Linearisation, error correction coding and equalisation for multi-level modulation schemes

University of Technology, Sydney. Faculty of Engineering.Orthogonal frequency division multiplexing (OFDM) has been standardised for digital audio broadcasting (DAB), digital video broadcasting (DVB) and wireless local area networks (WLAN). OFDM systems are capable of effectively coping with frequency- selective fading without using complex equalisation structures. The modulation and demodulation processes using fast fourier transform (FFT) and its inverse (IFFT) can be implemented very efficiently. More recently, multicarrier code division multiple access (MC-CDMA) based on the combination of OFDM and conventional CDMA has received growing attention in the field of wireless personal communication and digital multimedia broadcasting. It can cope with channel frequency selectivity due to its own capabilities of overcoming the asynchronous nature of multimedia data traffic and higher capacity over conventional multiple access techniques. On the other hand, multicarrier modulation schemes are based on the transmission of a given set of signals on large numbers of orthogonal subcarriers. Due to the fact that the multicarrier modulated (MCM) signal is a superposition of many amplitude modulated sinusoids, its probability density function is nearly Gaussian. Therefore, the MCM signal is characterised by a very high peak-to-average power ratio (PAPR). As a result of the high PAPR, the MCM signal is severely distorted when a nonlinear high power amplifier (HPA) is employed to obtain sufficient transmitting power. This is very common in most communication systems, and decreases the performance significantly. The simplest way to avoid the nonlinear distortion is substantial output backoff (OBO) operating in the linear region of the HPA. However, because of the high OBO, the peak transmit power has to be decreased. For this reason, many linearisation techniques have been proposed to compensate for the nonlinearity without applying high OBO. The predistortion techniques have been known and studied as one of the most promising means to solve the problem. In this thesis, an improved memory mapping predistortion technique devised to reduce the large computational complexity of a fixed point iterative (FPI) predistorter is proposed, suitable especially for multicarrier modulation schemes. The proposed memory mapping predistortion technique is further extended to compensate for nonlinear distortion with memory caused by a shaping linear filter. The case of varying HPA characteristics is also considered by using an adaptive memory mapping predistorter which updates the lookup table (LUT) and counteracts these variations. Finally, an amplitude memory mapping predistorter is presented to reduce the LUT size. Channel coding techniques have been widely used as an effective solution against channel fading in wireless environments. Amongst these, particular attention has been paid to turbo codes due to their performance being close to the Shannon limit. In-depth study and evaluation of turbo coding has been carried out for constant envelope signaling systems such as BPSK, QPSK and M-ary PSK. In this thesis, the performance of TTCM-OFDM systems with high-order modulation schemes, e.g. 16-QAM and 64-QAM, is investigated and compared with conventional channel coding schemes such as Reed-Solomon and convolutional coding. The analysis is performed in terms of spectral efficiency over a multipath fading channel and in presence of an HPA. Maximum a-priori probability (MAP), soft output Viterbi algorithm (SOVA) and pragmatic algorithms are compared for non-binary turbo decoding with these systems. For this setup, iterative multiuser detection in TTCM/MC-CDMA systems with M-QAM is introduced and investigated, adopting a set of random codes to decrease the PAPR. As another application of TTCM, the performance of multicode CDMA systems with TTCM for outer coding over multipath fading channels is investigated

Multiple lookup table predistortion for adaptive modulation

This paper presents a multiple LUT digital adaptive predistorter based on a Hammerstein model that uses the return channel to feed back information from the receiver, concretely the bit error rate (BER), in order to train and later adapt the specific LUT gains that permit always operating at the best back-off level. This new predistorter architecture is aimed at coping with modern communication standards that use adaptive modulation (such as IEEE 802.11 or IEEE 802.16) and therefore continuously searching the best linear amplification to maximize power efficiency at the time that a certain quality of service (BER) in reception is guaranteed. Simulations provided will show the advantages of this multi-LUT configuration, where in front of different channel conditions, linear and efficient amplification (minimum back-off) is achieved at the time that a certain level of BER at reception is ensured. Index terms – Lookup tables (LUT), digital adaptive predistortion, Hammerstein models, adaptive modulation systems, peak to average power ratio (PAPR), bit error rate (BER).Peer Reviewe

