Link Selection in Buffer-Aided Cooperative Networks for Green IoT

In this paper, the link selection algorithm in buffer-aided cooperative networks with multiple co-channel interferers for green internet of things (IoT) is investigated. In the considered system, the relay node selects the better link from the first and the second hop with the help of buffers. We evaluate the effects of the system parameters by deriving the analytical analysis as well as the asymptotic results on the exact expressions of the outage probability. The impacts of system parameters, such as the predefined target rate, the priority-outage tradeoff parameter, the buffer length and the number of interferers are evaluated in different setup scenarios. Considerable performance gains can be obtained compared with the classical decode-and-forward relaying networks. Simulation results are provided to verify the theoretical analysis

Performance analysis of relay-aided wireless communication systems

Relay-aided networks have been proved to be cost-efficient solutions for wireless communications in respect of high data rates, enhanced spectrum efficiency and improved signal coverage. In the past decade, relaying techniques have been written into standards of modern wireless communications and significantly improve the quality of service (QoS) in wireless communications. In order to satisfy exponentially increased demands for data rates and wireless connectivities, various novel techniques for wireless communications have been proposed in recent years, which have brought significant challenges for the performance analysis of relaying networks. For the purpose of more practical investigations into relaying systems, researchers should not only analyse the relays employing novel techniques but also attach more importance to complex environments of wireless communications. With these objectives in mind, in this thesis, in-depth investigations into system performance for relay-assisted wireless communications are detailed. Firstly, the theoretic reliability of dual-hop amplify-and-forward (AF) systems over generalised η-μ and κ-μ fading channels are investigated using Gallager’s error exponents. These two versatile channel models can encompass a number of popular fading channels such as Rayleigh, Rician, Nakagami-m, Hoyt and one-sided Gaussian fading channels. We derive new analytical expressions for the probability distribution function (pdf) of the end-to-end signal-to-noise-ratio (SNR) of the system. These analytical expressions are then applied to analyse the system performance through the study of Gallager’s exponents, which are classical tight bounds of error exponents and present the trade-off between the practical information rate and the reliability of communication. Two types of Gallager’s exponents, namely the random coding error exponent (RCEE) and the expurgated error exponent, are studied. Based on the newly derived analytical expressions, we provide an efficient method to compute the required codeword length to achieve a predefined upper bound of error probability. In addition, the analytical expressions are derived for the cut-off rate and ergodic capacity of the system. Moreover, simplified expressions are presented at the high SNR regime. Secondly, the performance of a dual-hop amplify-and-forward (AF) multi-antenna relaying system over complex Gaussian channels is investigated. Three classical receiving strategies, i.e. the maximal-ratio combining (MRC), zero-forcing (ZF) and minimum mean square error (MMSE) are employed in the relay to mitigate the impact of co-channel interference (CCI), which follows the Poisson point process (PPP). We derive the exact analytical expressions of the capacities for this system in the infinite-area interference environment and the asymptotic analytical expressions for the lower bounds of capacities in the limited-area interference scenario. By computing the numerical results and the Monte Carlo simulation, we can observe the effect of relay processing schemes under different interference regimes. In the end, the non-orthogonal multiple access (NOMA) technique is introduced to relaying systems, which exploits multiplexing in the power domain. Order statistics are applied in this part to analyse the performances of ordered users. The randomness of both channel fading and path loss are taken into consideration. In addition to the exact analytical expressions, asymptotic expressions at high-SNR regimes are provided, which clearly show the effects of NOMA techniques using at relaying systems

Performanse kooperativnih bežičnih telekomunikacionih sistema i mogućnosti povećanja kapaciteta kanala u prisustvu fedinga i međukanalne interferencije

In order to improve the performance of the wireless signal transmission system in the presence of various types of interference, new methods of combining diversion techniques in the relay and on the receiving side have been proposed. When using diversi, the combining technique has shown a significant improvement in the performance of wireless relay signal transmission, and thus a lower probability of system failure. Increasing the capacity of wireless telecommunications systems is feasible in terms of fixed bandwidth and specified modulation format by using the cooperative concept to increase the signal strength to noise and interference ratio. By using mobile stations as a relay, performance improvement can be achieved in M2M communication, which can be rationally used to increase channel information capacity and transmission reliability. A more detailed analysis has been conducted and can answer questions about quantitative measures of improvement in the conditions of fading and inter-channel interference. The cases of relay transmission are discussed, as well as the possibility of applying a diversion technique to improve performance in conditions of simultaneous reception of a signal through a direct connection and through a relay. For the above cases, standard performance measures will be determined using statistical telecommunications theory

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

Selected On-Demand Medical Applications of 3D-Printing for Long-Duration Manned Space Missions

Recent technological advances in the area of Additive Manufacturing (i.e. 3D printing) allow for exploration of their use within long-duration manned space missions. Among the many potential application domains, medical and dental fabrication in support of crew health is of interest to NASA’s Advanced Exploration Systems directorate. A classification of medical events with their associated response timeline discern between those applications where current 3D printing technologies can provide adequate support. Products and devices that require on-demand fabrication (due to the high level of personal customization) but that can wait for a reasonable (e.g. few hours) fabrication time are the most promising areas. Among these non-emergency, on-demand applications, two were identified for further investigation: dental health and pharmaceutical drugs. A discussion on the challenges presented by a microgravity operational environment on these technologies is provided

Marshall Space Flight Center Faculty Fellowship Program

The research projects conducted by the 2016 Faculty Fellows at NASA Marshall Space Flight Center included propulsion studies on propellant issues, and materials investigations involving plasma effects and friction stir welding. Spacecraft Systems research was conducted on wireless systems and 3D printing of avionics. Vehicle Systems studies were performed on controllers and spacecraft instruments. The Science and Technology group investigated additive construction applied to Mars and Lunar regolith, medical uses of 3D printing, and unique instrumentation, while the Test Laboratory measured pressure vessel leakage and crack growth rates

Personality Identification from Social Media Using Deep Learning: A Review

Social media helps in sharing of ideas and information among people scattered around the world and thus helps in creating communities, groups, and virtual networks. Identification of personality is significant in many types of applications such as in detecting the mental state or character of a person, predicting job satisfaction, professional and personal relationship success, in recommendation systems. Personality is also an important factor to determine individual variation in thoughts, feelings, and conduct systems. According to the survey of Global social media research in 2018, approximately 3.196 billion social media users are in worldwide. The numbers are estimated to grow rapidly further with the use of mobile smart devices and advancement in technology. Support vector machine (SVM), Naive Bayes (NB), Multilayer perceptron neural network, and convolutional neural network (CNN) are some of the machine learning techniques used for personality identification in the literature review. This paper presents various studies conducted in identifying the personality of social media users with the help of machine learning approaches and the recent studies that targeted to predict the personality of online social media (OSM) users are reviewed