A Hybrid Segmentation Pattern of Partial Transmission in Computer Networks to Reduce the Complexity Level

Partial transmission sequence (PTS) is seen as a related project in the framework of the Orthogonal Frequency Division ‎Multiplexing (OFDM) to suppress the medium to high Peak-to-Average Power Ratio problem. The PTS chart data is based on dividing the back into subdivisions and their weight by combining step-by-step factors. Despite the fact that PTS can reduce the high specifications. The Computational Complexity Level (CC) limits the scope of application to match PTS use with ground applications. In PTS, there are three main distribution schemes. Interleaving projects (IL-PTS), arbitrary and alternate (PR-PTS) and Ad-PTS. In this paper, another algorithm called the Hybrid Pseudo-Random and Interleaving Cosine Wave Shape ‎‎(H-PRC-PTS) is presented and the PR-PTS equilibrium is established by stabilizing the cousin waveform between languages (S-IL-C- PTS), which was suggested in the previous work. The results showed that the proposed algorithm could reduce the validity of PAPR as a PR-PTS scheme, although the CC level was significantly reduced

Communication Subsystems for Emerging Wireless Technologies

The paper describes a multi-disciplinary design of modern communication systems. The design starts with the analysis of a system in order to define requirements on its individual components. The design exploits proper models of communication channels to adapt the systems to expected transmission conditions. Input filtering of signals both in the frequency domain and in the spatial domain is ensured by a properly designed antenna. Further signal processing (amplification and further filtering) is done by electronics circuits. Finally, signal processing techniques are applied to yield information about current properties of frequency spectrum and to distribute the transmission over free subcarrier channels

Intelligent Processing in Wireless Communications Using Particle Swarm Based Methods

There are a lot of optimization needs in the research and design of wireless communica- tion systems. Many of these optimization problems are Nondeterministic Polynomial (NP) hard problems and could not be solved well. Many of other non-NP-hard optimization problems are combinatorial and do not have satisfying solutions either. This dissertation presents a series of Particle Swarm Optimization (PSO) based search and optimization algorithms that solve open research and design problems in wireless communications. These problems are either avoided or solved approximately before. PSO is a bottom-up approach for optimization problems. It imposes no conditions on the underlying problem. Its simple formulation makes it easy to implement, apply, extend and hybridize. The algorithm uses simple operators like adders, and multipliers to travel through the search space and the process requires just five simple steps. PSO is also easy to control because it has limited number of parameters and is less sensitive to parameters than other swarm intelligence algorithms. It is not dependent on initial points and converges very fast. Four types of PSO based approaches are proposed targeting four different kinds of problems in wireless communications. First, we use binary PSO and continuous PSO together to find optimal compositions of Gaussian derivative pulses to form several UWB pulses that not only comply with the FCC spectrum mask, but also best exploit the avail- able spectrum and power. Second, three different PSO based algorithms are developed to solve the NLOS/LOS channel differentiation, NLOS range error mitigation and multilateration problems respectively. Third, a PSO based search method is proposed to find optimal orthogonal code sets to reduce the inter carrier interference effects in an frequency redundant OFDM system. Fourth, a PSO based phase optimization technique is proposed in reducing the PAPR of an frequency redundant OFDM system. The PSO based approaches are compared with other canonical solutions for these communication problems and showed superior performance in many aspects. which are confirmed by analysis and simulation results provided respectively. Open questions and future Open questions and future works for the dissertation are proposed to serve as a guide for the future research efforts

Optimización de problemas de varios objetivos desde un enfoque de eficiencia energética aplicado a redes celulares heterogéneas 5G usando un marco de conmutación de celdas pequeñas