Design and implementation of an ETSI-SDR OFDM transmitter with power amplifier linearizer

Satellite radio has attained great popularity because of its wide range of geographical coverage and high signal quality as compared to the terrestrial broadcasts. Most Satellite Digital Radio (SDR) based systems favor multi-carrier transmission schemes, especially, orthogonal frequency division multiplexing (OFDM) transmission because of high data transfer rate and spectral efficiency. It is a challenging task to find a suitable platform that supports fast data rates and superior processing capabilities required for the development and deployment of the new SDR standards. Field programmable gate array (FPGA) devices have the potential to become suitable development platform for such standards. Another challenging factor in SDR systems is the distortion of variable envelope signals used in OFDM transmission by the nonlinear RF power amplifiers (PA) used in the base station transmitters. An attractive option is to use a linearizer that would compensate for the nonlinear effects of the PA. In this research, an OFDM transmitter, according to European Telecommunications Standard Institute (ETSI) SDR Technical Specifications 2007-2008, was designed and implemented on a low-cost Xilinx FPGA platform. A weakly nonlinear PA, operating in the L-band SDR frequency (1.450-1.490GHz), was used for signal transmission. An FPGA-based, low-cost, adaptive linearizer was designed and implemented based on the digital predistortion (DPD) reference design from Xilinx, to correct the distortion effects of the PA on the transmitted signal

High power amplifier pre-distorter based on neural-fuzzy systems for OFDM signals

In this paper, a novel High Power Amplifier (HPA) pre-distorter based on Adaptive Networks - Fuzzy Inference Systems (ANFIS) for Orthogonal Frequency Division Multiplexing (OFDM) signals is proposed and analyzed. Models of Traveling Wave Tube Amplifiers (TWTA) and Solid State Power Amplifiers (SSPA), both memoryless and with memory, have been used for evaluation of the proposed technique. After training, the ANFIS linearizes the HPA response and thus, the obtained signal is extremely similar to the original. An average Error Vector Magnitude (EVM) of 10-6 can be easily obtained with our proposal. As a consequence, the Bit Error Rate (BER) degradation is negligible showing a better performance than what can be achieved with other methods available in the literature. Moreover, the complexity of the proposed scheme is reducedThis work was supported in part by projectsMULTIADAPTIVE (TEC2008-06327-C03-02) and AECI Program of Research Cooperation with MoroccoPublicad

A Joint Linearization/Companding Approach for Improving a CO-OFDM Transmitter

International audience—The joint use of peak-to-average power ratio (PAPR) reduction and linearization via digital predistortion is investigated in this letter, with the view to improve the performances of coherent optical OFDM (CO-OFDM) systems employing a semiconductor optical amplifier (SOA). PAPR reduction is performed via Wang's nonlinear companding transform (WNCT), which has been recently pointed out as a pertinent choice for optical communications, and a Filter Lookup Table (FLUT) scheme is considered for linearizing the transmitter. Experimental results prove the effectiveness of the proposed scheme, as a lower EVM is achieved with respect to system implementations using only PAPR reduction or linearization

Digital predistortion of RF amplifiers using baseband injection for mobile broadband communications

Radio frequency (RF) power amplifiers (PAs) represent the most challenging design parts of wireless transmitters. In order to be more energy efficient, PAs should operate in nonlinear region where they produce distortion that significantly degrades the quality of signal at transmitter’s output. With the aim of reducing this distortion and improve signal quality, digital predistortion (DPD) techniques are widely used. This work focuses on improving the performances of DPDs in modern, next-generation wireless transmitters. A new adaptive DPD based on an iterative injection approach is developed and experimentally verified using a 4G signal. The signal performances at transmitter output are notably improved, while the proposed DPD does not require large digital signal processing memory resources and computational complexity. Moreover, the injection-based DPD theory is extended to be applicable in concurrent dual-band wireless transmitters. A cross-modulation problem specific to concurrent dual-band transmitters is investigated in detail and novel DPD based on simultaneous injection of intermodulation and cross-modulation distortion products is proposed. In order to mitigate distortion compensation limit phenomena and memory effects in highly nonlinear RF PAs, this DPD is further extended and complete generalised DPD system for concurrent dual-band transmitters is developed. It is clearly proved in experiments that the proposed predistorter remarkably improves the in-band and out-of-band performances of both signals. Furthermore, it does not depend on frequency separation between frequency bands and has significantly lower complexity in comparison with previously reported concurrent dual-band DPDs

