Tese de mestrado integrado. Engenharia Electrotécnica e de Computadores - Major de Telecomunicações. Faculdade de Engenharia. Universidade do Porto. 2008

Tese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto. 2010

Estágio realizado no INESC Porto / Tese de mestrado integrado. Engenharia Informática e Computação. Faculdade de Engenharia. Universidade do Porto. 2009

Virtually every industry and discipline (e.g., mining, pharmaceutical, construction, agriculture, reclamation, etc.) is finding applications for wireless data acquisition for monitoring and managing processes and resources. Two sectors, namely agriculture and environmental research, are seeking ways to obtain distributed soil and plant measurements over larger areas like a watershed or large fields rather than a single site of intensive instrumentation (i.e., a weather station). Wireless sensor networks and remote sensing have been explored as a means to satisfy this need. Commercial products are readily available that have remote wireless options to support distributed senor networking. However, these systems have been designed with a field engineer or technician as the target end-user. Equipment and operating costs, device specific programming languages, and complex wireless configuration schemes have impeded the adoption of large-scale, multi-node wireless systems in these fields. This report details the development of an easy-to-use, ultra-low power wireless datalogger incorporating a scalable, intelligent data collection and transmission topology. The final product can interface to various sensor types including SDI-12 and uses an LCD display to help simplify device setup.

The number of users who get access to wireless links is increasing each day and many new applications require very high data rates. The increasing demand for higher data rates has led to the development of new techniques to increase spectrum efficiency to achieve this goal. However, the limited bandwidth of the frequency bands that are currently used for wireless communication bounds the maximum data rate possible. In the past few years, researchers have developed new devices that work as Terahertz (THz) transmitters and receivers. The development of these devices and the large available bandwidth of the THz band is a possible solution to this ever increasing demand. However, THz communication is still in its infancy and more research needs to be done to bring THz technology into every day life. In this research, we study wireless THz communication systems. As the first step, we conducted detailed channel measurements to study and analyze the characteristics of THz signals under different channel conditions. These propagation models mimic the behavior of THz signals in real applications. Then we use these models to study appropriate modulation methods for directional and omni-directional THz channels. We also use pulsed THz signals in wireless communication channels to send data at a very high rate. We have developed rate adaptation algorithms to allow multiple users to share the same THz channel for downlink applications while fairness is maintained among them.

Large enterprises are often interested in tracking objects and people within buildings to improve resource allocation and occupant experience. Infrastructure-based indoor positioning systems (IIPS) can provide this service at low-cost by leveraging already deployed Wi-Fi infrastructure. Typically, IIPS perform localization and tracking of devices by measuring only Wi-Fi signals at wireless access points and do not rely on inertial sensor data at mobile devices (e.g., smartphones), which would require explicit user consent and sensing capabilities of the devices. Despite these advantages, building an economically viable cost-effective IIPS that can accurately and simultaneously track many devices over very large buildings is difficult due to three main challenges. First, Wi-Fi signal measurements are extremely noisy due to unpredictable multipath propagation and signal attenuation. Second, as the IIPS obtain measurements in a best effort manner without requiring any applications installed on a tracked device, the measurements are temporally sparse and non-periodic, which makes it difficult to exploit historical measurements. Third, the cost-effective IIPS have limited computational resources, in turn limiting scalability in terms of the number of simultaneously tracked devices. Prior approaches have narrowly focused on either improving the accuracy or reducing the complexity of localization algorithms. To compute the location at the current time step, they typically use only the latest explicit Wi-Fi measurements (e.g., signal strengths). The novelty of our approach lies in considering contexts of a device that can provide useful indications of the device's location. One such example of context is device motion. It indicates whether or not the device's location has changed. For a stationary device, the IIPS can either skip expensive device localization or aggregate noisy, temporally sparse location estimates to improve localization accuracy. Another example of context applicable to a moving device is a floor map that consists of pre-defined path segments that a user can take. The map can be leveraged to constrain noisy, temporally sparse location estimates on the paths. The thesis of this dissertation is that embedding context-aware capabilities in the IIPS enhances its performance in tracking many devices simultaneously and accurately. Specifically, we develop motion detection and map matching to show the benefits of leveraging two critical contexts: device motion and floor map. Providing motion detection and map matching is non-trivial in the IIPS where we must rely only on data from the Wi-Fi infrastructure. This thesis makes two contributions. First, we develop feature-based and deep learning-based motion detection models that exploit temporal patterns in Wi-Fi measurements across different access points to classify device motion in real time. Our extensive evaluations on datasets from real Wi-Fi deployments show that our motion detection models can detect device motion accurately. This, in turn, allows the IIPS to skip repeated location computation for stationary devices or improve the accuracy of localizing these devices. Second, we develop graph-based and image-based map matching models to exploit floor maps. The novelty of the graph-based approach lies in applying geometric and topological constraints to select which path segment to align the current location estimate. Our graph-based map matching can align a location estimate of a user device on the path taken by the user and close to the user's current location. The novelty of the image-based approach lies in representing for the first time, input data including location estimates and the floor map as 2D images. This novel representation enables the design, development, and application of encoder-decoder neural networks to exploit spatial relationships in input images to potentially improve location accuracy. In our evaluation, we show that the image-based approach can improve location accuracy with large simulated datasets, compared to the graph-based approach. Together, these contributions enable improvement of the IIPS in its ability to accurately and simultaneously track many devices over large buildings.

