On PAPR Reduction of OFDM using Partial Transmit Sequence with Intelligent Optimization Algorithms

In recent time, the demand for multimedia data services over wireless links has grown up rapidly. Orthogonal Frequency Division Multiplexing (OFDM) forms the basis for all 3G and beyond wireless communication standards due to its efficient frequency utilization permitting near ideal data rate and ubiquitous coverage with high mobility. OFDM signals are prone to high peak-to-average-power ratio (PAPR). Unfortunately, the high PAPR inherent to OFDM signal envelopes occasionally drives high power amplifiers (HPAs) to operate in the nonlinear region of their characteristic leading out-of-band radiation, reduction in efficiency of communication system etc. A plethora of research has been devoted to reducing the performance degradation due to the PAPR problem inherent to OFDM systems. Advanced techniques such as partial transmit sequences (PTS) and selected mapping (SLM) have been considered most promising for PAPR reduction. Such techniques are seen to be efficient for distortion-less signal processing but suffer from computational complexity and often requires transmission of extra information in terms of several side information (SI) bits leading to loss in effective data rate. This thesis investigates the PAPR problem using Partial Transmit Sequence (PTS) scheme, where optimization is achieved with evolutionary bio-inspired metaheuristic stochastic algorithms. The phase factor optimization in PTS is used for PAPR reduction. At first, swarm intelligence based Firefly PTS (FF-PTS) algorithm is proposed which delivers improved PAPR performance with reduced searching complexity. Following this, Cuckoo Search based PTS (CS-PTS) technique is presented, which offers good PAPR performance in terms of solution quality and convergence speed. Lastly, Improved Harmony search based PTS (IHS-PTS) is introduced, which provides improved PAPR. The algorithm has simple structure with a very few parameters for larger PTS sub-blocks. The PAPR performance of the proposed technique with different parameters is also verified through extensive computer simulations. Furthermore, complexity analysis of algorithms demonstrates that the proposed schemes offer significant complexity reduction when compared to standard PAPR reduction techniques. Findings have been validated through extensive simulation tests

Evaluasi Penerapan Algoritma Neural Network Sebagai Teknik Reduksi PAPR Pada Sistem OFDM

Pada makalah ini dilakukan evaluasi kinerja algoritma Neural Network sebagai teknik reduksi sistem OFDM.  Hasil simulasi untuk sinyal OFDM dengan jumlah subcarrier sebanyak 64 dan modulasi 16 QAM menunjukkan penerapan algorima NN menghasilkan penurunan nilai PAPR sekitar 5,6 dB dari PAPR sinyal OFDM tanpa reduksi. Juga dibandingkan dengan teknik reduksi PAPR metode Iterative Clipping and Filtering, (ICF), Selective Mapping (SLM) dan Partial Transmit Sequence (PTS). Dari kurva CCDF juga ditunjukkan bahwa metode NN menghasilkan kinerja yang lebih baik dibanding metode digabungkan dengan teknik Iterative Clipping and Filtering, (ICF), Selective Mapping (SLM) dan Partial Transmit Sequence (PTS). Evaluasi di sisi penerima dengan pengamatan nilai bit error rate, penerapan algoritma NN memiliki kinerja yang terbai

Resource Allocation-Based PAPR Analysis in Uplink SCMA-OFDM Systems

Sparse code multiple access (SCMA) is a non-orthogonal multiple access (NOMA) uplink solution that overloads resource elements (RE's) with more than one user. Given the success of orthogonal frequency division multiplexing (OFDM) systems, SCMA will likely be deployed as a multiple access scheme over OFDM, called an SCMA-OFDM system. One of the major challenges with OFDM systems is the high peak-to-average power ratio (PAPR) problem, which is typically studied through the PAPR statistics for a system with a large number of independently modulated sub-carriers (SCs). In the context of SCMA systems, the PAPR problem has been studied before through the SCMA codebook design for certain narrowband scenarios, applicable more for low-rate users. However, we show that for high-rate users in wideband systems, it is more meaningful to study the PAPR statistics. In this paper, we highlight some novel aspects to the PAPR statistics for SCMA-OFDM systems that is different from the vast body of existing PAPR literature in the context of traditional OFDM systems. The main difference lies in the fact that the SCs are not independently modulated in SCMA-OFDM systems. Instead, the SCMA codebook uses multi-dimensional constellations, leading to a statistical dependency between the data carrying SCs. Further, the SCMA codebook dictates that an UL user can only transmit on a subset of the available SCs. We highlight the joint effect of the two major factors that influence the PAPR statistics-the phase bias in the multi-dimensional constellation design along with the resource allocation strategy. The choice of modulation scheme and SC allocation strategy are static configuration options, thus allowing for PAPR reduction opportunities in SCMA-OFDM systems through the setting of static configuration parameters. Compared to the class of PAPR reduction techniques in the OFDM literature that rely on multiple signalling and probabilistic techniques, these gains come with no computational overhead. In this paper, we also examine these PAPR reduction techniques and their applicability to SCMA-OFDM systems

