Image Processing Reference
In-Depth Information
3. Conclusions
The use of complex number mathematics greatly enhances the power of DSP, offering
techniques which cannot be implemented with real number mathematics alone. In
comparison with real DSP, complex DSP is more abstract and theoretical, but also more
powerful and comprehensive. Complex transformations and techniques, such as complex
modulation, filtering, mixing, z-transform, speech analysis and synthesis, adaptive complex
processing, complex Fourier transforms etc., are the essence of theoretical DSP. Complex
Fourier transforms appear to be difficult when practical problems are to be solved but they
overcome the limitations of real Fourier transforms in a mathematically elegant way.
Complex DSP techniques are required for many wireless high-speed telecommunication
standards. In telecommunications, the complex representation of signals is very common,
hence complex processing techniques are often necessary.
Adaptive complex filtering is examined in this chapter, since it is one of the most frequently-
used real-time processing techniques. Adaptive complex selective structures are
investigated, in order to demonstrate the high efficiency of adaptive complex digital signal
processing.
The complex DSP filtering method, based on the developed ACFB, is applied to suppress
narrowband interference signals in MIMO telecommunication systems and is then
compared to other suppression methods. The study shows that different narrowband
interference mitigation methods perform differently, depending on the parameters of the
telecommunication system investigated, but the complex DSP adaptive filtering technique
offers considerable benefits, including comparatively low computational complexity.
Advances in diverse areas of human endeavour, of which modern telecommunications is
only one, will continue to inspire the progress of complex DSP.
It is indeed fair to say that complex digital signal processing techniques still contribute more
to the expansion of theoretical knowledge rather than to the solution of existing practical
problems - but watch this space!
4. Acknowledgment
This work was supported by the Bulgarian National Science Fund - Grant No. ДО-02-
135/2008“Research on Cross Layer Optimization of Telecommunication Resource
Allocation”.
5. References
Baccareli, E.; Baggi, M. & Tagilione, L. (2002). A novel approach to in-band interference
mitigation in ultra wide band radio systems. IEEE Conf. on Ultra Wide Band Systems
and Technologies , pp. 297-301, 7 Aug. 2002.
Crystal, T. & Ehrman, L. (1968). The design and applications of digital filters with complex
coefficients, IEEE Trans. on Audio and Electroacoustics , vol. 16, Issue: 3, pp. 315-
320, Sept. 1968.
Douglas, S. (1999). Adaptive filtering, in Digital signal processing handbook , D. Williams & V.
Madisetti, Eds., Boca Raton: CRC Press LLC, pp. 451-619, 1999.
Fink L.M . (1984). Signals, hindrances, errors , Radio and communication, 1984.
Search WWH ::




Custom Search