Integrated Filters and Couplers for Next Generation Wireless Tranceivers

The main focus of this thesis is to investigate the critical nonlinear distortion issues affecting RF/Microwave components such as power amplifiers (PA) and develop new and improved solutions that will improve efficiency and linearity of next generation RF/Microwave mobile wireless communication systems. This research involves evaluating the nonlinear distortions in PA for different analog and digital signals which have been a major concern. The second harmonic injection technique is explored and used to effectively suppress nonlinear distortions. This method consists of simultaneously feeding back the second harmonics at the output of the power amplifier (PA) into the input of the PA. Simulated and measured results show improved linearity results. However, for increasing frequency bandwidth, the suppression abilities reduced which is a limitation for 4G LTE and 5G networks that require larger bandwidth (above 5 MHz). This thesis explores creative ways to deal with this major drawback. The injection technique was modified with the aid of a well-designed band-stop filter. The compact narrowband notch filter designed was able to suppress nonlinear distortions very effectively when used before the PA. The notch filter is also integrated in the injection technique for LTE carrier aggregation (CA) with multiple carriers and significant improvement in nonlinear distortion performance was observed. This thesis also considers maximizing efficiency alongside with improved linearity performance. To improve on the efficiency performance of the PA, the balanced PA configuration was investigated. However, another major challenge was that the couplers used in this configuration are very large in size at the desired operating frequency. In this thesis, this problem was solved by designing a compact branch line coupler. The novel coupler was simulated, fabricated and measured with performance comparable to its conventional equivalent and the coupler achieved substantial size reduction over others. The coupler is implemented in the balanced PA configuration giving improved input and output matching abilities. The proposed balanced PA is also implemented in 4G LTE and 5G wireless transmitters. This thesis provides simulation and measured results for all balanced PA cases with substantial efficiency and linearity improvements observed even for higher bandwidths (above 5 MHz). Additionally, the coupler is successfully integrated with rectifiers for improved energy harvesting performance and gave improved RF-dc conversion efficienc

Compensation of nonlinear distortion in RF amplifiers for mobile communications

Compensation of nonlinear distortion of power amplifiers in mobile communications is an important requirement for improving power consumption performance while maintaining efficiency, since mobile phone became an essential accessory for everyone nowadays. This problem demands a good power amplifier model, in order to develop an effective predistortion system. Current researches are focused on modelling and predistortion of power amplifiers with memory, as well as memoryless ones. Different methods for modelling are used, as the Volterra series, polynomial models, look-up tables, the Hammerstein models, the Wiener models, and artificial intelligence systems. For predistortion feedback, feedforward and digital predistortion techniques are used. Among digital predistortion methods there are artificial intelligence systems, used in this thesis for linearization of power amplifier. This thesis presents developed robust method for modelling power amplifiers without memory effects and gives a comparison of proposed method with least squares method. Also, this research presents two novel techniques based on artificial intelligence systems for modelling and predistortion of highly nonlinear power amplifier with memory. The first approach is based on artificial neural networks, while the second one uses adaptive fuzzy logic systems. Forward and inverse models of power amplifier are created with both proposed methods. Superiority of artificial intelligence systems over partial least squares method is presented. Developed models are employed in a cascade to make a linearized system. Verification of proposed methods is carried out through the signal performance parameters and spectra of measured signal and signal from predistortion system. The feasibility and performances of the proposed digital predistortions are examined by simulations and experiments. The comparison of proposed methods is given to present advantages/disadvantages of both methods. The achieved distortion suppression from 72.2% to 93.6% and spectral regrowth improvement from 11.4 dB to 16.2 dB prove that the proposed methods have great ability to compensate the nonlinear distortion in power amplifier

