RF Power Amplifier Linearization in Professional Mobile Radio Communications Using Artificial Neural Networks

This paper is focused on the linearization of the radio frequency power amplifier of a professional digital handheld by means of an artificial neural network. The simplicity of the neural network that is used, together with the fact that a feedback path is unnecessary, makes this solution ideal to reduce both the cost of a handheld and its hardware complexity, while fully maintaining its performance. A compensation system is also needed to keep the linearization characteristics of the neural network stable against frequency, temperature, and voltage variations. The whole solution that comprises both the neural network and the compensation system has been implemented in the digital signal processor of a real handheld and afterward fully tested. It has proved to be satisfactory to meet the telecommunication standard requirements in all frequency, temperature, and voltage ranges under consideration while efficient to lower the computational cost of the handheld and to make its internal hardware simpler in comparison with other traditional linearization techniques. The results obtained demonstrate that a neural network can be used to linearize the power amplifiers that are used in transmitters of telecommunication equipment, leading to a significant reduction of both their hardware cost and complexity

Numerical Analysis of Modeling Based on Improved Elman Neural Network

A modeling based on the improved Elman neural network (IENN) is proposed to analyze the nonlinear circuits with the memory effect. The hidden layer neurons are activated by a group of Chebyshev orthogonal basis functions instead of sigmoid functions in this model. The error curves of the sum of squared error (SSE) varying with the number of hidden neurons and the iteration step are studied to determine the number of the hidden layer neurons. Simulation results of the half-bridge class-D power amplifier (CDPA) with two-tone signal and broadband signals as input have shown that the proposed behavioral modeling can reconstruct the system of CDPAs accurately and depict the memory effect of CDPAs well. Compared with Volterra-Laguerre (VL) model, Chebyshev neural network (CNN) model, and basic Elman neural network (BENN) model, the proposed model has better performance

Linealización de amplificadores de radiofrecuencia con redes neuronales

Linealización de Amplificadores de Radiofrecuencia con Redes Neuronales:En está tesis doctoral se aborda la linealización de amplificadores de Radiofrecuencia en profundidad.En primer lugar se lleva a cabo una descripción detallada de los diversos sistemas de linealización de amplificadores de radiofrecuencia existentes en la actualidad.Posteriormente se lleva a cabo una minuciosa descripción de la modulación de telecomunicaciones TETRA, sobre la cual va a implementarse el sistema de linealización del amplificador de radiofrecuencia.A continuación se selecciona la tecnología del amplificador de Radiofrecuencia, llevando a cabo un riguroso análisis de las tres tecnologías más importantes (LDMOS, GaN y GaAs) y demostrando las principales ventajas de la solución escogida.Posteriormente, se implementa un sistema de linealización basado en redes neuronales, capaz de linealizar el amplificador de Radiofrecuencia seleccionado, de forma que se cumplan los estándares de telecomunicaciones internacionales para la modulación TETRA y consiguiendo que la complejidad del sistema sea la menor posible, de cara a poder ser implementado empleando los mínimos recursos computacionales y con el menor coste económico posible.Por último se lleva a cabo la implementación física real de la solución completa en un terminal portátil de telecomunicaciones, obteniendo unos excelentes resultados en cuanto a prestaciones y ahorro económico y de recursos computacionales de esta solución respecto a las existentes en el mercado hasta la fecha.<br /

Imaging Sensors and Applications

In past decades, various sensor technologies have been used in all areas of our lives, thus improving our quality of life. In particular, imaging sensors have been widely applied in the development of various imaging approaches such as optical imaging, ultrasound imaging, X-ray imaging, and nuclear imaging, and contributed to achieve high sensitivity, miniaturization, and real-time imaging. These advanced image sensing technologies play an important role not only in the medical field but also in the industrial field. This Special Issue covers broad topics on imaging sensors and applications. The scope range of imaging sensors can be extended to novel imaging sensors and diverse imaging systems, including hardware and software advancements. Additionally, biomedical and nondestructive sensing applications are welcome

1-D broadside-radiating leaky-wave antenna based on a numerically synthesized impedance surface