Mobile wireless sensor networks (MWSNs) will enable information systems to gather detailed information about the environment on an unprecedented scale. These selforganising, distributed networks of sensors, processors and actuators that are capable of movement have a broad range of potential applications, including military reconnaissance, surveillance, planetary exploration and geophysical mapping. In many of the foreseen applications a certain geometric pattern will be required for the task. Hence, algorithms for maintaining the geometric pattern of an MWSN are investigated. In many tasks such as land mine detection, a group of nodes arranged in a line must provide continuous coverage between each end of the formation. Thus, we present algorithms for maintaining the geometric pattern of a group of nodes arranged in a line. An MWSN may also need to form a geometric pattern without assistance from the user. In military reconnaissance, for example, the nodes will be dropped onto the battlefield from a plane and land at random positions. The nodes will be expected to arrange themselves into a predetermined formation in order to perform a specific task. Thus, we present algorithms for forming a circle and regular polygon from a given set of random positions. The algorithms are distributed and use no communication between the nodes to minimise energy consumption. Unlike past studies of geometric problems where algorithms are either tested in simulations where each node has global knowledge of all the other nodes or implemented on a small number of robots, the robustness of our algorithms has been studied with simulations that model the sensor system in detail. / The nodes locate their neighbours using simulated vision where a ray-tracer is used to generate images of a model of the scene that would be captured by each node's cameras. The simulations demonstrate that the algorithms are robust against random errors in the sensors and actuators. Even though the nodes had incomplete knowledge of the positions of other nodes due to occlusion, they were still able to perform the assigned tasks.

Doctor of Philosophy(PhD) / Recent advances in miniaturization and low power design have led to a flurry of activity in wireless sensor networks. Sensor networks have different constraints than traditional wired networks. A wireless sensor network is a special network with large numbers of nodes equipped with embedded processors, sensors, and radios. These nodes collaborate to accomplish a common task such as environment monitoring or asset tracking. In many applications, sensor nodes will be deployed in an ad-hoc fashion without careful planning. They must organize themselves to form a multihop, wireless communication network. In sensor network environments, much research has been conducted in areas such as power consumption, self-organisation techniques, routing between the sensors, and the communication between the sensor and the sink. On the other hand, real-time communication with the Quality of Service (QoS) concept in wireless sensor networks is still an open research field. Most protocols either ignore real time or simply attempt to process as fast as possible and hope that this speed is sufficient to meet the deadline. However, the introduction of real-time communication has created additional challenges in this area. The sensor node spends most of its life routing packets from one node to another until the packet reaches the sink; therefore, the node functions as a small router most of the time. Since sensor networks deal with time-critical applications, it is often necessary for communication to meet real time constraints. However, research that deals with providing QoS guarantees for real-time traffic in sensor networks is still in its infancy.This thesis presents a real-time communication framework to provide quality of service in sensor networks environments. The proposed framework consists of four components: First, present an analytical model for implementing Priority Queuing (PQ) in a sensor node to calculate the queuing delay. The exact packet delay for corresponding classes is calculated. Further, the analytical results are validated through an extensive simulation study. Second, report on a novel analytical model based on a limited service polling discipline. The model is based on an M/D/1 queuing system (a special class of M/G/1 queuing systems), which takes into account two different classes of traffic in a sensor node. The proposed model implements two queues in a sensor node that are served in a round robin fashion. The exact queuing delay in a sensor node for corresponding classes is calculated. Then, the analytical results are validated through an extensive simulation study. Third, exhibit a novel packet delivery mechanism, namely the Multiple Level Stateless Protocol (MLSP), as a real-time protocol for sensor networks to guarantee the traffic in wireless sensor networks. MLSP improves the packet loss rate and the handling of holes in sensor network much better than its counterpart, MMSPEED. It also introduces the k-limited polling model for the first time. In addition, the whole sending packets dropped significantly compared to MMSPEED, which it leads to decrease the consumption power. Fourth, explain a new framework for moving data from the sink to the user, at a low cost and low power, using the Universal Mobile Telecommunication System (UMTS), which is standard for the Third Generation Mobile System (3G). The integration of sensor networks with the 3G mobile network infrastructure will reduce the cost of building new infrastructures and enable the large-scale deployment of sensor networks

