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

A reduced-CP approach to SC/FDE block transmission for broadband wireless communications

For conventional cyclic prefix (CP)-assisted single-carrier/frequency-domain equalization (SC/FDE) implementations, as well as for orthogonal frequency-division multiplexing (OFDM) implementations, the CP length is known to be selected on the basis of the expected maximum delay spread. Next, the data block size can be chosen to be large enough to minimize the CP overhead, yet small enough to make the channel variation over the block negligible. This paper considers the possibility of reducing the overall CP assistance, when transmitting sequences of SC blocks, while avoiding an excessively long fast Fourier transform window for FDE purposes and keeping good FDE performances through low-complexity, noniterative receiver techniques. These techniques, which take advantage of specially designed frame structures, rely on a basic algorithm for decision-directed correction (DDC) of the FDE inputs when the CP is not long enough to cope with the time-dispersive channel effects. More specifically, we present and evaluate a novel class of reduced-CP SC/FDE schemes, which takes advantage of a special frame structure for replacing "useless" CP redundancy by fully useful channel coding redundancy, with the help of the DDC algorithm. When using the DDC-FDE technique with these especially designed frame structures, the impact of previous decisions, which are not error-free, is shown to be rather small, thereby allowing a power-efficiency advantage (in addition to the obvious bandwidth-efficiency advantage) over conventional block transmission implementations under full-length CP. Additionally, the DDC algorithm is also shown to be useful to improve the power efficiency of these conventional implementations.Fundação para a Ciencia e Tecnologia (FCT), Centro de Análise e processamento de Sinais (CAPS

Implementação de códigos LDPC em OFDM e SC-FDE

Os desenvolvimentos dos sistemas de comunicação sem fios apontam para transmissões de alta velocidade e alta qualidade de serviço com um uso eficiente de energia. Eficiência espectral pode ser obtida por modulações multinível, enquanto que melhorias na eficiência de potência podem ser proporcionadas pelo uso de códigos corretores de erros. Os códigos Low-Density Parity-Check (LDPC), devido ao seu desempenho próximo do limite de Shannon e baixa complexidade na implementação e descodificação são apropriados para futuros sistemas de comunicações sem fios. Por outro lado, o uso de modulações multinível acarreta limitações na amplificação. Contudo, uma amplificação eficiente pode ser assegurada por estruturas de transmissão onde as modulações multinível são decompostas em submodulações com envolvente constante que podem ser amplificadas por amplificadores não lineares a operar na zona de saturação. Neste tipo de estruturas surgem desvios de fase e ganho, produzindo distorções na constelação resultante da soma de todos os sinais amplificados. O trabalho foca-se no uso dos códigos LDPC em esquemas multiportadora e monoportadora, com especial ênfase na performance de uma equalização iterativa implementada no domínio da frequência por um Iterative Block-Decision Feedback Equalizer (IB-DFE). São analisados aspectos como o impacto do número de iterações no processo de descodificação dentro das iterações do processo de equalização. Os códigos LDPC também serão utilizados para compensar os desvios de fase em recetores iterativos para sistemas baseados em transmissores com vários ramos de amplificação. É feito um estudo sobre o modo como estes códigos podem aumentar a tolerância a erros de fase que incluí uma análise da complexidade e um algoritmo para estimação dos desequilíbrios de fase

Master of Science

thesisFully integrated, implantable, and wireless neural interface systems typically re-quire a forward data link in addition to the telemetry link that transmits data from the chip. One popular way to create this forward data link is to amplitude modulate the magnetic fi eld of the inductive link that provides the device with wireless power. However, the limitations of these channels when loaded with a recti fier and amplitude modulated have not previously been characterized, and this lack of understanding caused previous versions of the Integrated Neural Interface (INI) to have forward data communication issues, which needed to be corrected for the next generation of the device, INIR8. This thesis first develops an analytical method of characterizing this sort of wireless channel. It then shows measurement data that verifies the validity of the model in the desired region of operation. The available bandwidth as determined by this analytical method, and confirmed by simulation, is insufficient for many applications. Therefore, the next subject of this thesis is to increase the data rate beyond what the bandwidth of the system can intrinsically support by using an equalization technique. This technique is shown to support very robust data recovery under a variety of operating conditions and to data rates much higher than otherwise possible. Another way to improve the reliability of data recovery is to develop a robust digital control system with error detection capabilities. This was done for INIR8, and works very reliably. The end result of this eff ort is a very robust forward data communication in INIR8, as well as a new analytical method for characterizing inductively coupled channels with certain loads and modulation techniques

Advanced Modulation and Coding Technology Conference

The objectives, approach, and status of all current LeRC-sponsored industry contracts and university grants are presented. The following topics are covered: (1) the LeRC Space Communications Program, and Advanced Modulation and Coding Projects; (2) the status of four contracts for development of proof-of-concept modems; (3) modulation and coding work done under three university grants, two small business innovation research contracts, and two demonstration model hardware development contracts; and (4) technology needs and opportunities for future missions

Communications protocols for wireless sensor networks in perturbed environment

This thesis is mainly in the Smart Grid (SG) domain. SGs improve the safety of electrical networks and allow a more adapted use of electricity storage, available in a limited way. SGs also increase overall energy efficiency by reducing peak consumption. The use of this technology is the most appropriate solution because it allows more efficient energy management. In this context, manufacturers such as Hydro-Quebec deploy sensor networks in the nerve centers to control major equipment. To reduce deployment costs and cabling complexity, the option of a wireless sensor network seems the most obvious solution. However, deploying a sensor network requires in-depth knowledge of the environment. High voltages substations are strategic points in the power grid and generate impulse noise that can degrade the performance of wireless communications. The works in this thesis are focused on the development of high performance communication protocols for the profoundly disturbed environments. For this purpose, we have proposed an approach based on the concatenation of rank metric and convolutional coding with orthogonal frequency division multiplexing. This technique is very efficient in reducing the bursty nature of impulsive noise while having a quite low level of complexity. Another solution based on a multi-antenna system is also designed. We have proposed a cooperative closed-loop coded MIMO system based on rank metric code and max−dmin precoder. The second technique is also an optimal solution for both improving the reliability of the system and energy saving in wireless sensor networks