Resource allocation technique for powerline network using a modified shuffled frog-leaping algorithm

Resource allocation (RA) techniques should be made efficient and optimized in order to enhance the QoS (power & bit, capacity, scalability) of high-speed networking data applications. This research attempts to further increase the efficiency towards near-optimal performance. RA’s problem involves assignment of subcarriers, power and bit amounts for each user efficiently. Several studies conducted by the Federal Communication Commission have proven that conventional RA approaches are becoming insufficient for rapid demand in networking resulted in spectrum underutilization, low capacity and convergence, also low performance of bit error rate, delay of channel feedback, weak scalability as well as computational complexity make real-time solutions intractable. Mainly due to sophisticated, restrictive constraints, multi-objectives, unfairness, channel noise, also unrealistic when assume perfect channel state is available. The main goal of this work is to develop a conceptual framework and mathematical model for resource allocation using Shuffled Frog-Leap Algorithm (SFLA). Thus, a modified SFLA is introduced and integrated in Orthogonal Frequency Division Multiplexing (OFDM) system. Then SFLA generated random population of solutions (power, bit), the fitness of each solution is calculated and improved for each subcarrier and user. The solution is numerically validated and verified by simulation-based powerline channel. The system performance was compared to similar research works in terms of the system’s capacity, scalability, allocated rate/power, and convergence. The resources allocated are constantly optimized and the capacity obtained is constantly higher as compared to Root-finding, Linear, and Hybrid evolutionary algorithms. The proposed algorithm managed to offer fastest convergence given that the number of iterations required to get to the 0.001% error of the global optimum is 75 compared to 92 in the conventional techniques. Finally, joint allocation models for selection of optima resource values are introduced; adaptive power and bit allocators in OFDM system-based Powerline and using modified SFLA-based TLBO and PSO are propose

Signal processing techniques for mobile multimedia systems

Recent trends in wireless communication systems show a significant demand for the delivery of multimedia services and applications over mobile networks - mobile multimedia - like video telephony, multimedia messaging, mobile gaming, interactive and streaming video, etc. However, despite the ongoing development of key communication technologies that support these applications, the communication resources and bandwidth available to wireless/mobile radio systems are often severely limited. It is well known, that these bottlenecks are inherently due to the processing capabilities of mobile transmission systems, and the time-varying nature of wireless channel conditions and propagation environments. Therefore, new ways of processing and transmitting multimedia data over mobile radio channels have become essential which is the principal focus of this thesis. In this work, the performance and suitability of various signal processing techniques and transmission strategies in the application of multimedia data over wireless/mobile radio links are investigated. The proposed transmission systems for multimedia communication employ different data encoding schemes which include source coding in the wavelet domain, transmit diversity coding (space-time coding), and adaptive antenna beamforming (eigenbeamforming). By integrating these techniques into a robust communication system, the quality (SNR, etc) of multimedia signals received on mobile devices is maximised while mitigating the fast fading and multi-path effects of mobile channels. To support the transmission of high data-rate multimedia applications, a well known multi-carrier transmission technology known as Orthogonal Frequency Division Multiplexing (OFDM) has been implemented. As shown in this study, this results in significant performance gains when combined with other signal-processing techniques such as spa ce-time block coding (STBC). To optimise signal transmission, a novel unequal adaptive modulation scheme for the communication of multimedia data over MIMO-OFDM systems has been proposed. In this system, discrete wavelet transform/subband coding is used to compress data into their respective low-frequency and high-frequency components. Unlike traditional methods, however, data representing the low-frequency data are processed and modulated separately as they are more sensitive to the distortion effects of mobile radio channels. To make use of a desirable subchannel state, such that the quality (SNR) of the multimedia data recovered at the receiver is optimized, we employ a lookup matrix-adaptive bit and power allocation (LM-ABPA) algorithm. Apart from improving the spectral efficiency of OFDM, the modified LM-ABPA scheme, sorts and allocates subcarriers with the highest SNR to low-frequency data and the remaining to the least important data. To maintain a target system SNR, the LM-ABPA loading scheme assigns appropriate signal constella tion sizes and transmit power levels (modulation type) across all subcarriers and is adapted to the varying channel conditions such that the average system error-rate (SER/BER) is minimised. When configured for a constant data-rate load, simulation results show significant performance gains over non-adaptive systems. In addition to the above studies, the simulation framework developed in this work is applied to investigate the performance of other signal processing techniques for multimedia communication such as blind channel equalization, and to examine the effectiveness of a secure communication system based on a logistic chaotic generator (LCG) for chaos shift-keying (CSK)