Peak to average power ratio reduction and error control in MIMO-OFDM HARQ System

Currently, multiple-input multiple-output orthogonal frequency division multiplexing (MIMOOFDM) systems underlie crucial wireless communication systems such as commercial 4G and 5G networks, tactical communication, and interoperable Public Safety communications. However, one drawback arising from OFDM modulation is its resulting high peak-to-average power ratio (PAPR). This problem increases with an increase in the number of transmit antennas. In this work, a new hybrid PAPR reduction technique is proposed for space-time block coding (STBC) MIMO-OFDM systems that combine the coding capabilities to PAPR reduction methods, while leveraging the new degree of freedom provided by the presence of multiple transmit chairs (MIMO). In the first part, we presented an extensive literature review of PAPR reduction techniques for OFDM and MIMO-OFDM systems. The work developed a PAPR reduction technique taxonomy, and analyzed the motivations for reducing the PAPR in current communication systems, emphasizing two important motivations such as power savings and coverage gain. In the tax onomy presented here, we include a new category, namely, hybrid techniques. Additionally, we drew a conclusion regarding the importance of hybrid PAPR reduction techniques. In the second part, we studied the effect of forward error correction (FEC) codes on the PAPR for the coded OFDM (COFDM) system. We simulated and compared the CCDF of the PAPR and its relationship with the autocorrelation of the COFDM signal before the inverse fast Fourier transform (IFFT) block. This allows to conclude on the main characteristics of the codes that generate high peaks in the COFDM signal, and therefore, the optimal parameters in order to reduce PAPR. We emphasize our study in FEC codes as linear block codes, and convolutional codes. Finally, we proposed a new hybrid PAPR reduction technique for an STBC MIMO-OFDM system, in which the convolutional code is optimized to avoid PAPR degradation, which also combines successive suboptimal cross-antenna rotation and inversion (SS-CARI) and iterative modified companding and filtering schemes. The new method permits to obtain a significant net gain for the system, i.e., considerable PAPR reduction, bit error rate (BER) gain as compared to the basic MIMO-OFDM system, low complexity, and reduced spectral splatter. The new hybrid technique was extensively evaluated by simulation, and the complementary cumulative distribution function (CCDF), the BER, and the power spectral density (PSD) were compared to the original STBC MIMO-OFDM signal

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

Multidimensional Index Modulation for 5G and Beyond Wireless Networks

This study examines the flexible utilization of existing IM techniques in a comprehensive manner to satisfy the challenging and diverse requirements of 5G and beyond services. After spatial modulation (SM), which transmits information bits through antenna indices, application of IM to orthogonal frequency division multiplexing (OFDM) subcarriers has opened the door for the extension of IM into different dimensions, such as radio frequency (RF) mirrors, time slots, codes, and dispersion matrices. Recent studies have introduced the concept of multidimensional IM by various combinations of one-dimensional IM techniques to provide higher spectral efficiency (SE) and better bit error rate (BER) performance at the expense of higher transmitter (Tx) and receiver (Rx) complexity. Despite the ongoing research on the design of new IM techniques and their implementation challenges, proper use of the available IM techniques to address different requirements of 5G and beyond networks is an open research area in the literature. For this reason, we first provide the dimensional-based categorization of available IM domains and review the existing IM types regarding this categorization. Then, we develop a framework that investigates the efficient utilization of these techniques and establishes a link between the IM schemes and 5G services, namely enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), and ultra-reliable low-latency communication (URLLC). Additionally, this work defines key performance indicators (KPIs) to quantify the advantages and disadvantages of IM techniques in time, frequency, space, and code dimensions. Finally, future recommendations are given regarding the design of flexible IM-based communication systems for 5G and beyond wireless networks.Comment: This work has been submitted to Proceedings of the IEEE for possible publicatio

