Joint signal detection and channel estimation in rank-deficient MIMO systems

L'évolution de la prospère famille des standards 802.11 a encouragé le développement des technologies appliquées aux réseaux locaux sans fil (WLANs). Pour faire face à la toujours croissante nécessité de rendre possible les communications à très haut débit, les systèmes à antennes multiples (MIMO) sont une solution viable. Ils ont l'avantage d'accroître le débit de transmission sans avoir recours à plus de puissance ou de largeur de bande. Cependant, l'industrie hésite encore à augmenter le nombre d'antennes des portables et des accésoires sans fil. De plus, à l'intérieur des bâtiments, la déficience de rang de la matrice de canal peut se produire dû à la nature de la dispersion des parcours de propagation, ce phénomène est aussi occasionné à l'extérieur par de longues distances de transmission. Ce projet est motivé par les raisons décrites antérieurement, il se veut un étude sur la viabilité des transcepteurs sans fil à large bande capables de régulariser la déficience de rang du canal sans fil. On vise le développement des techniques capables de séparer M signaux co-canal, même avec une seule antenne et à faire une estimation précise du canal. Les solutions décrites dans ce document cherchent à surmonter les difficultés posées par le medium aux transcepteurs sans fil à large bande. Le résultat de cette étude est un algorithme transcepteur approprié aux systèmes MIMO à rang déficient

Efficient radio resource management in next generation wireless networks

The current decade has witnessed a phenomenal growth in mobile wireless communication networks and subscribers. In 2015, mobile wireless devices and connections were reported to have grown to about 7.9 billion, exceeding human population. The explosive growth in mobile wireless communication network subscribers has created a huge demand for wireless network capacity, ubiquitous wireless network coverage, and enhanced Quality of Service (QoS). These demands have led to several challenging problems for wireless communication networks operators and designers. The Next Generation Wireless Networks (NGWNs) will support high mobility communications, such as communication in high-speed rails. Mobile users in such high mobility environment demand reliable QoS, however, such users are plagued with a poor signal-tonoise ratio, due to the high vehicular penetration loss, increased transmission outage and handover information overhead, leading to poor QoS provisioning for the networks' mobile users. Providing a reliable QoS for high mobility users remains one of the unique challenges for NGWNs. The increased wireless network capacity and coverage of NGWNs means that mobile communication users at the cell-edge should have enhanced network performance. However, due to path loss (path attenuation), interference, and radio background noise, mobile communication users at the cell-edge can experience relatively poor transmission channel qualities and subsequently forced to transmit at a low bit transmission rate, even when the wireless communication networks can support high bit transmission rate. Furthermore, the NGWNs are envisioned to be Heterogeneous Wireless Networks (HWNs). The NGWNs are going to be the integration platform of diverse homogeneous wireless communication networks for a convergent wireless communication network. The HWNs support single and multiple calls (group calls), simultaneously. Decision making is an integral core of radio resource management. One crucial decision making in HWNs is network selection. Network selection addresses the problem of how to select the best available access network for a given network user connection. For the integrated platform of HWNs to be truly seamless and efficient, a robust and stable wireless access network selection algorithm is needed. To meet these challenges for the different mobile wireless communication network users, the NGWNs will have to provide a great leap in wireless network capacity, coverage, QoS, and radio resource utilization. Moving wireless communication networks (mobile hotspots) have been proposed as a solution to providing reliable QoS to high mobility users. In this thesis, an Adaptive Thinning Mobility Aware (ATMA) Call Admission Control (CAC) algorithm for improving the QoS and radio resource utilization of the mobile hotspot networks, which are of critical importance for communicating nodes in moving wireless networks is proposed. The performance of proposed ATMA CAC scheme is investigated and compare it with the traditional CAC scheme. The ATMA scheme exploits the mobility events in the highspeed mobility communication environment and the calls (new and handoff calls) generation pattern to enhance the QoS (new call blocking and handoff call dropping probabilities) of the mobile users. The numbers of new and handoff calls in wireless communication networks are dynamic random processes that can be effectively modeled by the Continuous Furthermore, the NGWNs are envisioned to be Heterogeneous Wireless Networks (HWNs). The NGWNs are going to be the integration platform of diverse homogeneous wireless communication networks for a convergent wireless communication network. The HWNs support single and multiple calls (group calls), simultaneously. Decision making is an integral core of radio resource management. One crucial decision making in HWNs is network selection. Network selection addresses the problem of how to select the best available access network for a given network user connection. For the integrated platform of HWNs to be truly seamless and efficient, a robust and stable wireless access network selection algorithm is needed. To meet these challenges for the different mobile wireless communication network users, the NGWNs will have to provide a great leap in wireless network capacity, coverage, QoS, and radio resource utilization. Moving wireless communication networks (mobile hotspots) have been proposed as a solution to providing reliable QoS to high mobility users. In this thesis, an Adaptive Thinning Mobility Aware (ATMA) Call Admission Control (CAC) algorithm for improving the QoS and radio resource utilization of the mobile hotspot networks, which are of critical importance for communicating nodes in moving wireless networks is proposed

