Boosted PTS Method with Mu-Law Companding Techniques for PAPR Reduction in OFDM Systems

This paper proposes an enhanced PAPR reduction technique which combines an enhanced PTS method with Mu-Law companding. The enhanced PTS method improves performances in both the partitioning and phase rotation steps. Enhancement in partitioning is achieved through a judicious incorporation of AP-PTS scheme into the IP-PTS. As for phase rotation, an optimal set of rotation vectors is derived based on the correlation properties of candidate signals. The PAPR reduction of this enhanced PTS method is further improved by annexing Mu-Law companding at the end of the enhanced PTS. This application of Mu-Law characteristic in the time domain of OFDM signal significantly improves the PAPR reduction capability of the approach. Simulation results show that the PAPR performance of the enhanced PTS method with Mu-Law companding technique on various scenarios with different modulation schemes is better than that of the PRP-PTS. This approach can be considered as a very attractive candidate for achieving a significant reduction of PAPR, while maintaining a low computational complexity

Automatic transmit power control for power efficient communications in UAS

Nowadays, unmanned aerial vehicles (UAV) have become one of the most popular tools that can be used in commercial, scientific, agricultural and military applications. As drones become faster, smaller and cheaper, with the ability to add payloads, the usage of the drone can be versatile. In most of the cases, unmanned aerials systems (UAS) are equipped with a wireless communication system to establish a link with the ground control station to transfer the control commands, video stream, and payload data. However, with the limited onboard calculation resources in the UAS, and the growing size and volume of the payload data, computational complex signal processing such as deep learning cannot be easily done on the drone. Hence, in many drone applications, the UAS is just a tool for capturing and storing data, and then the data is post-processed off-line in a more powerful computing device. The other solution is to stream payload data to the ground control station (GCS) and let the powerful computer on the ground station to handle these data in real-time. With the development of communication techniques such as orthogonal frequency-division multiplexing (OFDM) and multiple-input multiple-output (MIMO) transmissions, it is possible to increase the spectral efficiency over large bandwidths and consequently achieve high transmission rates. However, the drone and the communication system are usually being designed separately, which means that regardless of the situation of the drone, the communication system is working independently to provide the data link. Consequently, by taking into account the position of the drone, the communication system has some room to optimize the link budget efficiency. In this master thesis, a power-efficient wireless communication downlink for UAS has been designed. It is achieved by developing an automatic transmit power control system and a custom OFDM communication system. The work has been divided into three parts: research of the drone communication system, an optimized communication system design and finally, FPGA implementation. In the first part, an overview on commercial drone communication schemes is presented and discussed. The advantages and disadvantages shown are the source of inspiration for improvement. With these ideas, an optimized scheme is presented. In the second part, an automatic transmit power control system for UAV wireless communication and a power-efficient OFDM downlink scheme are proposed. The automatic transmit power control system can estimate the required power level by the relative position between the drone and the GCS and then inform the system to adjust the power amplifier (PA) gain and power supply settings. To obtain high power efficiency for different output power levels, a searching strategy has been applied to the PA testbed to find out the best voltage supply and gain configurations. Besides, the OFDM signal generation developed in Python can encode data bytes to the baseband signal for testing purpose. Digital predistortion (DPD) linearization has been included in the transmitter’s design to guarantee the signal linearity. In the third part, two core algorithms: IFFT and LUT-based DPD, have been implemented in the FPGA platform to meet the real-time and high-speed I/O requirements. By using the high-level synthesis design process provided by Xilinx Corp, the algorithms are implemented as reusable IP blocks. The conclusion of the project is given in the end, including the summary of the proposed drone communication system and envisioning possible future lines of research

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

Positioning of a wireless relay node for useful cooperative communication

Given the exorbitant amount of data transmitted and the increasing demand for data connectivity in the 21st century, it has become imperative to search for pro-active and sustainable solutions to the effectively alleviate the overwhelming burden imposed on wireless networks. In this study a Decode and Forward cooperative relay channel is analyzed, with the employment of Maximal Ratio Combining at the destination node as the method of offering diversity combining. The system framework used is based on a three-node relay channel with a source node, relay node and a destination node. A model for the wireless communications channel is formulated in order for simulation to be carried out to investigate the impact on performance of relaying on a node placed at the edge of cell. Firstly, an AWGN channel is used before the effect of Rayleigh fading is taken into consideration. Result shows that performance of cooperative relaying performance is always superior or similar to conventional relaying. Additionally, relaying is beneficial when the relay is placed closer to the receiver

