Performance optimization of a UWB-based network for safety-critical avionics

To reduce the aircraft weight and maintenance costs while guaranteeing system performance and reliability, an alternative avionic communication architecture based on Ultra Wide Band (UWB) and TDMA protocol is proposed to replace the back-up part of safety-critical avionics network. The analysis and performance optimization of such a proposal is tackled as follows. First, appropriate system modeling and timing analysis, using Network Calculus and Integer Linear Programing (ILP) approach, are provided to evaluate the end-to-end delays and verify system predictability. Then, an optimization approach to find the optimal TDMA cycle duration, which minimizes the end-to-end delays, is proposed. Finally, the efficiency of our proposal to enhance the system performance is validated through a realistic avionic case study

Timing Analysis of TDMA-based Networks using Network Calculus and Integer Linear Programming

For distributed safety-critical systems, such as avionics and automotive, shared networks represent a bottleneck for timing predictability, a key issue to fulfill certification requirements. To control interferences on such shared resources and guarantee bounded delays, the Time Division Multiple Access (TDMA) protocol is considered as one of the most interesting arbitration protocols due to its deterministic timing behavior and fault-tolerance features. This paper addresses the problem of computing the worst-case end-to-end delay bounds for traffic flows sharing a TDMA-based network using Network Calculus. First, we extend classic timing analysis to integrate the impact of non-preemptive message transmission and various service policies in end-systems, e.g., First In First Out (FIFO), Fixed Priority (FP) and Weighted Round Robin (WRR). Afterwards, the proposed models are refined using Integer Linear Programming (ILP) to obtain tighter end-to-end delay bounds. Finally, this general analysis is illustrated and validated in the case of a TDMA-based Ethernet network for I/O avionics applications. Results show the efficiency of the proposed models to provide stronger guarantees on system schedulability, compared to classic models

Clustering objectives in wireless sensor networks: A survey and research direction analysis

Wireless Sensor Networks (WSNs) typically include thousands of resource-constrained sensors to monitor their surroundings, collect data, and transfer it to remote servers for further processing. Although WSNs are considered highly flexible ad-hoc networks, network management has been a fundamental challenge in these types of net- works given the deployment size and the associated quality concerns such as resource management, scalability, and reliability. Topology management is considered a viable technique to address these concerns. Clustering is the most well-known topology management method in WSNs, grouping nodes to manage them and/or executing various tasks in a distributed manner, such as resource management. Although clustering techniques are mainly known to improve energy consumption, there are various quality-driven objectives that can be realized through clustering. In this paper, we review comprehensively existing WSN clustering techniques, their objectives and the network properties supported by those techniques. After refining more than 500 clustering techniques, we extract about 215 of them as the most important ones, which we further review, catergorize and classify based on clustering objectives and also the network properties such as mobility and heterogeneity. In addition, statistics are provided based on the chosen metrics, providing highly useful insights into the design of clustering techniques in WSNs.publishedVersio

Optimización de energía y eficiencia de transmisión con análisis de imparcialidad en comunicaciones inalámbricas adaptativas

