Multicarrier Frequency Hopping Spread Spectrum Techniques With Quasi-Cyclic Low Density Parity Check Codes Channel Coding

This work presents a new proposed Multicarrier Frequency Hopping Spread Spectrum (MCFH-SS) system employing Quasi-Cyclic Low Density Parity Check (QC-LDPC) codes instead of the conventional LDPC codes. A new technique for constructing the QC-LDPC codes based on row division method is proposed. The new codes offer more flexibility in terms of high girth, multiple code rates and block length. Moreover, a new scheme for channel prediction in MCFH-SS system is proposed. The technique adaptively estimates the channel conditions and eliminates the need for the system to transmit a request message prior to transmitting the packet data. The ready-to-use channel will be occupied with a Pseudonoise (PN) code and use for transmission or else, it will be banned

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

Identification of Technologies for Provision of Future Aeronautical Communications

This report describes the process, findings, and recommendations of the second of three phases of the Future Communications Study (FCS) technology investigation conducted by NASA Glenn Research Center and ITT Advanced Engineering & Sciences Division for the Federal Aviation Administration (FAA). The FCS is a collaborative research effort between the FAA and Eurocontrol to address frequency congestion and spectrum depletion for safety critical airground communications. The goal of the technology investigation is to identify technologies that can support the longterm aeronautical mobile communication operating concept. A derived set of evaluation criteria traceable to the operating concept document is presented. An adaptation of the analytical hierarchy process is described and recommended for selecting candidates for detailed evaluation. Evaluations of a subset of technologies brought forward from the prescreening process are provided. Five of those are identified as candidates with the highest potential for continental airspace solutions in L-band (P-34, W-CDMA, LDL, B-VHF, and E-TDMA). Additional technologies are identified as best performers in the unique environments of remote/oceanic airspace in the satellite bands (Inmarsat SBB and a custom satellite solution) and the airport flight domain in C-band (802.16e). Details of the evaluation criteria, channel models, and the technology evaluations are provided in appendixes

Multi-dimensional direct-sequence spread spectrum multiple-access communication with adaptive channel coding

During the race towards the4th generation (4G) cellular-based digital communication systems, a growth in the demand for high capacity, multi-media capable, improved Quality-of-Service (QoS) mobile communication systems have caused the developing mobile communications world to turn towards betterMultiple Access (MA) techniques, like Code Division Multiple Access (CDMA) [5]. The demand for higher throughput and better QoS in future 4G systems have also given rise to a scheme that is becoming ever more popular for use in these so-called ‘bandwidth-on-demand’ systems. This scheme is known as adaptive channel coding, and gives a system the ability to firstly sense changes in conditions, and secondly, to adapt to these changes, exploiting the fact that under good channel conditions, a very simple or even no channel coding scheme can be used for Forward Error Correction(FEC). This will ultimately result in better system throughput utilization. One such scheme, known as incremental redundancy, is already implemented in the Enhanced Data Rates for GSM Evolution (EDGE) standard. This study presents an extensive simulation study of a Multi-User (MU), adaptive channel coded Direct Sequence Spread Spectrum Multiple Access (DS/SSMA) communication system. This study firstly presents and utilizes a complex Base Band(BB) DS/SSMA transmitter model, aimed at user data diversity [6] in order to realize the MU input data to the system. This transmitter employs sophisticated double-sideband (DSB)Constant-Envelope Linearly Interpolated Root-of-Unity (CE-LI-RU) filtered General Chirp-Like (GCL) sequences [34, 37, 38] to band limit and spread user data. It then utilizes a fully user-definable, complex Multipath Fading Channel Simulator(MFCS), first presented by Staphorst [3], which is capable of reproducing all of the physical attributes of realistic mobile fading channels. Next, this study presents a matching DS/SSMA receiver structure that aims to optimally recover user data from the channel, ensuring the achievement of data diversity. In order to provide the basic channel coding functionality needed by the system of this study, three simple, but well-known channel coding schemes are investigated and employed. These are: binary Hamming (7,4,3) block code, (15,7,5) binary Bose-Chadhuri-Hocquenghem (BCH) block code and a rate 1/3 <i.Non-Systematic (NS) binary convolutional code [6]. The first step towards the realization of any adaptive channel coded system is the ability to measure channel conditions as fast as possible, without the loss of accuracy or inclusion of known data. In 1965, Gooding presented a paper in which he described a technique that measures communication conditions at the receiving end of a system through a device called a Performance Monitoring Unit (PMU) [12, 13]. This device accelerates the system’sBit Error Rate (BER) to a so-called Pseudo Error Rate(PER) through a process known as threshold modification. It then uses a simple PER extrapolation algorithm to estimate the system’s true BER with moderate accuracy and without the need for known data. This study extends the work of Gooding by applying his technique to the DS/SSMA system that utilizes a generic Soft-Output Viterbi Algorithm(SOVA) decoder [39] structure for the trellis decoding of the binary linear block codes [3, 41-50], as well as binary convolutional codes mentioned, over realistic MU frequency selective channel conditions. This application will grant the system the ability to sense changes in communication conditions through real-time BER measurement and, ultimately, to adapt to these changes by switching to different channel codes. Because no previous literature exists on this application, this work is considered novel. Extensive simulation results also investigate the linearity of the PER vs. modified threshold relationship for uncoded, as well as all coded cases. These simulations are all done for single, as well as multiple user systems. This study also provides extensive simulation results that investigate the calculation accuracy and speed advantages that Gooding’s technique possesses over that of the classic Monte-Carlo technique for BER estimation. These simulations also consider uncoded and coded cases, as well as single and multiple users. Finally, this study investigates the experimental real-time performance of the fully functional MU, adaptive coded, DS/SSMA communication system over varying channel conditions. During this part of the study, the channel conditions are varied over time, and the system’s adaptation (channel code switching) performance is observed through a real-time observation of the system’s estimated BER. This study also extends into cases with multiple system users. Since the adaptive coded system of this study does not require known data sequences (training sequences), inclusion of Gooding’s technique for real-time BER estimation through threshold modification and PER extrapolation in future 4G adaptive systems will enable better Quality-of-Service (QoS) management without sacrificing throughput. Furthermore, this study proves that when Gooding’s technique is applied to a coded system with a soft-output, it can be an effective technique for QoS monitoring, and should be considered in 4G systems of the future.Dissertation (MEng (Computer Engineering))--University of Pretoria, 2007.Electrical, Electronic and Computer EngineeringMEngunrestricte

