Wireless systems are offering a wide variety of services to an ever increasing number of users. Undeniably, this connectivity has contributed to enhancing the quality of life. Though, the proliferation of wireless handheld devices and base stations led to an alarming downside due to their environmental impact. In fact, the carbon footprint of the wireless communication infrastructure is reaching unprecedented levels. This stimulated a global awareness about the need to reduce base stations energy consumption. In order to make communication systems more eco-friendly and “greener”, significant research work is being carried out at various aspects of base station design. This includes, among other things, scaling of energy needs depending on the traffic and network load, improving the ratio of quality of service to radiofrequency power, and increasing the overall efficiency of the base station. A closer look at base stations power consumption reflects that their overall efficiency can be significantly improved by increasing that of the radio frequency front end and especially the power amplifier. This would not only make communication systems greener but also reduce their deployment and running costs in terms of capital expenditure (CAPEX) and operational expenditure (OPEX), and result in substantial financial benefits.
Technically, building power amplifiers with peak power efficiencies as high as 80% has become feasible thanks to the development of new transistor technologies and new classes of operation such as switching mode. However, getting such high efficiencies from power amplifiers handling modern wireless communication systems is a tricky challenge. In fact, and due to the nature of the highly varying envelop signals being transmitted, base station power amplification systems have to be highly linear and meet the spectrum emission masks set by standardization and regulatory authorities. This requires the use of linearization techniques, which virtually make the power amplifier linear over its entire power range, thus allowing operation with less power back-off, and hence resulting in higher efficiencies compared to what could have been obtained from the same amplifier if no linearization was adopted. In this context, digital predistortion has received tremendous attention from the industrial and academic communities and incontestably appears to be the preferred technology for base station power amplifier linearization.
Conceptually, behavioral modeling and digital predistortion are intimately related. They are often referred to as forward and reverse modeling, respectively. This book focuses on the behavioral modeling and digital predistortion of wideband power amplifiers and transmitters. It compiles a wide range of topics related to this theme. The book is organized in 10 chapters, which can be organized into three parts. Chapters 1-3 set the ground for the remainder of the book by introducing the key parameters used to model and characterize the nonlinear behavior of wireless transmitters in Chapter 1, classifying and discussing the theory of dynamic nonlinear systems in Chapter 2, and providing a review of model performance evaluations metrics in Chapter 3. The second part of the book, Chapters 4-7, is a thorough review of behavioral models and predistortion functions that encompasses quasi-memoryless models in Chapter 4, memory polynomial based models in Chapter 5, box-oriented models in Chapter 6, and neural networks based models in Chapter 7. These models are introduced and their specificities discussed. The last part of the book, Chapters 8-10, is application oriented and provides comprehensive and insightful information about the use, in an experimental environment, of the models described earlier in the book. Chapter 8 covers the acquisition of the device-under-test (DUT) input and output data and its processing prior to the model identification. Chapter 9 is devoted to baseband digital predistortion and its practical aspects. Chapter 10 concludes the book by exposing recent trends in behavioral modeling and digital predistortion such as joint quadrature impairment compensation and digital predistortion, as well as the predistortion of dual-band and multi-input multi-output (MIMO) transmitters.
The book chapters are complemented with a software tool available through the Wiley website (www.wiley.com/go/Ghannouchi/Behavioral) that implements several of the topics discussed in the book and can be used to demonstrate these topics in a more tangible way.