A newly-developed deterministic numerical technique for the automated design of metasurface antennas is applied here for the first time to the design of a 1-D printed Leaky-Wave Antenna (LWA) for broadside radiation. The surface impedance synthesis process does not require any a priori knowledge on the impedance pattern, and starts from a mask constraint on the desired far-field and practical bounds on the unit cell impedance values. The designed reactance surface for broadside radiation exhibits a non conventional patterning; this highlights the merit of using an automated design process for a design well known to be challenging for analytical methods. The antenna is physically implemented with an array of metal strips with varying gap widths and simulation results show very good agreement with the predicted performance

Beam scanning by liquid-crystal biasing in a modified SIW structure

A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

Optical Wireless Data Center Networks

Bandwidth and computation-intensive Big Data applications in disciplines like social media, bio- and nano-informatics, Internet-of-Things (IoT), and real-time analytics, are pushing existing access and core (backbone) networks as well as Data Center Networks (DCNs) to their limits. Next generation DCNs must support continuously increasing network traffic while satisfying minimum performance requirements of latency, reliability, flexibility and scalability. Therefore, a larger number of cables (i.e., copper-cables and fiber optics) may be required in conventional wired DCNs. In addition to limiting the possible topologies, large number of cables may result into design and development problems related to wire ducting and maintenance, heat dissipation, and power consumption. To address the cabling complexity in wired DCNs, we propose OWCells, a class of optical wireless cellular data center network architectures in which fixed line of sight (LOS) optical wireless communication (OWC) links are used to connect the racks arranged in regular polygonal topologies. We present the OWCell DCN architecture, develop its theoretical underpinnings, and investigate routing protocols and OWC transceiver design. To realize a fully wireless DCN, servers in racks must also be connected using OWC links. There is, however, a difficulty of connecting multiple adjacent network components, such as servers in a rack, using point-to-point LOS links. To overcome this problem, we propose and validate the feasibility of an FSO-Bus to connect multiple adjacent network components using NLOS point-to-point OWC links. Finally, to complete the design of the OWC transceiver, we develop a new class of strictly and rearrangeably non-blocking multicast optical switches in which multicast is performed efficiently at the physical optical (lower) layer rather than upper layers (e.g., application layer). Advisors: Jitender S. Deogun and Dennis R. Alexande

High spectral efficiency transmission using optical frequency combs

Modern long-haul optical communication systems transmit data on all available single-mode fiber dimensions, time, polarization, wavelength, phase and amplitude. Powerful digital signal processing and forward error correction has pushed the per-channel throughput towards its theoretical limits and the bandwidth is limited by the erbium-doped fiber amplifiers. Maximizing the spectral efficiency (SE), i.e. the throughput normalized to bandwidth, is therefore of indisputable importance. Even more so in optical networks as large routing guard-bands drastically reduce the SE of traditional WDM systems. Flex-grid networks with optical superchannels can overcome this limitation. Superchannels consist of multiple tightly packed WDM channels routed as a unit. A comb-based superchannel is formed by encoding independent information onto lines from an optical frequency comb, a multi-wavelength light source fully determined by its center frequency and line spacing. This thesis studies the generation, transmission and detection of comb-based superchannels. Focus is on profiting from unique frequency comb properties to realize systems with capabilities beyond that of conventional systems using arrays of independent lasers. Digital, analog and optical processing schemes are proposed, and combined, to increase the system SE. Superchannel modulation is investigated and a scheme capable of encoding independent information onto the lines from a frequency comb in a single waveguide structure is demonstrated. By combining overhead-optimized pilot-based DSP with a 22GHz-spaced soliton microcomb, superchannel transmission with record SE for distances up to 3000km is realized, closing the performance gap between chip-scale and bulk-optic combs in optical communications. The use of two optical pilot tones (PTs) to phase-lock a transmitter and receiver comb pair is studied, realizing self-homodyne detection of a 50x20Gbaud PM-64QAM superchannel with 4% pilot overhead. The PT gains are furthermore analyzed and a complexity-performance trade-off using a single PT and low complexity DSP is proposed. The scheme is used to demonstrate 12bits/s/Hz SE over the full C-band using 3x50xGBaud PM-256QAM superchannels and DSP-complexity reduction at distances exceeding 1000km is shown. Finally, a comb-enabled multi-channel joint equalization scheme capable of mitigating inter-channel crosstalk and thereby minimizing the SE loss from spectral guard bands is demonstrated