DESIGN OF A GAAS DISTRIBUTED AMPLIFIER WITH LC TRAPS BASED BROADBAND LINEARIZATION

Increasing the linearity of power amplifiers has been an important area of research because its signal integrity influences the performance of the entire transreceiver system and there are strict regulatory requirements on them. Due to the nonlinear behaviour of power amplifiers, third order intermodulation products are generated close to the desired signals and cannot be removed by filters. Increasing linearity will help bring these distortion products closer to the noise floor. However, it is not an easy task to increase linearity without trading off output power. To maintain the same level of output power generated but with higher linearity, many techniques, each with its own pros and cons, have been implemented to linearize an amplifier. Techniques involving feedback are seriously limited in terms of modulation bandwidth whereas methods such as predistortion and feedforward are very difficult to implement. This project seeks to use a simple method of placing terminations directly to the distributed amplifier (DA), making it a device level linearization technique and can be used in addition to the other system level techniques mentioned earlier. To increase linearity over a broad bandwidth of 0.5 to 3.0 GHz, this work proposes using low impedance terminations (LC traps) at the envelope frequency to the input and output of several distributed amplifiers. This research is novel since this is the first time broadband improvement in linearity has been demonstrated using the LC trap method. Two design iterations were completed (first design iteration has four variants to test the output trap while the second design iteration has three variants to test the input trap). The low impedance terminations are implemented using inductor-capacitor networks that are external to the monolithic microwave integrated circuit (MMIC). Design and layout of the DAs were carried out using Agilent’s Advanced Design System (ADS). Results show that placing the traps at the output of the DA does not truly affect the linearity of the device at lower frequencies but provide an improvement of 1.6 dB and 3.4 dB to the third-order output intercept point (OIP3) at 2.5 GHz and 3.0 GHz, respectively. With traps at the input, measurement results at -5 dBm input power, viii 1.375 V base bias (61 mA total collector current) and 10 MHz two tone spacing show a broadband improvement throughout the band (0.5 GHz to 3.0 GHz) of 3.3 dB to 7.4 dB in OIP3. Furthermore, the OIP3 is increased to 19.2 dB above P1dB. Results show that the improvement in OIP3 comes without lowering gain, return loss or P1dB and without causing any stability problems

A Survey of Blind Modulation Classification Techniques for OFDM Signals

Blind modulation classification (MC) is an integral part of designing an adaptive or intelligent transceiver for future wireless communications. Blind MC has several applications in the adaptive and automated systems of sixth generation (6G) communications to improve spectral efficiency and power efficiency, and reduce latency. It will become a integral part of intelligent software-defined radios (SDR) for future communication. In this paper, we provide various MC techniques for orthogonal frequency division multiplexing (OFDM) signals in a systematic way. We focus on the most widely used statistical and machine learning (ML) models and emphasize their advantages and limitations. The statistical-based blind MC includes likelihood-based (LB), maximum a posteriori (MAP) and feature-based methods (FB). The ML-based automated MC includes k-nearest neighbors (KNN), support vector machine (SVM), decision trees (DTs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) based MC methods. This survey will help the reader to understand the main characteristics of each technique, their advantages and disadvantages. We have also simulated some primary methods, i.e., statistical- and ML-based algorithms, under various constraints, which allows a fair comparison among different methodologies. The overall system performance in terms bit error rate (BER) in the presence of MC is also provided. We also provide a survey of some practical experiment works carried out through National Instrument hardware over an indoor propagation environment. In the end, open problems and possible directions for blind MC research are briefly discussed