Access network selection schemes for multiple calls in next generation wireless networks

There is an increasing demand for internet services by mobile subscribers over the wireless access networks, with limited radio resources and capacity constraints. A viable solution to this capacity crunch is the deployment of heterogeneous networks. However, in this wireless environment, the choice of the most appropriate Radio Access Technology (RAT) that can Tsustain or meet the quality of service (QoS) requirements of users' applications require careful planning and cost efficient radio resource management methods. Previous research works on access network selection have focused on selecting a suitable RAT for a user's single call request. With the present request for multiple calls over wireless access networks, where each call has different QoS requirements and the available networks exhibit dynamic channel conditions, the choice of a suitable RAT capable of providing the "Always Best Connected" (ABC) experience for the user becomes a challenge. In this thesis, the problem of selecting the suitable RAT that is capable of meeting the QoS requirements for multiple call requests by mobile users in access networks is investigated. In addressing this problem, we proposed the use of Complex PRoprtional ASsesment (COPRAS) and Consensus-based Multi-Attribute Group Decision Making (MAGDM) techniques as novel and viable RAT selection methods for a grouped-multiple call. The performance of the proposed COPRAS multi-attribute decision making approach to RAT selection for a grouped-call has been evaluated through simulations in different network scenarios. The results show that the COPRAS method, which is simple and flexible, is more efficient in the selection of appropriate RAT for group multiple calls. The COPRAS method reduces handoff frequency and is computationally inexpensive when compared with other methods such as the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Simple Additive Weighting (SAW) and Multiplicative Exponent Weighting (MEW). The application of the proposed consensus-based algorithm in the selection of a suitable RAT for group-multiple calls, comprising of voice, video-streaming, and file-downloading has been intensively investigated. This algorithm aggregates the QoS requirement of the individual application into a collective QoS for the group calls. This new and novel approach to RAT selection for a grouped-call measures and compares the consensus degree of the collective solution and individual solution against a predefined threshold value. Using the methods of coincidence among preferences and coincidence among solutions with a predefined consensus threshold of 0.9, we evaluated the performance of the consensus-based RAT selection scheme through simulations under different network scenarios. The obtained results show that both methods of coincidences have the capability to select the most suitable RAT for a group of multiple calls. However, the method of coincidence among solutions achieves better results in terms of accuracy, it is less complex and the number of iteration before achieving the predefined consensus threshold is reduced. A utility-based RAT selection method for parallel traffic-streaming in an overlapped heterogeneous wireless network has also been developed. The RAT selection method was modeled with constraints on terminal battery power, service cost and network congestion to select a specified number of RATs that optimizes the terminal interface utility. The results obtained show an optimum RAT selection strategy that maximizes the terminal utility and selects the best RAT combinations for user's parallel-streaming for voice, video and file-download

Safe Intelligent Driver Assistance System in V2X Communication Environments based on IoT