Energy-Efficient Distributed Estimation by Utilizing a Nonlinear Amplifier

abstract: Distributed estimation uses many inexpensive sensors to compose an accurate estimate of a given parameter. It is frequently implemented using wireless sensor networks. There have been several studies on optimizing power allocation in wireless sensor networks used for distributed estimation, the vast majority of which assume linear radio-frequency amplifiers. Linear amplifiers are inherently inefficient, so in this dissertation nonlinear amplifiers are examined to gain efficiency while operating distributed sensor networks. This research presents a method to boost efficiency by operating the amplifiers in the nonlinear region of operation. Operating amplifiers nonlinearly presents new challenges. First, nonlinear amplifier characteristics change across manufacturing process variation, temperature, operating voltage, and aging. Secondly, the equations conventionally used for estimators and performance expectations in linear amplify-and-forward systems fail. To compensate for the first challenge, predistortion is utilized not to linearize amplifiers but rather to force them to fit a common nonlinear limiting amplifier model close to the inherent amplifier performance. This minimizes the power impact and the training requirements for predistortion. Second, new estimators are required that account for transmitter nonlinearity. This research derives analytically and confirms via simulation new estimators and performance expectation equations for use in nonlinear distributed estimation. An additional complication when operating nonlinear amplifiers in a wireless environment is the influence of varied and potentially unknown channel gains. The impact of these varied gains and both measurement and channel noise sources on estimation performance are analyzed in this paper. Techniques for minimizing the estimate variance are developed. It is shown that optimizing transmitter power allocation to minimize estimate variance for the most-compressed parameter measurement is equivalent to the problem for linear sensors. Finally, a method for operating distributed estimation in a multipath environment is presented that is capable of developing robust estimates for a wide range of Rician K-factors. This dissertation demonstrates that implementing distributed estimation using nonlinear sensors can boost system efficiency and is compatible with existing techniques from the literature for boosting efficiency at the system level via sensor power allocation. Nonlinear transmitters work best when channel gains are known and channel noise and receiver noise levels are low.Dissertation/ThesisPh.D. Electrical Engineering 201

Design and Implementation of a Software Predistorter for amplifier linearization in OFDM-based SDR systems

In modern wireless communication systems, an important role is played by the amplifier in the RF transmitter. It controls the maximum distance covered, the battery consumption for mobile devices, heating, etc. Nowadays RF transmitter has a lot of uses, starting from old FM stations, and arriving, in the recent period, to piloting of drones. Simplifying as much as possible, what this device accomplishes is to convert the baseband signal containing the data to be transmitted into a radio frequency signal able to travel through the ether. This can be done directly, or in two distinct phases before passing to an intermediate frequency (IF). In both cases, the signal after conversion must be amplified with a power amplifier and then transmitted on the channel. This thesis will focus on the amplifier part of the transmitter. In particular, existing predistortion techniques, used to improve the linearity of the power amplifier, and a software, non-real time, predistorter developed for the thesis will be described

Contribution to dimensionality reduction of digital predistorter behavioral models for RF power amplifier linearization