Applications of MATLAB in Science and Engineering

The book consists of 24 chapters illustrating a wide range of areas where MATLAB tools are applied. These areas include mathematics, physics, chemistry and chemical engineering, mechanical engineering, biological (molecular biology) and medical sciences, communication and control systems, digital signal, image and video processing, system modeling and simulation. Many interesting problems have been included throughout the book, and its contents will be beneficial for students and professionals in wide areas of interest

Advanced Trends in Wireless Communications

Physical limitations on wireless communication channels impose huge challenges to reliable communication. Bandwidth limitations, propagation loss, noise and interference make the wireless channel a narrow pipe that does not readily accommodate rapid flow of data. Thus, researches aim to design systems that are suitable to operate in such channels, in order to have high performance quality of service. Also, the mobility of the communication systems requires further investigations to reduce the complexity and the power consumption of the receiver. This book aims to provide highlights of the current research in the field of wireless communications. The subjects discussed are very valuable to communication researchers rather than researchers in the wireless related areas. The book chapters cover a wide range of wireless communication topics

Smart Wireless Sensor Networks

The recent development of communication and sensor technology results in the growth of a new attractive and challenging area - wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors which do not only perceive ambient physical parameters but also be able to process information, cooperate with each other and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption. Special purposes of the applications require design and operation of WSNs different from conventional networks such as the internet. The network design must take into account of the objectives of specific applications. The nature of deployed environment must be considered. The limited of sensor nodes� resources such as memory, computational ability, communication bandwidth and energy source are the challenges in network design. A smart wireless sensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage, reliability and security of network's operation for a maximized lifetime. This book discusses various aspects of designing such smart wireless sensor networks. Main topics includes: design methodologies, network protocols and algorithms, quality of service management, coverage optimization, time synchronization and security techniques for sensor networks

Real-Time Sensor Networks and Systems for the Industrial IoT

The Industrial Internet of Things (Industrial IoT—IIoT) has emerged as the core construct behind the various cyber-physical systems constituting a principal dimension of the fourth Industrial Revolution. While initially born as the concept behind specific industrial applications of generic IoT technologies, for the optimization of operational efficiency in automation and control, it quickly enabled the achievement of the total convergence of Operational (OT) and Information Technologies (IT). The IIoT has now surpassed the traditional borders of automation and control functions in the process and manufacturing industry, shifting towards a wider domain of functions and industries, embraced under the dominant global initiatives and architectural frameworks of Industry 4.0 (or Industrie 4.0) in Germany, Industrial Internet in the US, Society 5.0 in Japan, and Made-in-China 2025 in China. As real-time embedded systems are quickly achieving ubiquity in everyday life and in industrial environments, and many processes already depend on real-time cyber-physical systems and embedded sensors, the integration of IoT with cognitive computing and real-time data exchange is essential for real-time analytics and realization of digital twins in smart environments and services under the various frameworks’ provisions. In this context, real-time sensor networks and systems for the Industrial IoT encompass multiple technologies and raise significant design, optimization, integration and exploitation challenges. The ten articles in this Special Issue describe advances in real-time sensor networks and systems that are significant enablers of the Industrial IoT paradigm. In the relevant landscape, the domain of wireless networking technologies is centrally positioned, as expected