Understanding mobile network quality and infrastructure with user-side measurements

Measurement collection is a primary step towards analyzing and optimizing performance of a telecommunication service. With an Mobile Broadband (MBB) network, the measurement process has not only to track the network’s Quality of Service (QoS) features but also to asses a user’s perspective about its service performance. The later requirement leads to “user-side measurements” which assist in discovery of performance issues that makes a user of a service unsatisfied and finally switch to another network. User-side measurements also serve as first-hand survey of the problem domain. In this thesis, we exhibit the potential in the measurements collected at network edge by considering two well-known approaches namely crowdsourced and distributed testbed-based measurements. Primary focus is on exploiting crowdsourced measurements while dealing with the challenges associated with it. These challenges consist of differences in sampling densities at different parts of the region, skewed and non-uniform measurement layouts, inaccuracy in sampling locations, differences in RSS readings due to device-diversity and other non-ideal measurement sampling characteristics. In presence of heterogeneous characteristics of the user-side measurements we propose how to accurately detect mobile coverage holes, to devise sample selection process so to generate a reliable radio map with reduced sample cost, and to identify cellular infrastructure at places where the information is not public. Finally, the thesis unveils potential of a distributed measurement test-bed in retrieving performance features from domains including user’s context, service content and network features, and understanding impact from these features upon the MBB service at the application layer. By taking web-browsing as a case study, it further presents an objective web-browsing Quality of Experience (QoE) model

Cognitive Radio Systems

Cognitive radio is a hot research area for future wireless communications in the recent years. In order to increase the spectrum utilization, cognitive radio makes it possible for unlicensed users to access the spectrum unoccupied by licensed users. Cognitive radio let the equipments more intelligent to communicate with each other in a spectrum-aware manner and provide a new approach for the co-existence of multiple wireless systems. The goal of this book is to provide highlights of the current research topics in the field of cognitive radio systems. The book consists of 17 chapters, addressing various problems in cognitive radio systems

Smart Monitoring and Control in the Future Internet of Things

The Internet of Things (IoT) and related technologies have the promise of realizing pervasive and smart applications which, in turn, have the potential of improving the quality of life of people living in a connected world. According to the IoT vision, all things can cooperate amongst themselves and be managed from anywhere via the Internet, allowing tight integration between the physical and cyber worlds and thus improving efficiency, promoting usability, and opening up new application opportunities. Nowadays, IoT technologies have successfully been exploited in several domains, providing both social and economic benefits. The realization of the full potential of the next generation of the Internet of Things still needs further research efforts concerning, for instance, the identification of new architectures, methodologies, and infrastructures dealing with distributed and decentralized IoT systems; the integration of IoT with cognitive and social capabilities; the enhancement of the sensing–analysis–control cycle; the integration of consciousness and awareness in IoT environments; and the design of new algorithms and techniques for managing IoT big data. This Special Issue is devoted to advancements in technologies, methodologies, and applications for IoT, together with emerging standards and research topics which would lead to realization of the future Internet of Things

Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications

Applications

Volume 3 describes how resource-aware machine learning methods and techniques are used to successfully solve real-world problems. The book provides numerous specific application examples: in health and medicine for risk modelling, diagnosis, and treatment selection for diseases in electronics, steel production and milling for quality control during manufacturing processes in traffic, logistics for smart cities and for mobile communications

Contemporary Robotics

This book book is a collection of 18 chapters written by internationally recognized experts and well-known professionals of the field. Chapters contribute to diverse facets of contemporary robotics and autonomous systems. The volume is organized in four thematic parts according to the main subjects, regarding the recent advances in the contemporary robotics. The first thematic topics of the book are devoted to the theoretical issues. This includes development of algorithms for automatic trajectory generation using redudancy resolution scheme, intelligent algorithms for robotic grasping, modelling approach for reactive mode handling of flexible manufacturing and design of an advanced controller for robot manipulators. The second part of the book deals with different aspects of robot calibration and sensing. This includes a geometric and treshold calibration of a multiple robotic line-vision system, robot-based inline 2D/3D quality monitoring using picture-giving and laser triangulation, and a study on prospective polymer composite materials for flexible tactile sensors. The third part addresses issues of mobile robots and multi-agent systems, including SLAM of mobile robots based on fusion of odometry and visual data, configuration of a localization system by a team of mobile robots, development of generic real-time motion controller for differential mobile robots, control of fuel cells of mobile robots, modelling of omni-directional wheeled-based robots, building of hunter- hybrid tracking environment, as well as design of a cooperative control in distributed population-based multi-agent approach. The fourth part presents recent approaches and results in humanoid and bioinspirative robotics. It deals with design of adaptive control of anthropomorphic biped gait, building of dynamic-based simulation for humanoid robot walking, building controller for perceptual motor control dynamics of humans and biomimetic approach to control mechatronic structure using smart materials

Combining wearables and nearables for patient state analysis

Recently, ambient patient monitoring using wearable and nearable sensors is becoming more prevalent, especially in the neurodegenerative (Rett syndrome) and sleep disorder (Obstructive sleep apnea) populations. While wearables capture localized physiological data such as pulse rate, wrist acceleration and brain signals, nearables record global passive data including body movements, ambient sound and environmental variables. Together, wearables and nearables provide a more comprehensive understanding of the patient state. The processing of data captured from wearables and nearables have multiple challenges including handling missing data, time synchronization between sensors and developing data fusion techniques for multimodal analysis. The research described in this thesis addresses these issues while working on data captured in the wild. First, we describe a Rett syndrome severity estimator using a wearable biosensor and uncover physio-motor biomarkers. Second, we present the applications of an edge computing and ambient data capture system for home and clinical environments. Finally, we describe a transfer learning and multimodal data fusion based sleep-wake detector for a mixed-disorder elderly population. We show that combining data from wearables and nearables improves the performance of sleep-wake detection in terms of the F1-score and the Cohen’s kappa compared to the unimodal models.Ph.D