This Ph.D. dissertation addresses the Many-Objective Optimization Problem (MaOP) study to reduce the inter-cell interference and the power consumption for realistic Centralized, Collaborative, Cloud, and Clean Radio Access Networks (C-RANs). It uses the Cell Switch-Off (CSO) scheme to switch-off/on Remote Radio Units (RRUs) and the Coordinated Scheduling (CS) technique to allocate resource blocks smartly. The EF1-NSGA-III (It is a variation of the NSGA-III algorithm that uses the front 1 to find extreme points at the normalization procedure extended in this thesis) algorithm is employed to solve a proposed Many-Objective Optimization Problem (MaOP). It is composed of four objective functions, four constraints, and two decision variables. However, the above problem is redefined to have three objective functions to see the performance comparison between the NSGA-II and EF1-NSGA-III algorithms. The OpenAirInterface (OAI) platform is used to evaluate and validate the performance of an indoor coverage system because most of the user-end equipment of next-generation cellular networks will be in an indoor environment. It constitutes the fastest growing 5G open-source platform that implements 3GPP technology on general-purpose computers, fast Ethernet transport ports, and Commercial-Off-The-Shelf (COTS) software-defined radio hardware. This document is composed of five contributions. The first one is a survey about testbed, emulators, and simulators for 4G/5G cellular networks. The second one is the extension of the KanGAL's NSGA-II code to implement the EF1-NSGA-III, adaptive EF1-NSGA-III (A-EF1-NSGA-III), and efficient adaptive EF1-NSGA-III (A$^2$-EF1-NSGA-III). They support up to 10 objective functions, manage real, integer, and binary decision variables, and many constraints. The above algorithms outperform other works in terms of the Inverted Generational Distance (IGD) metric. The third contribution is the implementation of real-time emulation methodologies for C-RANs using a frequency domain representation in OAI. It improves the average computation time 10-fold compared to the time domain without using Radio Frequency hardware and avoids their uncertainties. The fourth one is the implementation of the Coordination Scheduling (CS) technique as a proof-of-concept to validate the advantages of frequency domain methodologies and to allocate resource blocks dynamically among RRUs. Finally, a many-objective optimization problem is defined and solved with evolutionary algorithms where diversity is managed based on crowded-distance and reference points to reduce the power consumption for C-RANs. The solutions obtained are considered to control the scheduling task at the Radio Cloud Center (RCC) and to switch RRUs.Este disertación aborda el estudio del problema de optimización de varios objetivos (MaOP) para reducir la interferencia entre células y el consumo de energía para redes de acceso de radio en tiempo real, colaborativas, en la nube y limpias (C-RAN). Utiliza el esquema de conmutacion de celdas (CSO) para apagar / encender unidades de radio remotas (RRU) y la técnica de programación coordinada (CS) para asignar bloques de recursos de manera inteligente. El algoritmo EF1-NSGA-III (es una variación del algoritmo NSGA-III que usa el primer frente de pareto para encontrar puntos extremos en el procedimiento de normalización extendido en esta tesis) se utiliza para resolver un problema de optimización de varios objetivos (MaOP) propuesto. Se compone de cuatro funciones objetivos, cuatro restricciones y dos variables de decisión. Sin embargo, el problema anterior se redefine para tener tres funciones objetivas para ver la comparación de rendimiento entre los algoritmos NSGA-II y EF1-NSGA-III. La plataforma OpenAirInterface (OAI) se utiliza para evaluar y validar el rendimiento de un sistema de cobertura en interiores porque la mayoría del equipos móviles de las redes celulares de próxima generación estarán en un entorno interior. Ella constituye la plataforma de código abierto 5G de más rápido crecimiento que implementa la tecnología 3GPP en computadoras de uso general, puertos de transporte Ethernet rápidos y hardware de radio definido por software comercial (COTS). Este documento se compone de cinco contribuciones. La primera es una estudio sobre banco de pruebas, emuladores y simuladores para redes celulares 4G / 5G. El segundo es la extensión del código NSGA-II de KanGAL para implementar EF1-NSGA-III, EF1-NSGA-III adaptativo (A-EF1-NSGA-III) y EF1-NSGA-III adaptativo eficiente (A $^ 2$ -EF1-NSGA-III). Admiten hasta 10 funciones objetivas, gestionan variables de decisión reales, enteras y binarias, y muchas restricciones. Los algoritmos anteriores superan a otros trabajos en términos de la métrica de distancia generacional invertida (IGD). La tercera contribución es la implementación de metodologías de emulación en tiempo real para C-RAN utilizando una representación de dominio de frecuencia en OAI. Mejora el tiempo de cálculo promedio 10 veces en comparación con el dominio del tiempo sin usar hardware de radiofrecuencia y evita sus incertidumbres. El cuarto es la implementación de la técnica de Programación de Coordinación (CS) como prueba de concepto para validar las ventajas de las metodologías de dominio de frecuencia y asignar bloques de recursos dinámicamente entre las RRU. Finalmente, un problema de optimización de muchos objetivos se define y resuelve con algoritmos evolutivos en los que la diversidad se gestiona en función de la distancia de crouding y los puntos de referencia para reducir el consumo de energía de las C-RAN. Las soluciones obtenidas controlan la tarea de programación en Radio Cloud Center (RCC) y conmutan las RRU.Proyecto personal: Redes celulares de próxima generaciónDoctorad