Comparative genomics for studying the proteomes of mucosal microorganisms

A tremendous number of microorganisms are known to interact with their animal hosts. The outcome of the interactions between microbes and their animal hosts range from modulating the maintenance of homeostasis to the establishment of processes leading to pathogenesis. Of the numerous species known to inhabit humans, the great majority live on mucosal surfaces which are highly defended. Despite their importance in human health, little is known about the molecular and cellular basis of most host-microbe interactions across the tremendous diversity of mucosal-adapted microorganisms. The ever-increasing availability of genome sequence data allows systematic comparative genomics studies to identify proteins with potential important molecular functions at the host-microbe interface. In this study, a genome-wide analysis was performed on 3,021,490 protein sequences derived from 867 complete microbial genome sequences across the three domains of cellular life. The ability of microbes to thrive successfully in a mucosal environment was examined in relation to functional genomics data from a range of publicly available databases. Particular emphasis was placed on the extracytoplasmic proteins of microorganisms that thrive on human mucosal surfaces. These proteins form the interface between the complex host-microbe and microbe-microbe interactions. The large amounts of data involved, combined with the numerous analytical techniques that need to be performed makes the study intractable with conventional bioinformatics. The lack of habitat annotations for microorganisms further compounds the problem of identifying the microbial extracytoplasmic proteins playing important roles in the mucosal environments. In order to address these problems, a distributed high throughput computational workflow was developed, and a system for mining biomedical literature was trained to automatically identify microorganisms’ habitats. The workflow integrated existing bioinformatics tools to identify and characterise protein-targeting signals, cell surface-anchoring features, protein domains and protein families. This study successfully demonstrated a large-scale comparative genomics approach utilising a system called Microbase to harness Grid and Cloud computing technologies. A number of conserved protein domains and families that are significantly associated with a speiii iv cific set of mucosa-inhabiting microorganisms were identified. These conserved protein regions of which their functions were either characterised or unknown, were quite narrow in their coverage of taxa distribution, with only a few protein domains more widely distributed, suggesting that mucosal microorganisms evolved different solutions in their strategies and mechanisms for their survival in the host mucosal environments. Metabolic and biological processes common to many mucosal microorganisms included: carbohydrate and amino acid metabolisms, signal transduction, adhesion to host tissues or contents in mucosal environments (e.g. food remnants, mucins), and resistance to host defence mechanisms. Invasive or virulence factors were also identified in pathogenic strains. Several extracytoplasmic protein families were shared among prominent bacterial members of gut microbiota and microbial eukaryotes known to thrive in the same environment, suggesting that the ability of microbes to adapt to particular niches can be influenced by lateral gene transfer. A large number of conserved regions or protein families that potentially play important roles in the mucosa-microbe interactions were revealed by this study. Several of these candidates were proteins of unknown function. The identified candidates were subjected to more detailed computational analysis providing hypothesis for their function that will be tested experimentally in order to contribute to our understanding of the complex host-microbe interactions. Among the candidates of unknown function, a novel M60-like domain was identified. The domain was deposited in the Pfam database with accession number PF13402. The M60-like domain is shared amongst a broad range of mucosal microorganisms as well as their vertebrate hosts. Bioinformatics analyses of the M60-like domain suggested a potential catalytic function of the conserved motif as gluzincins metalloproteases. Targeting signals were detected across microbial M60-likecontaining proteins. Mucosa-related carbohydrate-binding modules (CBMs), CBM32 was also identified on several proteins containing M60-like domains encoded by known mucosal commensals and pathogens. The co-occurrence of the CBMs and M60-like domain, as well as annotated potential peptidase function unveiled a new functional context for the CBM, which is typically connected with carbohydrate processing enzymes but not proteases. The CBM domains linked with members of different protease families are likely to enable these proteases to bind to specific glycoproteins from host animals further highlighting the importance of proteases and CBMs (CBM32 and CBM5_12) in host-microbe interactions.EThOS - Electronic Theses Online ServiceMedical School, Newcastle UniversityGBUnited Kingdo

Third International Symposium on Space Mission Operations and Ground Data Systems, part 1

Under the theme of 'Opportunities in Ground Data Systems for High Efficiency Operations of Space Missions,' the SpaceOps '94 symposium included presentations of more than 150 technical papers spanning five topic areas: Mission Management, Operations, Data Management, System Development, and Systems Engineering. The papers focus on improvements in the efficiency, effectiveness, productivity, and quality of data acquisition, ground systems, and mission operations. New technology, techniques, methods, and human systems are discussed. Accomplishments are also reported in the application of information systems to improve data retrieval, reporting, and archiving; the management of human factors; the use of telescience and teleoperations; and the design and implementation of logistics support for mission operations

Bibliography of Lewis Research Center technical publications announced in 1977

This compilation of abstracts describes and indexes over 780 technical reports resulting from the scientific and engineering work performed and managed by the Lewis Research Center in 1977. All the publications were announced in the 1977 issues of STAR (Scientific and Technical Aerospace Reports) and/or IAA (International Aerospace Abstracts). Documents cited include research reports, journal articles, conference presentations, patents and patent applications, and theses