Due to the enormous capacity and performance gains associated with the use of antenna arrays in wireless multi-input multi-output (MIMO) communication links, it is inevitable that these technologies will become an integral part of future systems. In order to assess the potential of such beam-oriented technologies, direct representation of the dispersion of multipath fading channel in angular and temporal domains is required. This representation can only be achieved with the use of spatial channel models. This thesis thus focuses on the issue of spatial channel modeling for cellular systems and on its use in the characteri- zation of multipath fading channels. The results of this thesis are presented mainly in five parts: a) modeling of scattering mechanisms, b) derivation of the closed-form expressions for the spatio-temporal characteristics, c) generalization of the quantitative measure of angular spread, d) investigation of the effect of mobile motion on the spatio-temporal characteris- tics, and e) characterization of fast fading channel and its use in the signature sequence adaptation for direct sequence code division multiple access (DS-CDMA) system. The thesis begins with an overview of the fundamentals of spatial channel modeling with regards to the specifics of cellular environments. Previous modeling approaches are dis- cussed intensively and a generalized spatial channel model, the 'Eccentro-Scattering Model' is proposed. Using this model, closed-form mathematical expressions for the distributions of angle and time of multipath arrival are derived. These theoretical results for the picocell, microcell and macrocell environments, when compared with previous models and available measurements, are found to be realistic and generic. In macrocell environment, the model incorporates the effect of distant scattering structures in addition to the local ones. Since the angular spread is a key factor of the second order statistics of fading processes in wireless communications, the thesis proposes a novel generalized method of quantifying the angular spread of the multipath power distribution. The proposed method provides almost all parameters about the angular spread, which can be further used for calculating more accurate spatial correlations and other statistics of multipath fading channels. The degree of accuracy in such correlation calculations can lead to the computation of exact separation distances among array elements required for maximizing capacity in MIMO systems or diversity antennas. The proposed method is also helpful in finding the exact standard deviation of the truncated angular distributions and angular data acquired in measurement campaigns. This thesis also indicates the significance of the effects of angular distribution truncation on the angular spread. Due to the importance of angular spread in the fading statistics, it is proposed as the goodness-of-fit measure in measurement campaigns. In this regard, comparisons of some notable azimuthal models with the measurement results are shown. The effect of mobile motion on the spatial and temporal characteristics of the channel is also discussed. Three mobile motion scenarios are presented, which can be considered to be responsible for the variations of the spatio-temporal statistical parameters of the multipath signals. Two different cases are also identified, when the terrain and clutter of the mobile surroundings have an additional effect on the temporal spread of the channel during mobile motion. The effect of increasing mobile-base separation on the angular and temporal spreads is elaborated in detail. The proposed theoretical results in spatial characteristics can be extended to characterizing and tracking transient behavior of Doppler spread in time-varying fast fading channels; likewise the proposed theoretical results in temporal characteristics can be utilized in designing efficient equalizers for combating inter-symbol interference (ISI) in time-varying frequency-selective fading channels. In the last part of the thesis, a linear state-space model is developed for signature sequence adaptation over time-varying fast fading channels in DS-CDMA systems. A decision directed adaptive algorithm, based on the proposed state-space model and Kalman filter, is presented. The algorithm outperforms the gradient-based algorithms in tracking the received distorted signature sequence over time-varying fast fading channels. Simulation results are presented which show that the performance of a linear adaptive receiver can be improved significantly with signature tracking on high Doppler spreads in DS-CDMA systems.

Telecommunication has experienced significant changes over the past few years and its paradigm has moved from wired to wireless communications. The wireless channel constitutes the basic physical link between the transmitter and the receiver antennas. Therefore, complete knowledge of the wireless channel and radio propagation environment is necessary in order to design efficient wireless communication systems. This PhD thesis is devoted to studying the spatial and temporal statistics of the wireless channel in cellular environments based on a geometry-based stochastic physical channel modeling approach. Contributions in this thesis report include the following: ??? A new physical channel model called the eccentro-scattering model is proposed to study the spatial and temporal statistics of the multipath signals in cellular environments. ??? Generic closed-form formulas for the probability density function (pdf) of angle of arrival (AoA) and time of arrival (ToA) of the multipath signals in each cellular environment are derived. These formulas can be helpful for the design and evaluation of modern communication systems. ??? A new Gaussian scattering model is proposed, which consists of two Gaussian functions for the distribution of scatterers around base station (BS) and mobile station (MS) and confines these scatterers within a scattering disc. ??? The effect of mobile motion on the spatial and temporal statistics of the multipath signals in cellular environments is discussed. Three motion scenarios are considered for the possible trajectory of the mobile unit. Furthermore, two different cases are identified when the terrain and clutter of mobile surrounding have additional effect on the temporal spread of the multipath signals during motion. ??? The physical channel model is employed to assess the performance of a RAKE receiver in cellular environments. ??? Comparisons between uniform scattering and Gaussian scattering, which are the two assumptions for the distribution of scatterers usually used in the derivation of the pdf of AoA, are also presented. ??? An overview of earlier physical channel models and comparisons between these models and with the proposed model are presented.