Intercarrier Interference Suppression for the OFDM Systems in Time-Varying Multipath Fading Channels

Due to its spectral efficiency and robustness over the multipath channels, orthogonal frequency division multiplexing (OFDM) has served as one of the major modulation schemes for the modern communication systems. In the future, the wireless OFDM systems are expected to operate at high carrier-frequencies, high speed and high throughput mobile reception, where the fasting time-varying fading channels are encountered. The channel variation destroys the orthogonality among the subcarriers and leads to the intercarrier interference (ICI). ICI poses a significant limitation to the wireless OFDM systems. The aim of this dissertation is to find an efficient method of providing reliable communication using OFDM in the fast time-varying fading channel scenarios. First, we investigate the OFDM performance in the situation of time-varying mobile channels in the presence of multiple Doppler frequency shifts. A new mathematical framework of the ICI effect is derived. The simulation results show that ICI induces an irreducible error probability floor, which in proportional to the Doppler frequency shifts. Furthermore, it is observed that ICI power arises from a few adjacent subcarriers. This observation motivates us to design the low-complexity Q-tap equalizers, namely, Minimum Mean Square Error (MMSE) linear equalizer and Decision Feedback (DF) non-linear equalizer to mitigate the ICI. Simulation results show that both Q-tap equalizers can improve the system performance in the sense of symbol error rate (SER). To employ these equalizers, the channel state information is also required. In this dissertation, we also design a pilot-aided channel estimation via Wiener filtering for a time-varying Wide-sense Stationary Uncorrelated Scatterers (WSSUS) channel model. The channel estimator utilizes that channel statistical properties. Our proposed low-complexity ICI suppression scheme, which incorporates the Q-tap equalizer with our proposed channel estimator, can significantly improve the performance of the OFDM systems in a fast time-varying fading channels. At the last part of the dissertation, an alternative ICI mitigation approach, which is based on the ICI self-cancellation coding, is also discussed. The EM-based approach, which solves the phase and amplitude ambiguities associated with this approach, is also introduced

A Survey on Reservoir Computing and its Interdisciplinary Applications Beyond Traditional Machine Learning

Reservoir computing (RC), first applied to temporal signal processing, is a recurrent neural network in which neurons are randomly connected. Once initialized, the connection strengths remain unchanged. Such a simple structure turns RC into a non-linear dynamical system that maps low-dimensional inputs into a high-dimensional space. The model's rich dynamics, linear separability, and memory capacity then enable a simple linear readout to generate adequate responses for various applications. RC spans areas far beyond machine learning, since it has been shown that the complex dynamics can be realized in various physical hardware implementations and biological devices. This yields greater flexibility and shorter computation time. Moreover, the neuronal responses triggered by the model's dynamics shed light on understanding brain mechanisms that also exploit similar dynamical processes. While the literature on RC is vast and fragmented, here we conduct a unified review of RC's recent developments from machine learning to physics, biology, and neuroscience. We first review the early RC models, and then survey the state-of-the-art models and their applications. We further introduce studies on modeling the brain's mechanisms by RC. Finally, we offer new perspectives on RC development, including reservoir design, coding frameworks unification, physical RC implementations, and interaction between RC, cognitive neuroscience and evolution.Comment: 51 pages, 19 figures, IEEE Acces

OFDM based air interfaces for future mobile satellite systems

This thesis considers the performance of OFDM in a non-linear satellite channel and mechanisms for overcoming the degradations resulting from the high PAPR in the OFDM signal in the specific satellite architecture. It was motivated by new S-DMB applications but its results are applicable to any OFDM system via satellites. Despite many advantages of OFDM, higher PAPR is a major drawback. OFDM signals are therefore very sensitive to non-linear distortion introduced by the power amplifiers and thus, significantly reduce the power efficiency of the system, which is already crucial to satellite system economics. Simple power amplifier back-off to cope with high OFDM PAPR is not possible. Two transmitter based techniques have been considered: PAPR reduction and amplifier linearization.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Journal of Telecommunications and Information Technology, 2011, nr 4

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