Single-Frequency Network Terrestrial Broadcasting with 5GNR Numerology

L'abstract è presente nell'allegato / the abstract is in the attachmen

PAPR Reduction Solutions for 5G and Beyond

The latest fifth generation (5G) wireless technology provides improved communication quality compared to earlier generations. The 5G New Radio (NR), specified by the 3rd Generation Partnership Project (3GPP), addresses the modern requirements of the wireless networks and targets improved communication quality in terms of for example peak data rates, latency and reliability. On the other hand, there are still various crucial issues that impact the implementation and energy-efficiency of 5G NR networks and their different deployments. The power-efficiency of transmitter power amplifiers (PAs) is one of these issues. The PA is an important unit of a communication system, which is responsible from amplifying the transmit signal towards the antenna. Reaching high PA power-efficiency is known to be difficult when the transmit waveform has a high peak-to-average power ratio (PAPR). The cyclic prefix (CP)-orthogonal frequencydivision multiplexing (OFDM) that is the main physical-layer waveform of 5G NR, suffers from such high PAPR challenge. There are generally many PAPR reduction methods proposed in the literature, however, many of these have either very notable computational complexity or impose substantial inband distortion. Moreover, 5G NR has new features that require redesigning the PAPR reduction methods. In line with these, the first contribution of this thesis is the novel frequencyselective PAPR reduction concept, where clipping noise is shaped in a frequencyselective manner over the active passband. This concept is in line with the 5G NR, where aggressive frequency-domain multiplexing is considered as an important feature. Utilizing the frequency-selective PAPR reduction enables the realization of the heterogeneous resource utilization within one passband. The second contribution of this thesis is the frequency-selective single-numerology (SN) and mixed-numerology (MN) PAPR reduction methods. The 5G NR targets utilizing different physical resource blocks (PRBs) and bandwidth parts (BWPs) within one passband flexibly. Yet, existing PAPR reduction methods do not exploit these features. Based on this, novel algorithms utilizing PRB and BWP level control of clipping noise are designed to meet error vector magnitude (EVM) limits of the modulations while reducing the PAPR. TheMNallocation has one critical challenge as inter numerology interference (INI) emerges after aggregation of subband signals. Proposed MN PAPR reduction algorithm overcomes this issue by cancelling INI within the PAPR reduction loop, which has not been considered earlier. The third contribution of this thesis is the proposal of two novel non-iterative PAPR reduction methods. First method utilizes the fast-convolution filteredOFDM (FC-F-OFDM) that has excellent spectral containment, and combines it with clipping. Moreover, clipping noise is also allocated to guard bands by filter passband extension (FPE) and clipping noise in out-of-band (OOB) regions is essentially filtered through FC filtering. The second method is the guard-tone reservation (GTR) which is applied to discrete Fourier transform-spread-OFDM (DFT-s-OFDM). Uniquely, GTR estimates the time domain peaks in data symbol domain before inverse fast Fourier transform (IFFT), and uses guard band tones for PAPR reduction. The fourth contribution of the thesis is the design of two novel machine learning (ML) algorithms that improve the drawbacks of frequency-selective PAPRreduction. The first ML algorithm, PAPRer, models the nonlinear relation between the PAPR target and the realized PAPR value. Then, it auto-tunes the optimal PAPR target and this way minimizes the realized PAPR. The second ML algorithm, one-shot clipping-and-filtering (OSCF), solves the complexity problem of iterative clipping and filtering (ICF)-like methods by generating proper approximated clipping noise signal after running only one iteration, leading to very efficient PAPR reduction. Finally, an over-arching contribution of this thesis is the experimental validation of the performance benefits of the proposed methods by considering realistic 5GNR uplink (UL) and downlink (DL) testbeds that include realistic PAs and associated hardware. It is very important to confirm the practical benefits of the proposed methods and, this is realized with the conducted experimental work

