Commutation in linear and nonlinear systems

In this paper we consider the commutability of linear and nonlinear blocks. We show that linearity is not necessary nor sufficient requirement for the commutability since matrix multiplication is not in general commutative although scalar multiplication is commutative. For linear time-invariant systems following the superposition principle we can use the product of two transfer functions, essentially a set of scalar multiplications, and therefore the blocks commute. On the other hand, some blocks are represented by a matrix, for example linear time-variant blocks and blocks describing I/Q imbalance. Such blocks do not in general commute unless the matrices have some special properties. Furthermore, nonlinear systems are not in general commutative. The commutability is not valid unless there is a special reason for that. Typical examples for commutability include (1) the systems are combined through a commutable operation, or (2) one of the systems is the inverse of the other system. Index Terms – commutability, linear systems, nonlinear systems, time-invariant systems, time-variant systems, inverse systems, predistortion, postdistortion, I/Q imbalance

[1]  Dayong Zhou,et al.  A novel adaptive nonlinear predistorter based on the direct learning algorithm , 2004, 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577).

[2]  J.E. Mazo,et al.  Digital communications , 1985, Proceedings of the IEEE.

[3]  Thomas Kailath,et al.  Correlation detection of signals perturbed by a random channel , 1960, IRE Trans. Inf. Theory.

[4]  P. K. Chaturvedi,et al.  Communication Systems , 2002, IFIP — The International Federation for Information Processing.

[5]  S. Haykin,et al.  Adaptive Filter Theory , 1986 .

[6]  Alan B. Marcovitz On inverses and quasi-inverses of linear time-varying discrete systems☆ , 1961 .

[7]  R W Lucky,et al.  Principles of data communication , 1968 .

[8]  J. Cavers,et al.  An adaptive direct conversion transmitter , 1992, [1992 Proceedings] Vehicular Technology Society 42nd VTS Conference - Frontiers of Technology.

[9]  S. Kay Fundamentals of statistical signal processing: estimation theory , 1993 .

[10]  P. Bello Characterization of Randomly Time-Variant Linear Channels , 1963 .

[11]  Edward J. Powers,et al.  A reconsideration of the pth-order inverse predistorter , 1999, 1999 IEEE 49th Vehicular Technology Conference (Cat. No.99CH36363).

[12]  A. Sideris,et al.  A multilayered neural network controller , 1988, IEEE Control Systems Magazine.

[13]  B. Widrow,et al.  Adaptive inverse control , 1987, Proceedings of 8th IEEE International Symposium on Intelligent Control.

[14]  R. de Figueiredo The Volterra and Wiener theories of nonlinear systems , 1982, Proceedings of the IEEE.

[15]  Frédéric de Coulon,et al.  Signal theory and processing , 1986 .