Novel Models and Algorithms Paving the Road towards RF Convergence

After decades of rapid evolution in electronics and signal processing, the technologies in communications, positioning, and sensing have achieved considerable progress. Our daily lives are fundamentally changed and substantially defined by the advancement in these technologies. However, the trend is challenged by a well-established fact that the spectrum resources, like other natural resources, are gradually becoming scarce. This thesis carries out research in the field of RF convergence, which is regarded as a mean to intelligently exploit spectrum resources, e.g., by finding novel methods of optimising and sharing tasks between communication, positioning, and sensing. The work has been done to closely explore opportunities for supporting the RF convergence. As a supplement for the electromagnetic waves propagation near the ground, ground-to-air channel models are first proposed and analysed, by incorporating the atmospheric effects when the altitude of aerial users is higher than 300 m. The status quos of techniques in communications, positioning, and sensing are separately reviewed, and our newly developments in each field are briefly introduced. For instance, we study the MIMO techniques for interference mitigation on aerial users; we construct the reflected echoes, i.e., the radar receiving, for the joint sensing and communications system. The availability of GNSS signals is of vital importance to the GNSS-enabled services, particularly the life-critical applications. To enhance the resilience of GNSS receivers, the RF fingerprinting based anti-spoofing techniques are also proposed and discussed. Such a guarantee on GNSS and ubiquitous GNSS services drive the utilisation of location information, also needed for communications, hence the proposal of a location-based beamforming algorithm. The superposition coding scheme, as an attempt of the waveform design, is also brought up for the joint sensing and communications. The RF convergence will come with many facets: the joint sensing and communications promotes an efficient use of frequency spectrum; the positioning-aided communications encourage the cooperation between systems; the availability of robust global positioning systems benefits the applications relying on the GNSS service

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

Abstracts on Radio Direction Finding (1899 - 1995)

The files on this record represent the various databases that originally composed the CD-ROM issue of "Abstracts on Radio Direction Finding" database, which is now part of the Dudley Knox Library's Abstracts and Selected Full Text Documents on Radio Direction Finding (1899 - 1995) Collection. (See Calhoun record https://calhoun.nps.edu/handle/10945/57364 for further information on this collection and the bibliography). Due to issues of technological obsolescence preventing current and future audiences from accessing the bibliography, DKL exported and converted into the three files on this record the various databases contained in the CD-ROM. The contents of these files are: 1) RDFA_CompleteBibliography_xls.zip [RDFA_CompleteBibliography.xls: Metadata for the complete bibliography, in Excel 97-2003 Workbook format; RDFA_Glossary.xls: Glossary of terms, in Excel 97-2003 Workbookformat; RDFA_Biographies.xls: Biographies of leading figures, in Excel 97-2003 Workbook format]; 2) RDFA_CompleteBibliography_csv.zip [RDFA_CompleteBibliography.TXT: Metadata for the complete bibliography, in CSV format; RDFA_Glossary.TXT: Glossary of terms, in CSV format; RDFA_Biographies.TXT: Biographies of leading figures, in CSV format]; 3) RDFA_CompleteBibliography.pdf: A human readable display of the bibliographic data, as a means of double-checking any possible deviations due to conversion

State-of-the-Art Sensors Technology in Spain 2015: Volume 1

This book provides a comprehensive overview of state-of-the-art sensors technology in specific leading areas. Industrial researchers, engineers and professionals can find information on the most advanced technologies and developments, together with data processing. Further research covers specific devices and technologies that capture and distribute data to be processed by applying dedicated techniques or procedures, which is where sensors play the most important role. The book provides insights and solutions for different problems covering a broad spectrum of possibilities, thanks to a set of applications and solutions based on sensory technologies. Topics include: • Signal analysis for spectral power • 3D precise measurements • Electromagnetic propagation • Drugs detection • e-health environments based on social sensor networks • Robots in wireless environments, navigation, teleoperation, object grasping, demining • Wireless sensor networks • Industrial IoT • Insights in smart cities • Voice recognition • FPGA interfaces • Flight mill device for measurements on insects • Optical systems: UV, LEDs, lasers, fiber optics • Machine vision • Power dissipation • Liquid level in fuel tanks • Parabolic solar tracker • Force sensors • Control for a twin roto

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering

18th IEEE Workshop on Nonlinear Dynamics of Electronic Systems: Proceedings

Proceedings of the 18th IEEE Workshop on Nonlinear Dynamics of Electronic Systems, which took place in Dresden, Germany, 26 – 28 May 2010.:Welcome Address ........................ Page I Table of Contents ........................ Page III Symposium Committees .............. Page IV Special Thanks ............................. Page V Conference program (incl. page numbers of papers) ................... Page VI Conference papers Invited talks ................................ Page 1 Regular Papers ........................... Page 14 Wednesday, May 26th, 2010 ......... Page 15 Thursday, May 27th, 2010 .......... Page 110 Friday, May 28th, 2010 ............... Page 210 Author index ............................... Page XII