Algoritmos para la reducción de los picos de potencia en los sistemas OFDM

La modulación OFDM (Orthogonal Frequency Division Multiplexing) es una técnica de transmisión multiportadora, que debido a sus grandes ventajas se utiliza en numerosos estándares de comunicaciones de banda ancha. Sin embargo, uno de los principales inconvenientes que presenta la modulación OFDM, en el lado transmisor, es la presencia ocasional de grandes picos en su potencia instantánea con respecto a su potencia media, conocido en la literatura como el problema de la PAPR (Peak-to-Average Power Ratio) de los sistemas OFDM. Al pasar la señal con PAPR elevada por el amplificador de alta potencia (HPA - High Power Amplifier ) se produce saturación del dispositivo, provocando radiación fuera de banda, que afecta a las bandas adyacentes, y radiación dentro de banda, que produce rotación, atenuación y desplazamiento de la señal, provocando un incremento en la tasa de error de bit (BER - Bit Error Rate). Para contrarrestar estos efectos, se debe reducir la PAPR de la senñal OFDM transmitida con algún tipo de manipulación en la señal. Una de las técnicas de reducción de la PAPR más prometedoras es la técnica CE (Constellation Extension), que mueve inteligentemente ciertos puntos externos de la constelación del símbolo OFDM en el dominio de la frecuencia, de tal forma que la señal en el dominio del tiempo tenga una PAPR menor. La extensión de la constelación de esta forma no afecta a la distancia mínima de la constelación y, consecuentemente, no se experimenta degradación en la BER del sistema. Además, no hay pérdida en la tasa de transmisión de datos porque no se requiere la transmisión de información de control. Sin embargo, se introduce un incremento de la energía por símbolo. El objetivo principal de esta Tesis es proponer varios algoritmos de reducción de la PAPR, basados en técnicas CE. Por un lado, como primer objetivo (capítulo 4) se presentan algoritmos eficientes en energía, que se consiguen al combinar adecuadamente un esquema CE, basado en métrica, con secuencias piloto. Dicha combinación deja tres posibles arquitecturas de implementación dependiendo del orden en que se usa cada algoritmo. Se determina la arquitectura que proporciona un compromiso adecuado entre reducción de la PAPR y complejidad, esta última medida en términos del número de ciclos adicionales del procesador (que se traducen en energía consumida) que se requieren para procesar la reducción de la PAPR. Además, se demuestra que las tres arquitecturas propuestas demandan una energía por símbolo menor que otras técnicas CE, si se insertan adecuadamente las secuencias piloto en el símbolo OFDM Por otro lado, como segundo objetivo se presentan los esquemas de reducción de la PAPR, basados en técnicas CE, que se formulan como problemas de optimización (capítulo 5). Se propone una solución óptima, en térrminos de reducción de la PAPR, llamada algoritmo GBDCE (Generalized Benders Decomposition for Constellation Extension), el cual se plantea como un problema no lineal mixto-entero (MINLP - Mixed Integer Non-Linear Programming) y que sirve como cota inferior de referencia para comparar con otras técnicas CE. Además, se proponen los algoritmos subóptimos: BBCE (Branch-and-Bound for Constellation Extension) que se formula como un problema de programación entera, y DCE (Dynamic Constellation Extension) que combina un esquema BBCE con un algoritmo basado en métrica. El objetivo de ambos algoritmos subóptimos es reducir la complejidad del algoritmo óptimo.OFDM (Orthogonal Frequency Division Multiplexing) modulation is a multicarrier transmission technique that, due to its important advantages, has been widely used in many wideband communication standards. However, one of the major drawbacks of the transmitted OFDM signal is the infrequent high peak power with respect to average power, which is known in the literature as the PAPR (Peak-to-Average Power Ratio) problem in OFDM systems. When the signal with high PAPR passes through an HPA (High Power Amplifier), it suffers from saturation, which causes both out-of-band radiation, that affects the adjacent channels, and in-band radiation, which produces rotation, attenuation and shift of the signal, that increases the BER (Bit Error Rate). In order to address the PAPR problem, the OFDM signal must be manipulated. One of the most promising PAPR techniques is CE (Constellation Extension), that intelligently moves certain outer constellation points of the OFDM signal in the frequency domain, in such way that the OFDM signal in the time domain has a lower PAPR. The constellation extension in this way does not affect the minimum distance of the constellation, and BER degradation is not consequently experienced by the system. Moreover, there is no user's data rate loss because these methods do not require side information. Nevertheless, they introduce an increase in the energy per symbol. The main aim of this Thesis is to propose several PAPR reduction algorithms, based on CE techniques. On one side, the first objective (chapter 4) is to present an energy efficient algorithm, which consists in the adequate combination of a metric-based CE technique with pilot sequences. The combination allows three possible implementation architectures, depending on the order of use of the algorithms. It has been determined the architecture that provides an adequate trade-o_ between PAPR reduction and complexity, the latter measured in number of additional CPU cycles (which translates into energy consumption) needed to perform the PAPR reduction. Moreover, the three proposed architectures require less energy per symbol than other CE techniques, if the pilot sequences are appropriately inserted in the OFDM symbol. On the other side, the second objective is to present CE based algorithms, which are formulated as an optimization problem (chapter 5). The optimal solution, in terms of PAPR reduction is called GBDCE (Generalized Benders Decomposition for Constellation Extension) algorithm. GBDCE is formulated as a MINLP (Mixed Integer Non-Linear Programming) problem, and it turns out to be a lower bound for CE schemes and provides a benchmark to compare with other CE technique. Moreover, two suboptimal algorithms are proposed: BBCE (Branch-and-Bound for Constellation Extension), which is formulated as Integer Programming, and DCE (Dynamic Constellation Extension), that combines a BBCE scheme with a metric-based algorithm. The objective of both suboptimal algorithms is to reduce the GBDCE complexity.Financiación de la Secretaría de Educación Superior, Ciencia, Tecnología e Innovación (SENESCYT) de Ecuador, Fundación Carolina (España) y del Proyecto Nacional de España GRE3N-SYST (TEC2011-29006-C03-03).Doctor en Programa Oficial de Posgrado en Multimedia y ComunicacionesPresidente: Ana García Armada.- Secretario: Sancho Salcedo Sanz.- Vocal: Santiago Zazo Bell