Las redes inalámbricas se caracterizan por utilizar un medio de transmisión dinámico, en el que las condiciones de transmisión cambian de forma continua. Este cambio continuado lleva a diseñar los sistemas de comunicaciones desde dos puntos de vista. El más elemental es diseñar nuestro sistema para el caso peor. Aunque sencilla, esta solución lleva aparejado un sobredimensionamiento de los recursos empleados; si consideramos por ejemplo la potencia de transmisión, este sobredimensionamiento resultará, entre las consecuencias más inmediatas, en mayores interferencias y mayor consumo de energía (y por tanto menor duración de las baterías en sistemas así alimentados). Frente al anterior enfoque, la transmisión adaptativa permite adecuar los parámetros de transmisión a las condiciones del canal. El objetivo de esta tesis es proponer esquemas de transmisión adaptativos para sistemas inalámbricos que, bien mejoran técnicas existentes, como veremos para redes de sensores, o bien resuelven problemas nuevos, como la optimización de la eficiencia de transmisión de una estación base. Contribuimos por tanto al desarrollo de técnicas de transmisión adaptativa en redes inalámbricas para conseguir sistemas eficientes en energía y en tasa de transmisión. Para ello, previamente realizamos un recorrido por las técnicas existentes de transmisión adaptativa (capítulo 2) y presentamos las herramientas matemáticas que se utilizarán para resolver los problemas de optimización que resultan de las técnicas propuestas (capítulo 3). La transmisión eficiente en energía que proponemos tiene como objetivo optimizar la energía total de transmisión del enlace ascendente para un sistema centralizado, con comunicaciones de salto único. Se asume que la red es heterogénea, lo que se traduce en que cada nodo tendrá unos requisitos diferentes de calidad de servicio en función de la aplicación que se ejecute en cada nodo. La calidad de servicio vendrá expresada mediante la tasa de error de símbolo y una tasa de transmisión de bit. La optimización propuesta se basa en un esquema de modulación cross-layer que asigna adaptativamente la duración de los intervalos de transmisión, y por tanto los bits por símbolo a transmitir, cumpliendo con la calidad de servicio exigida. Este esquema lo particularizamos para redes inalámbricas de sensores. La optimización de la eficiencia de transmisión (o goodput) para el enlace descendente entre una estación base y los usuarios que de ella dependen, la realizaremos mediante la asignación de los recursos disponibles: subcanal (entendido como agrupación de subportadoras), potencia y tasa de bit por símbolo. El modelo del sistema implementa un mecanismo de control de imparcialidad que evita que resulten beneficiados aquellos usuarios que presenten unas condiciones más favorables de transmisión. Para resolver la asignación de recursos, se proponen dos esquemas: un esquema de asignación en dos pasos que reduce la complejidad del problema de asignación inicial, y un esquema subóptimo, orientado a la implementación práctica, que permite una reducción muy considerable de la carga computacional, sin una degradación apreciable del rendimiento respecto al óptimo.------------------------------------------------------------------------------------Wireless networks are characterized by the use of a dynamic transmission channel, in which transmission conditions are continuously changing. This continuous change asks for designing communication systems from two different viewpoints. The more basic one is to prepare our system for the worst case; this option, although straightforward, implies an excess of the resources used; for instance, if transmission power is considered, this excess of power results in a high interference and a high energy consumption (and, therefore, provokes a shorter lifetime for the batteries), among the most inmediate consequences. Contrary to the previous point of view, adaptive transmission allows to adjust transmission parameters values to channel conditions. The objective of this thesis is to propose new adaptive transmission schemes for wireless systems. Some of these schemes outperform existing techniques, as for the case of sensor networks, an others solve new problems, for instance the optimization of a base station transmitted goodput. We therefore contribute to the development of adaptive transmission techniques for wireless networks in order to achieve energy-efficient and transmision-efficent systems. To this end, we have previously reviewed the existing adaptive transmission techniques (chapter 2) and the mathematical tools that we apply to the optimization problems resulting from the proposed techniques (chapter 3). The energy-efficent scheme we propose targets the total transmission energy optimization in the uplink of a centralized system, with single-hop communications. Network heterogeneity is assumed, which translates into different quality of service requirements depending on the application running at each node. Quality of service is expressed by means of the symbol-error rate and the minimum bit-rate. The presented design is cross-layer-based and adapts time-slot duration to channel conditions, using adaptive modulation to fulfil the required quality of service. This proposal is particularly fitted to wireless sensor networks. Goodput optimization for the downlink is performed by means of resources allocation, specifically of subchannels, transmit power and bit-rate per symbol. For our purpose, a subchannel is defined as a group of subcarriers. Our system model is provided with a fairness control mechanism that prevents users with favourable channel conditions from obtaining most of the resources. We present a two-step assignment scheme to solve resource allocation that reduces the complexity of the original problem, and a suboptimal implementation-oriented approach that allows a significative reduction of the computational load, without a significant loss of performance

Backscatter-assisted data offloading in OFDMA-based wireless powered mobile edge computing for IoT networks

Mobile edge computing (MEC) has emerged as a prominent technology to overcome sudden demands on computation-intensive applications of the Internet of Things (IoT) with finite processing capabilities. Nevertheless, the limited energy resources also seriously hinders IoT devices from offloading tasks that consume high power in active RF communications. Despite the development of energy harvesting (EH) techniques, the harvested energy from surrounding environments could be inadequate for power-hungry tasks. Fortunately, Backscatter communications (Backcom) is an intriguing technology to narrow the gap between the power needed for communication and harvested power. Motivated by these considerations, this paper investigates a backscatter-assisted data offloading in OFDMA-based wireless-powered (WP) MEC for IoT systems. Specifically, we aim at maximizing the sum computation rate by jointly optimizing the transmit power at the gateway (GW), backscatter coefficient, time-splitting (TS) ratio, and binary decision-making matrices. This problem is challenging to solve due to its non-convexity. To find solutions, we first simplify the problem by determining the optimal values of transmit power of the GW and backscatter coefficient. Then, the original problem is decomposed into two sub-problems, namely, TS ratio optimization with given offloading decision matrices and offloading decision optimization with given TS ratio. Especially, a closedform expression for the TS ratio is obtained which greatly enhances the CPU execution time. Based on the solutions of the two sub-problems, an efficient algorithm, termed the fast-efficient algorithm (FEA), is proposed by leveraging the block coordinate descent method. Then, it is compared with exhaustive search (ES), bisection-based algorithm (BA), edge computing (EC), and local computing (LC) used as reference methods. As a result, the FEA is the best solution which results in a near-globally-optimal solution at a much lower complexity as compared to benchmark schemes. For instance, the CPU execution time of FEA is about 0.029 second in a 50-user network, which is tailored for ultralow latency applications of IoT networks