The power efficiency and linearity of radio frequency (RF) power amplifiers (PAs) are critical in wireless communication systems. The main scope of PA designers is to build the RF PAs capable to maintain high efficiency and linearity figures simultaneously. However, these figures are inherently conflicted to each other and system-level solutions based on linearization techniques are required. Digital predistortion (DPD) linearization has become the most widely used solution to mitigate the efficiency versus linearity trade-off. The dimensionality of the DPD model depends on the complexity of the system. It increases significantly in high efficient amplification architectures when considering current wideband and spectrally efficient technologies. Overparametrization may lead to an ill-conditioned least squares (LS) estimation of the DPD coefficients, which is usually solved by employing regularization techniques. However, in order to both reduce the computational complexity and avoid ill-conditioning problems derived from overparametrization, several efforts have been dedicated to investigate dimensionality reduction techniques to reduce the order of the DPD model. This dissertation contributes to the dimensionality reduction of DPD linearizers for RF PAs with emphasis on the identification and adaptation subsystem. In particular, several dynamic model order reduction approaches based on feature extraction techniques are proposed. Thus, the minimum number of relevant DPD coefficients are dynamically selected and estimated in the DPD adaptation subsystem. The number of DPD coefficients is reduced, ensuring a well-conditioned LS estimation while demanding minimum hardware resources. The presented dynamic linearization approaches are evaluated and compared through experimental validation with an envelope tracking PA and a class-J PA The experimental results show similar linearization performance than the conventional LS solution but at lower computational cost.La eficiencia energetica y la linealidad de los amplificadores de potencia (PA) de radiofrecuencia (RF) son fundamentales en los sistemas de comunicacion inalambrica. El principal objetivo a alcanzar en el diserio de amplificadores de radiofrecuencia es lograr simultaneamente elevadas cifras de eficiencia y de linealidad. Sin embargo, estas cifras estan inherentemente en conflicto entre si, y se requieren soluciones a nivel de sistema basadas en tecnicas de linealizacion. La linealizacion mediante predistorsion digital (DPD) se ha convertido en la solucion mas utilizada para mitigar el compromise entre eficiencia y linealidad. La dimension del modelo del predistorsionador DPD depende de la complejidad del sistema, y aumenta significativamente en las arquitecturas de amplificacion de alta eficiencia cuando se consideran los actuales anchos de banda y las tecnologfas espectralmente eficientes. El exceso de parametrizacion puede conducir a una estimacion de los coeficientes DPD, mediante minimos cuadrados (LS), mal condicionada, lo cual generalmente se resuelve empleando tecnicas de regularizacion. Sin embargo, con el fin de reducir la complejidad computacional y evitar dichos problemas de mal acondicionamiento derivados de la sobreparametrizacion, se han dedicado varies esfuerzos para investigar tecnicas de reduccion de dimensionalidad que permitan reducir el orden del modelo del DPD. Esta tesis doctoral contribuye a aportar soluciones para la reduccion de la dimension de los linealizadores DPD para RF PA, centrandose en el subsistema de identificacion y adaptacion. En concrete, se proponen varies enfoques de reduccion de orden del modelo dinamico, basados en tecnicas de extraccion de caracteristicas. El numero minimo de coeficientes DPD relevantes se seleccionan y estiman dinamicamente en el subsistema de adaptacion del DPD, y de este modo la cantidad de coeficientes DPD se reduce, lo cual ademas garantiza una estimacion de LS bien condicionada al tiempo que exige menos recursos de hardware. Las propuestas de linealizacion dinamica presentados en esta tesis se evaluan y comparan mediante validacion experimental con un PA de seguimiento de envolvente y un PA tipo clase J. Los resultados experimentales muestran unos resultados de linealizacion de los PA similares a los obtenidos cuando se em plea la solucion LS convencional, pero con un coste computacional mas reducido.Postprint (published version

Multi look-up table FPGA implementation of an adaptive digital predistorter for linearizing RF power amplifiers with memory effects

This paper presents a hardware implementation of a digital predistorter (DPD) for linearizing RF power amplifiers (PAs) for wideband applications. The proposed predistortion linearizer is based on a nonlinear auto-regressive moving average (NARMA) structure, which can be derived from the NARMA PA behavioral model and then mapped into a set of scalable lookup tables (LUTs). The linearizer takes advantage of its recursive nature to relax the LUT count needed to compensate memory effects in PAs. Experimental support is provided by the implementation of the proposed NARMA DPD in a field-programmable gate-array device to linearize a 170-W peak power PA, validating the recursive DPD NARMA structure for W-CDMA signals and flexible transmission bandwidth scenarios. To the best of the authors’ knowledge, it is the first time that a recursive structure is experimentally validated for DPD purposes. In addition to the results on PA efficiency and linearity, this paper addresses many practical implementation issues related to the use of FPGA in DPD applications, giving an original insight on actual prototyping scenarios. Finally, this study discusses the possibility of further enhancing the overall efficiency by degrading the PA operation mode, provided that DPD may be unavoidable due to the impact of memory effects.Peer Reviewe