In the modern world, power and speed of cars have increased steadily, as traffic continued to increase. At the same time highway-related fatalities and injuries due to road incidents are constantly growing and safety problems come first. Therefore, the development of Driver Assistance Systems (DAS) has become a major issue. Numerous innovations, systems and technologies have been developed in order to improve road transportation and safety. Modern computer vision algorithms enable cars to understand the road environment with low miss rates. A number of Intelligent Transportation Systems (ITSs), Vehicle Ad-Hoc Networks (VANETs) have been applied in the different cities over the world. Recently, a new global paradigm, known as the Internet of Things (IoT) brings new idea to update the existing solutions. Vehicle-to-Infrastructure communication based on IoT technologies would be a next step in intelligent transportation for the future Internet-of-Vehicles (IoV). The overall purpose of this research was to come up with a scalable IoT solution for driver assistance, which allows to combine safety relevant information for a driver from different types of in-vehicle sensors, in-vehicle DAS, vehicle networks and driver`s gadgets. This study brushed up on the evolution and state-of-the-art of Vehicle Systems. Existing ITSs, VANETs and DASs were evaluated in the research. The study proposed a design approach for the future development of transport systems applying IoT paradigm to the transport safety applications in order to enable driver assistance become part of Internet of Vehicles (IoV). The research proposed the architecture of the Safe Intelligent DAS (SiDAS) based on IoT V2X communications in order to combine different types of data from different available devices and vehicle systems. The research proposed IoT ARM structure for SiDAS, data flow diagrams, protocols. The study proposes several IoT system structures for the vehicle-pedestrian and vehicle-vehicle collision prediction as case studies for the flexible SiDAS framework architecture. The research has demonstrated the significant increase in driver situation awareness by using IoT SiDAS, especially in NLOS conditions. Moreover, the time analysis, taking into account IoT, Cloud, LTE and DSRS latency, has been provided for different collision scenarios, in order to evaluate the overall system latency and ensure applicability for real-time driver emergency notification. Experimental results demonstrate that the proposed SiDAS improves traffic safety

Advanced classification and time-series methods in marketing..

This collection of essays investigates diverse marketing issues ranging from customer retention to the elaboration of pan-European strategies, t hrough the use of advanced modeling techniques. This work follows two ma in streams of research, from the methodological viewpoint, but also with respect to the issues envisioned. As far as the methodology is concerne d, the first part concerns the development and the application of novel binary choice models that conceptually originated in the statistical mac hine learning literature. In turn, the second part is based on time-seri es analysis. In particular, we devote a special attention to the concept of Granger causality in the time and frequency domains. In addition to this unidirectional concept, we also use a measure of co-movement betwee n multiple time-series. Both parts also differ with respect to the issues envisioned. The main i nterest in the first part is customer retention and churn prediction. In the second part, we focus on the understanding of the similarities and divergences, as well as the mechanisms of interaction between the Europe an countries. In particular, we assess the predictive content of Busines s Tendency Surveys published by the European Commission, allowing for cr oss-country effects. In a second stage, we decompose this predictive con tent over the frequency band. Finally, we investigate to what extent the European countries exhibit homogeneous consumer confidence for various planning horizons and geographic regions. ------------------------------------------------------------------------ --------------------------

A Survey of Anticipatory Mobile Networking: Context-Based Classification, Prediction Methodologies, and Optimization Techniques

A growing trend for information technology is to not just react to changes, but anticipate them as much as possible. This paradigm made modern solutions, such as recommendation systems, a ubiquitous presence in today's digital transactions. Anticipatory networking extends the idea to communication technologies by studying patterns and periodicity in human behavior and network dynamics to optimize network performance. This survey collects and analyzes recent papers leveraging context information to forecast the evolution of network conditions and, in turn, to improve network performance. In particular, we identify the main prediction and optimization tools adopted in this body of work and link them with objectives and constraints of the typical applications and scenarios. Finally, we consider open challenges and research directions to make anticipatory networking part of next generation networks

