Complex polynomials in communications: motivation, algorithms, software

M. Hromcik1, M. Sebek1, J. Jezek2
1Centre for Applied Cybernetics Czech Technical University, Prague, Czech Republic
2Institute of Information Theory and Automation, AS CR, Prague, Czech Republic

Tóm tắt

Quite recently the polynomial design methods found a new great field of application outside the control area: the algebraic approach has been used successfully in signal processing and mobile communications. In contrast to the control systems synthesis, polynomials and polynomial matrices with complex coefficients are often required when designing filters, equalizers, decouplers and other components of mobile phones for instance. Polynomial Toolbox for Matlab admits complex polynomials in most computations, including Diophantine equations and spectral factorizations. As a result, the toolbox appears a suitable tool for rapid prototyping whenever polynomial design routines with complex coefficients are required. The objective of this report is twofold. First, we explain in a clear and popular manner how the complex coefficients arise in technical practice. Based on this motivation, we present important numerical algorithms for complex polynomials and polynomial matrices and their implementation in the Polynomial Toolbox for Matlab. Finally, the power of the Toolbox is illustrated by selected numerical examples involving complex coefficients.

Từ khóa

#Polynomials #Software algorithms #Signal processing algorithms #Mobile communication #Design methodology #Application software #Communication system control #Control system synthesis #Filters #Equalizers

Tài liệu tham khảo

hrorncfk, 0, Spectral Factorization by Means of Discrete Fourier Transform, 8th IEEE Mediterranean Conference on Control and Education MED 2000 henrion, 1998, Reliable algorithms for polynomial matrices kailath, 1980, Linear Systems kucera, 1991, Analysis and Design of Discrete Linear Control Systems vestry, 1975, New Algorithm for Polynomial Spectral Factorization with Quadratic Convergence I Kybernetika, 11, 415 vestry, 1976, New Algorithm for Polynomial Spectral Factorization with Quadratic Convergence I Kybernetika, 12, 248 jezek, 1985, Efficient Algorithm for Matrix Spectral Factorization, 29, 663 10.1137/0706001 kwakernaak, 0, PolyX Home Page hromcik, 2001, New Algorithm for Spectral Factorization Based on FFT and Its Practical Applications, Proceedings of the European Control Conference 2001 ahlen, 1994, Derivation and Design of Wiener Filters using Polynomial Equations, Control and Dynamic Systems, 64, 353 sternad, 1996, H-2 Design of Model-Based Nominal and Robust Discrete Time Filters, A Polynomial Approach to H-2 and H-infinity Robust Control Design, 171 tidestav, 1999, The multivariable decision feedback equalizer Multiuser detection and interference rejection, 197 10.1049/PBCE049E_ch5 proakis, 1994, Communication Systems Engineering macchi, 1995, Adaptive Processing The Least Mean Squares Approach and Applications in Transmission lindbom, 1995, A Wiener Filtering Approach to the Design of Tracking Algorithms with Applications to Mobile Radio Communication henrion, 1999, Efficient Algorithms for Discrete-TimeSymmetric Polynomial Equations with Complex Coefficients, Proceedings of the IFAC World Congress, d, 159 10.1109/TIT.1961.1057636