Rede neural de função de base radial de transmissão de fase complexa para decodificação mimo-ofdm massiva

Orientador: Dalton Soares ArantesDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: Os esquemas de transmissão MIMO (multiple-input multiple-output) se tornaram as técnicas escolhidas para aumentar a eficiência espectral em áreas congestionadas. No entanto, o projeto de receptores de baixo custo para canais MIMO continua sendo uma tarefa desafiadora. O detector de máxima verossimilhança pode atingir um desempenho excelente, geralmente o melhor, mas sua complexidade computacional é um fator limitante na implementação prática. Neste trabalho, um novo esquema MIMO é proposto com um algoritmo de decodificação pratico e viável baseado na PTRBFNN (rede neural de função de base radial de transmitância de fase). O esquema proposto atinge uma complexidade computacional bastante competitiva em relação à decodificação de Máxima Verossimilhança, aumentando substancialmente a aplicabilidade do algoritmo. Os resultados da simulação são apresentados para MIMO-OFDM sob desvanecimento Rayleigh em canais sem fio, para que uma comparação de desempenho justa com outras técnicas de referência possa ser estabelecidaAbstract: Multi-Input Multi-Output (MIMO) transmission schemes have become the techniques of choice for increasing spectral efficiency in bandwidth-congested areas. However, the design of cost-effective receivers for MIMO channels remains a challenging task. The maximum likelihood detector can achieve excellent performance, usually the best, but its computational complexity is a limiting factor in practical implementation. In this work, a new MIMO scheme is proposed with a practically feasible decoding algorithm based on the phase transmittance radial basis function neural network (PTRBFNN). The proposed scheme achieves a computational complexity that is quite competitive relative to the Maximum Likelihood decoding, thus substantially increasing the applicability of the algorithm. Simulation results are presented for MIMO-OFDM under wireless Rayleigh fading channels so that a fair performance comparison with other reference techniques can be establishedMestradoTelecomunicações e TelemáticaMestre em Engenharia Elétrica132545/2019-5CNP