Customer value assessment of Sichuan Mobile

The present research aims to contribute with the evaluation and a segmentation index criterion of the customer group value in order to improve knowledge to the telecommunication industry, in value assessment and in market subdivision based on customer value. This thesis gives practical instrument measure and guiding suggestions to a deeper customer value assessment, combining characteristics of the communication industry in China, based on outstanding domestic and foreign research results and taking the group customers of China Mobile Sichuan Company. A first brief crossing between theoretical backgrounds of customer value assessment, segmentation concept and group customer, allowed the selection and choices of the methodology and the variables that influence group customer value. The following empirical step complemented the development of the assessment index system to calculate the group customer value and the following cluster analysis. The results obtained included the industry experts' experience, which help the identification of the 14 factors that influence the group customer value and the data analysis from 2000 group customers, which has been extracted from the mobile BOSS system. Factor analysis and analytic hierarchy process (AHP) method are used to calculate weights of indexes. Finally, based on current value, potential value, social value and the total value, clusters with typical characteristics are discovered using K-means clustering method. And corresponding marketing strategy is put forward.Esta tese avalia o Valor de grupos de clientes, no âmbito da grande empresa chinesa de telecomunicações móveis, a Sichuan Mobile. O presente estudo contribui para a análise da avaliação e segmentação de grupos de clientes, nomeadamente no mercado das telecomunicações. Este, sugere, ainda, um instrumento prático de medida; um índice de medida do valor de grupo de clientes é proposto e construído com base em análise de dados secundários do sector e do mercado chinês e primários baseados opiniões de peritos do sector e de resposta a um inquérito dos grupos de clientes da China Mobile. Após uma breve revisão do enquadramento teórico de conceitos inseridos na Gestão do Marketing, como Valor do Cliente, Segmentação e cliente-grupo, foram analisadas e seleccionadas as opções metodológicas e as variáveis que podem influenciar a avaliação do valor de um grupo de clientes. O desenvolvimento do índice de ponderação do valor de grupo de clientes foi elaborado após vários passos. Em primeiro lugar foram identificados, junto de peritos do sector, 14 factores que influenciam a avaliação do valor de grupo de clientes; Depois, efectuou-se um inquérito a 2000 grupos de clientes, retirados do sistema móvel BOSS da empresa Sichuan Mobile. Por fim realizou-se à base de dados obtida análises estatísticas como Análise Factorial e de Hierarquia (AHP), métodos que permitiram obter a ponderação do índice. Finalmente, com base no índice de valor corrente, valor potencial, valor social e valor total foram identificados os clusters. A análise destes clusters permitiu ainda sugerir estratégias de marketing em adaptação a cada cluster

Radio Communications

In the last decades the restless evolution of information and communication technologies (ICT) brought to a deep transformation of our habits. The growth of the Internet and the advances in hardware and software implementations modified our way to communicate and to share information. In this book, an overview of the major issues faced today by researchers in the field of radio communications is given through 35 high quality chapters written by specialists working in universities and research centers all over the world. Various aspects will be deeply discussed: channel modeling, beamforming, multiple antennas, cooperative networks, opportunistic scheduling, advanced admission control, handover management, systems performance assessment, routing issues in mobility conditions, localization, web security. Advanced techniques for the radio resource management will be discussed both in single and multiple radio technologies; either in infrastructure, mesh or ad hoc networks

The detection and tracking of portable GSM handset using a 5-element circular array

Includes bibliographical references (leaves 130-131)Direction Finding (OF) is a process that involves estimating the directions of the arrival for propagating wavefronts impinging on an antenna array from arbitrary directions relative to that antenna array. By understanding how the signals captured relate to the geometry of the OF antenna, one can separate out these signals spatially, and provide their directions of arrival with some degree of certainty. GSM, the Global System for Mobile Communications is a mobile digital communications system which has rapidly gained acceptance on a global scale since the early 1990s. Because the communications standard is made use of throughout the world today, it would be desirable to investigate the feasibility of the detection and tracking of such signals as an extension for OF platforms that are used by monitoring authorities such as the police or service providers. This thesis presents and discusses the implications of detecting and tracking GSM mobile handsets. Because the thesis was commissioned by a company that already manufactures broadband surveillance equipment with a particular OF implementation, the thesis approaches the problem with their specific implementation in mind assessing its competency in detecting and tracking GSM mobile phones. To understand the nature of GSM, a simulator was developed to convey information about the structure of the datasets that would be recorded in the field, and is compared to datasets captured with the OF equipment. Conclusions are drawn from the recordings, and recommendations for future work in this field are discussed