A bibliography on nonlinear system identification
Signal Processing - Special section on digital signal processing for multimedia communications and services
Orthogonal polynomials for complex Gaussian processes
IEEE Transactions on Signal Processing - Part I
A Generalized Memory Polynomial Model for Digital Predistortion of RF Power Amplifiers
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
On the baseband representation of a bandpass nonlinearity
IEEE Transactions on Signal Processing - Part I
IEEE Transactions on Signal Processing
Identification of systems containing linear dynamic and static nonlinear elements
Automatica (Journal of IFAC)
IEEE Transactions on Consumer Electronics
Nonlinear Equalization of Digital Satellite Channels
IEEE Journal on Selected Areas in Communications
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This work presents an iterative receiver cancellation technique for mitigating the inband distortion introduced by a nonlinear wideband transmitter power amplifier (PA). The proposed decision-based technique employs a Wiener-Hammerstein model that accounts for the nonlinear transfer function and memory of the PA as well as for the wireless propagation channel. As such, the mitigation technique can be seen as a generalization of existing iterative decision-based techniques assuming memoryless PA nonlinearities. For successful distortion mitigation, the iterative technique requires an estimate of the nonlinear model that characterizes the PA. We propose to perform this model identification at the receiver, embedded in an iterative decision-based scheme, avoiding the nonideal analog-to-digital feedback loop associated with transmitter-based model identification. A stochastic algorithm is proposed for the model identification providing the necessary PA model parameters required for symbol detection. In addition, we analyze the convergence properties of the proposed technique. Simulation results confirm that the proposed mitigation technique provides distortion cancellation at almost the same level to the case of perfect knowledge of the PA model. These results enable us to employ power amplifiers with more relaxed linearity requirement, moving the operation point to a region with improved power efficiency while reducing the system overall degradation.