Enhanced Spectrum Sensing Techniques for Cognitive Radio Systems

Due to the rapid growth of new wireless communication services and applications, much attention has been directed to frequency spectrum resources. Considering the limited radio spectrum, supporting the demand for higher capacity and higher data rates is a challenging task that requires innovative technologies capable of providing new ways of exploiting the available radio spectrum. Cognitive radio (CR), which is among the core prominent technologies for the next generation of wireless communication systems, has received increasing attention and is considered a promising solution to the spectral crowding problem by introducing the notion of opportunistic spectrum usage. Spectrum sensing, which enables CRs to identify spectral holes, is a critical component in CR technology. Furthermore, improving the efficiency of the radio spectrum use through spectrum sensing and dynamic spectrum access (DSA) is one of the emerging trends. In this thesis, we focus on enhanced spectrum sensing techniques that provide performance gains with reduced computational complexity for realistic waveforms considering radio frequency (RF) impairments, such as noise uncertainty and power amplifier (PA) non-linearities. The first area of study is efficient energy detection (ED) methods for spectrum sensing under non-flat spectral characteristics, which deals with relatively simple methods for improving the detection performance. In realistic communication scenarios, the spectrum of the primary user (PU) is non-flat due to non-ideal frequency responses of the devices and frequency selective channel conditions. Weighting process with fast Fourier transform (FFT) and analysis filter bank (AFB) based multi-band sensing techniques are proposed for overcoming the challenge of non-flat characteristics. Furthermore, a sliding window based spectrum sensing approach is addressed to detect a re-appearing PU that is absent in one time and present in other time. Finally, the area under the receiver operating characteristics curve (AUC) is considered as a single-parameter performance metric and is derived for all the considered scenarios. The second area of study is reduced complexity energy and eigenvalue based spectrum sensing techniques utilizing frequency selectivity. More specifically, novel spectrum sensing techniques, which have relatively low computational complexity and are capable of providing accurate and robust performance in low signal-to-noise ratio (SNR) with noise uncertainty, as well as in the presence of frequency selectivity, are proposed. Closed-form expressions are derived for the corresponding probability of false alarm and probability of detection under frequency selectivity due the primary signal spectrum and/or the transmission channel. The offered results indicate that the proposed methods provide quite significant saving in complexity, e.g., 78% reduction in the studied example case, whereas their detection performance is improved both in the low SNR and under noise uncertainty. Finally, a new combined spectrum sensing and resource allocation approach for multicarrier radio systems is proposed. The main contribution of this study is the evaluation of the CR performance when using wideband spectrum sensing methods in combination with water-filling and power interference (PI) based resource allocation algorithms in realistic CR scenarios. Different waveforms, such as cyclic prefix based orthogonal frequency division multiplexing (CP-OFDM), enhanced orthogonal frequency division multiplexing (E-OFDM) and filter bank based multicarrier (FBMC), are considered with PA nonlinearity type RF impairments to see the effects of spectral leakage on the spectrum sensing and resource allocation performance. It is shown that AFB based spectrum sensing techniques and FBMC waveforms with excellent spectral containment properties have clearly better performance compared to the traditional FFT based spectrum sensing techniques with the CP-OFDM. Overall, the investigations in this thesis provide novel spectrum sensing techniques for overcoming the challenge of noise uncertainty with reduced computational complexity. The proposed methods are evaluated under realistic signal models

Cumulative index to NASA Tech Briefs, 1986-1990, volumes 10-14

Tech Briefs are short announcements of new technology derived from the R&D activities of the National Aeronautics and Space Administration. These briefs emphasize information considered likely to be transferrable across industrial, regional, or disciplinary lines and are issued to encourage commercial application. This cumulative index of Tech Briefs contains abstracts and four indexes (subject, personal author, originating center, and Tech Brief number) and covers the period 1986 to 1990. The abstract section is organized by the following subject categories: electronic components and circuits, electronic systems, physical sciences, materials, computer programs, life sciences, mechanics, machinery, fabrication technology, and mathematics and information sciences

LIPIcs, Volume 251, ITCS 2023, Complete Volume

LIPIcs, Volume 251, ITCS 2023, Complete Volum