Behavioral modeling and FPGA implementation of digital predistortion for RF and microwave power amplifiers

With the high interest in digital modulation techniques which are very sensitive to the PA nonlinearity, modern wireless communication systems require the usage of linearization techniques to improve the linear behavior of the RF power amplifier. The powerful and cheap digital processing technology makes the digital predistortion (DPD) a competitive candidate for the linearization of the PA. This thesis introduces the basic principle of DPD, its implementation on FPGA and the adaptive DPD system. The linearization of 4 PAs with DPD technique has been introduced: for the hybrid class AB PA operating at 2.6 GHz with a WiMAX testing signal, 33.7 dBm average power, 29.6 % drain efficiency, 13 dB ACPR and 9 dB NMSE improvement have been obtained; for the hybrid Doherty PA operating at 3.4 GHz with an I/Q testing signal, 35.0 dBm average power, 36.8 % drain efficiency, 12 dB ACPR and 13 dB NMSE improvement have been obtained; for the MMIC class AB PA operating at 7 GHz with an I/Q testing signal, 29.4 dBm average power, 25.7 % drain efficiency, 12 dB ACPR and 12 dB NMSE improvement have been obtained; for the two-stage PA operating at 24 GHz with an I/Q testing signal, 23.5 dBm average power, more than 14.0 % drain efficiency, 11 dB ACPR and 11 dB NMSE improvement have been obtained. The DPD algorithm has been implemented on FPGA with two methods based on LUT and a direct structure with only adders and multipliers. The block RAM on the FPGA board is chosen as the table in the LUT methods. The linearization performance for these three methods is similar. The test PA is the hybrid Doherty PA mentioned above and the test signal is the I/Q signal with 7.4 dB PAPR. 35.1 dBm average power, 36.8 % efficiency, 11 dB ACPR and 11 dB NMSE improvement have been obtained. The cost of logic resources for the direct structure method is the largest with 1,172 flip-flops, while the number of flip-flops for the two LUT methods are 263 and 583, respectively. A new adaptive algorithm has been proposed in this thesis for the adaptive DPD system. This new algorithm improves the performance in extracting the model parameters in complex number domain. With the experimental data from a combined class AB PA, the final accuracy of the model extracted by the new algorithm has been improved from -20 dB to about -40 dB and the converge speed is faster

Noise Cancellation Employing Adaptive Digital Filters for Mobile Applications

The persistent improvement of the hybrid adaptive algorithms and the swift growth of signal processing chip enhanced the performance of signal processing technique exalted mobile telecommunication systems. The proposed Artificial Neural Network Hybrid Back Propagation Adaptive Algorithm (ANNHBPAA) for mobile applications exploits relationship among the pure speech signal and noise corrupted signal in order to estimate of the noise. An adaptive linear system responds for changes in its environment as it is operating. Linear networks are gets adjusted at each time step based on new input and target vectors can find weights and biases that minimize the networks sum squared error for recent input and target vectors. Networks of this kind are quite oftenly used for error cancellation, speech signal processing and control systems.    Noise in an audio signal has become major problem and hence mobile communication systems are demanding noise-free signal. In order to achieve noise-free signal various research communities have provided significant techniques. Adaptive noise cancellation (ANC) is a kind of technique which helps in estimation of un-wanted signal and removes them from corrupted signal. This paper introduces an Adaptive Filter Based Noise Cancellation System (AFNCS) that incorporates a hybrid back propagation learning for the adaptive noise cancellation in mobile applications. An extensive study has been made to explore the effects of different parameters, such as number of samples, number of filter coefficients, step size and noise level at the input on the performance of the adaptive noise cancelling system. The proposed hybrid algorithm consists all the significant features of Gradient Adaptive Lattice (GAL) and Least Mean Square (LMS) algorithms. The performance analysis of the method is performed by considering convergence complexity and bit error rate (BER) parameters along with performance analyzed with varying some parameters such as number of filter coefficients, step size, number of samples and input noise level. The outcomes suggest the errors are reduced significantly when the numbers of epochs are increased. Also incorporation of less hidden layers resulted in negligible computational delay along with effective utilization of memory. All the results have been obtained using computer simulations built on MATLAB platfor

Process operating mode monitoring : switching online the right controller

This paper presents a structure which deals with process operating mode monitoring and allows the control law reconfiguration by switching online the right controller. After a short review of the advances in switching based control systems during the last decade, we introduce our approach based on the definition of operating modes of a plant. The control reconfiguration strategy is achieved by online selection of an adequate controller, in a case of active accommodation. The main contribution lies in settling up the design steps of the multicontroller structure and its accurate integration in the operating mode detection and accommodation loop. Simulation results show the effectiveness of the operating mode detection and accommodation (OMDA) structure for which the design steps propose a method to study the asymptotic stability, switching performances improvement, and the tuning of the multimodel based detector

Experimental comparison of parameter estimation methods in adaptive robot control

In the literature on adaptive robot control a large variety of parameter estimation methods have been proposed, ranging from tracking-error-driven gradient methods to combined tracking- and prediction-error-driven least-squares type adaptation methods. This paper presents experimental data from a comparative study between these adaptation methods, performed on a two-degrees-of-freedom robot manipulator. Our results show that the prediction error concept is sensitive to unavoidable model uncertainties. We also demonstrate empirically the fast convergence properties of least-squares adaptation relative to gradient approaches. However, in view of the noise sensitivity of the least-squares method, the marginal performance benefits, and the computational burden, we (cautiously) conclude that the tracking-error driven gradient method is preferred for parameter adaptation in robotic applications

Searching for improvement

Engineering design can be thought of as a search for the best solutions to engineering problems. To perform an effective search, one must distinguish between competing designs and establish a measure of design quality, or fitness. To compare different designs, their features must be adequately described in a well-defined framework, which can mean separating the creative and analytical parts of the design process. By this we mean that a distinction is drawn between coming up with novel design concepts, or architectures, and the process of detailing or refining existing design architecture. In the case of a given design architecture, one can consider the set of all possible designs that could be created by varying its features. If it were possible to measure the fitness of all designs in this set, then one could identify a fitness landscape and search for the best possible solution for this design architecture. In this Chapter, the significance of the interactions between design features in defining the metaphorical fitness landscape is described. This highlights that the efficiency of a search algorithm is inextricably linked to the problem structure (and hence the landscape). Two approaches, namely, Genetic Algorithms (GA) and Robust Engineering Design (RED) are considered in some detail with reference to a case study on improving the design of cardiovascular stents