelligent Power Electronics, Helsinki University of Technology, Espoo, Finland, Helsinki University of Technology Institute of Intelligent Power Electronics Publications, Publication 4, Aug. 2000 [electronic publication]. [article3.pdf] © 2000 by authors. Manuscript submitted to Digital Signal Processing, A Review Journal, Aug. 2000.
- J. M. A. Tanskanen, Coefficient quantization error free fixed-point IIR polynomial predictor design, in Proc. 2000 IEEE Nordic Signal Processing Symposium, Kolmården, Sweden, June 2000, pp. 219-222. [article4.pdf] © 2000 IEEE. By permission.
- J. M. A. Tanskanen, O. Vainio, and S. J. Ovaska, Adaptive general parameter extension for tuning FIR predictors, in Proc. 2nd IFAC Workshop on Linear Time Delay Systems, Ancona, Italy, Sept. 2000, pp. 42-47. [article5.pdf] © 2000 Elsevier Science. By permission.
- J. M. A. Tanskanen, A. Huang, T. I. Laakso, and S. J. Ovaska, Prediction of received signal power in CDMA cellular systems, in Proc. 45th IEEE Vehicular Technology Conference, Chicago, IL, USA, July 1995, pp. 922-926. [article6.pdf] © 1995 IEEE. By permission.
- J. M. A. Tanskanen, J. Mattila, M. Hall, T. Korhonen, and S. J. Ovaska, Predictive closed loop power control for mobile CDMA systems, in Proc. 47th IEEE Vehicular Technology Conference, Phoenix, AZ, USA, May 1997, pp. 934-938. [article7.pdf] © 1997 IEEE. By permission.
- J. M. A. Tanskanen, A. Huang, and I. O. Hartimo, Predictive power estimators in CDMA closed loop power control, in Proc. 48th IEEE Vehicular Technology Conference, Ottawa, Ontario, Canada, May 1998, pp. 1091-1095. [article8.pdf] © 1998 IEEE. By permission.
- X. M. Gao, X. Z. Gao, J. M. A. Tanskanen, and S. J. Ovaska, Power prediction in mobile communication systems using an optimal neural-network structure, IEEE Transactions on Neural Networks, vol. 8, pp. 1446-1455, Nov. 1997. [article9.pdf] © 1997 IEEE. By permission.