ワイヤレス通信のための先進的な信号処理技術を用いた非線形補償法の研究

The inherit nonlinearity in analogue front-ends of transmitters and receivers have had primary impact on the overall performance of the wireless communication systems, as it gives arise of substantial distortion when transmitting and processing signals with such circuits. Therefore, the nonlinear compensation (linearization) techniques become essential to suppress the distortion to an acceptable extent in order to ensure sufficient low bit error rate. Furthermore, the increasing demands on higher data rate and ubiquitous interoperability between various multi-coverage protocols are two of the most important features of the contemporary communication system. The former demand pushes the communication system to use wider bandwidth and the latter one brings up severe coexistence problems. Having fully considered the problems raised above, the work in this Ph.D. thesis carries out extensive researches on the nonlinear compensations utilizing advanced digital signal processing techniques. The motivation behind this is to push more processing tasks to the digital domain, as it can potentially cut down the bill of materials (BOM) costs paid for the off-chip devices and reduce practical implementation difficulties. The work here is carried out using three approaches: numerical analysis & computer simulations; experimental tests using commercial instruments; actual implementation with FPGA. The primary contributions for this thesis are summarized as the following three points: 1) An adaptive digital predistortion (DPD) with fast convergence rate and low complexity for multi-carrier GSM system is presented. Albeit a legacy system, the GSM, however, has a very strict requirement on the out-of-band emission, thus it represents a much more difficult hurdle for DPD application. It is successfully implemented in an FPGA without using any other auxiliary processor. A simplified multiplier-free NLMS algorithm, especially suitable for FPGA implementation, for fast adapting the LUT is proposed. Many design methodologies and practical implementation issues are discussed in details. Experimental results have shown that the DPD performed robustly when it is involved in the multichannel transmitter. 2) The next generation system (5G) will unquestionably use wider bandwidth to support higher throughput, which poses stringent needs for using high-speed data converters. Herein the analog-to-digital converter (ADC) tends to be the most expensive single device in the whole transmitter/receiver systems. Therefore, conventional DPD utilizing high-speed ADC becomes unaffordable, especially for small base stations (micro, pico and femto). A digital predistortion technique utilizing spectral extrapolation is proposed in this thesis, wherein with band-limited feedback signal, the requirement on ADC speed can be significantly released. Experimental results have validated the feasibility of the proposed technique for coping with band-limited feedback signal. It has been shown that adequate linearization performance can be achieved even if the acquisition bandwidth is less than the original signal bandwidth. The experimental results obtained by using LTE-Advanced signal of 320 MHz bandwidth are quite satisfactory, and to the authors’ knowledge, this is the first high-performance wideband DPD ever been reported. 3) To address the predicament that mobile operators do not have enough contiguous usable bandwidth, carrier aggregation (CA) technique is developed and imported into 4G LTE-Advanced. This pushes the utilization of concurrent dual-band transmitter/receiver, which reduces the hardware expense by using a single front-end. Compensation techniques for the respective concurrent dual-band transmitter and receiver front-ends are proposed to combat the inter-band modulation distortion, and simultaneously reduce the distortion for the both lower-side band and upper-side band signals.電気通信大学201

Cognitive Radio Systems

Cognitive radio is a hot research area for future wireless communications in the recent years. In order to increase the spectrum utilization, cognitive radio makes it possible for unlicensed users to access the spectrum unoccupied by licensed users. Cognitive radio let the equipments more intelligent to communicate with each other in a spectrum-aware manner and provide a new approach for the co-existence of multiple wireless systems. The goal of this book is to provide highlights of the current research topics in the field of cognitive radio systems. The book consists of 17 chapters, addressing various problems in cognitive radio systems

Design and Implementation of an RF Front-End for Software Defined Radios

Software Defined Radios have brought a major reformation in the design standards for radios, in which a large portion of the functionality is implemented through pro­ grammable signal processing devices, giving the radio the ability to change its op­ erating parameters to accommodate new features and capabilities. A software radio approach reduces the content of radio frequency and other analog components of the traditional radios and emphasizes digital signal processing to enhance overall receiver flexibility. Field Programmable Gate Arrays (FPGA) are a suitable technology for the hardware platform as they offer the potential of hardware-like performance coupled with software-like programmability. Software defined radio is a very broad field, encompassing the design of various technologies all the way from the antenna to RF, IF, and baseband digital design. The RF section primarily consists of analog hardware modules. The IF and baseband sections are primarily digital. It is the general process of the radio to convert the incoming signal from RF to IF and then IF to baseband for better signal processing system. In this thesis, some of major building blocks of a Software defined radio are de­ signed and implemented using FPGAs. The design of a Digital front end, which provides the bridge between the baseband and analog RF portions of a wireless receiver, is synthesized. The Digital front end receiver consists of a digital down converter(DDC) which in turn comprises of a direct digital frequency synthesizer (DDFS), a phase accumulator and a low pass filter. The signal processing block of the DDFS is executed using Co-ordinate Rotation Digital Computer (CORDIC) iii Abstract algorithm. Cascaded-Integrator-Comb filters (CIC) are implemented for changing the sample rate of the incoming data. Application of a DDC includes software ra­ dios, multicarrier, multimode digital receivers, micro and pico cell systems,broadband data applications, instrumentation and test equipment and in-building wireless tele­ phony. Also, in this thesis, interfaces for connecting Texas Instruments high speed and high resolution Analog-to-Digital converters (ADC) and Digital-to-Analog converters (DAC) with Xilinx Virtex-5 FPGAs are also implemented and demonstrated

Wavelet Theory

The wavelet is a powerful mathematical tool that plays an important role in science and technology. This book looks at some of the most creative and popular applications of wavelets including biomedical signal processing, image processing, communication signal processing, Internet of Things (IoT), acoustical signal processing, financial market data analysis, energy and power management, and COVID-19 pandemic measurements and calculations. The editor’s personal interest is the application of wavelet transform to identify time domain changes on signals and corresponding frequency components and in improving power amplifier behavior