Interpolation and extrapolation methods for WLAN-based positioning

WLAN-based positioning is obtaining more and more attention in the research field no-wadays. In order to create better Location Based Services (LBSs), the demand to achieve higher user location accuracy is increasing. This thesis aims at studying the ef-fect of different interpolation and extrapolation methods in the WLAN-based indoor positioning, based on collected WLAN data. Depending on the embraced positioning method, there are various errors in WLAN-based positioning, such as calibration error, measurement errors, shadowing, etc. The motivation of this work came from trying to decrease the positioning error in the ab-sence of complete information about the indoor environment. This can be done by using interpolation and extrapolation methods, which are widely used in image processing nowadays. However, they are also an available and efficient way to deal with WLAN-based positioning studies. Among interpolation methods, Delaunay triangulation can partly avoid introducing dis-tortions in the measurement databases. Therefore, it makes sense to investigate triangula-tion based methods and to study their usefulness in the WLAN context. Practically, it is very hard to extrapolate appropriately and the implementation of the extrapolation is much more complex than the one of the interpolation. Thus in this thesis, simple extrapo-lation methods have been performed. The results here are based on measurement data. The performance of each method is analyzed in terms of the error between the received signal strengths (RSS) coming from the measurements and the RSS obtained through interpolation and extrapolation. WLAN data was collected from several buildings of Tampere University of Technology. Results show that extrapolation methods may increase the RSS estimation error some-times because it is very hard to predict the outside range. However, with more accurate extrapolation, the error would decrease. The performances of natural neighbor, linear and cubic interpolation are similar. The highest impact on RSS estimation comes from the extrapolation

Short-term spectrum sharing with economic awareness in 5G networks

University of Technology Sydney. Faculty of Engineering and Information Technology.The next Generation Mobile Networks 5G is expected to start rolling out by 2020, targeting at significantly faster mobile data speeds and increasingly massive machine communications. As we are entering into a whole new wireless time, where the blend of spectrum policy and technology becomes more important, the networking practices are tightly coupled with economic considerations. Therefore, a novel economic-driven spectrum policy should be designed to support all spectrum access methods with flexibility to take advantage of potentially new spectrum sharing paradigms. In this thesis, we present the feasibility of putting economic models in the existing dynamic spectrum sharing architectures, from three aspects: spectrum sublicensing at a small scale, spectrum auction design, and licensed and unlicensed band selection. We point out the challenges under each scenario and propose solutions to address these problems. First, for the spectrum sublicensing, we introduce the concept of the protection zone to enable multiple operators to spatially share the spectrum and ensure exclusive usage without any interference. Furthermore, the trade-off between the precision of boundary estimation and the cost of sensing networks is analysed. Second, for the spectrum auction, we study how an interference graph influences performance of the auction algorithm and guarantees fairness and truthfulness. Additionally, we further propose a negotiable auction for a more efficient spectrum allocation based on a mixed graph which offers a base station a second chance if the original request is rejected. Unlike the existing work, our proposed solution with a faster grouping scheme performs better in a dense situation, hence it accommodates more base stations. Third, for the licensed and unlicensed band selection from the perspective of operators, we build a finite game and present performance comparisons of different strategies. Moreover, the analysis of the Nash equilibrium is provided and so are the suggestions on how to achieve high benefits for different scales of operators. We apply our design and findings to the potential spectrum sharing architectures, i.e., Licensed Shared Access and Spectrum Sharing System. We strengthen the coupling of the sublicensing scheme with the spectrum sharing platforms by enabling each base station as an individual bidder and let them bid for a contour based sublicense, ensuring the exclusive right and interference protection. Additionally, we also analyse the unlicensed and licensed band selection from the perspective of operators and prove the equilibrium existence in the spectrum market. In conclusion, the short-term sublicensing in the secondary market has not been fully studied and put into practice yet. The thesis has given rise to an integration of spectrum technology and policy. It is believed that, in the future, the economic-aware spectrum policy design could be incorporated into communication technology to realize an innovative, efficient and flexible sharing model

Application of cognitive radio based sensor network in smart grids for efficient, holistic monitoring and control.

Doctoral Degree. University of KwaZulu-Natal, Durban.This thesis is directed towards the application of cognitive radio based sensor network (CRSN) in smart grid (SG) for efficient, holistic monitoring and control. The work involves enabling of sensor network and wireless communication devices for spectra utilization via the capability of Dynamic Spectrum Access (DSA) of a cognitive radio (CR) as well as end to end communication access technology for unified monitoring and control in smart grids. Smart Grid (SG) is a new power grid paradigm that can provide predictive information and recommendations to utilities, including their suppliers, and their customers on how best to manage power delivery and consumption. SG can greatly reduce air pollution from our surrounding by renewable power sources such as wind energy, solar plants and huge hydro stations. SG also reduces electricity blackouts and surges. Communication network is the foundation for modern SG. Implementing an improved communication solution will help in addressing the problems of the existing SG. Hence, this study proposed and implemented improved CRSN model which will help to ultimately evade the inherent problems of communication network in the SG such as: energy inefficiency, interference, spectrum inefficiencies, poor quality of service (QoS), latency and throughput. To overcome these problems, the existing approach which is more predominant is the use of wireless sensor network (WSNs) for communication needs in SG. However, WSNs have low battery power, low computational complexity, low bandwidth support, and high latency or delay due to multihop transmission in existing WSN topology. Consequently, solving these problems by addressing energy efficiency, bandwidth or throughput, and latency have not been fully realized due to the limitations in the WSN and the existing network topology. Therefore, existing approach has not fully addressed the communication needs in SG. SG can be fully realized by integrating communication network technologies infrastructures into the power grid. Cognitive Radio-based Sensor Network (CRSN) is considered a feasible solution to enhance various aspects of the electric power grid such as communication with end and remote devices in real-time manner for efficient monitoring and to realize maximum benefits of a smart grid system. CRSN in SG is aimed at addressing the problem of spectrum inefficiency and interference which wireless sensor network (WSN) could not. However, numerous challenges for CRSNs are due to the harsh environmental wireless condition in a smart grid system. As a result, latency, throughput and reliability become critical issues. To overcome these challenges, lots of approaches can be adopted ranging from integration of CRSNs into SGs; proper implementation design model for SG; reliable communication access devices for SG; key immunity requirements for communication infrastructure in SG; up to communication network protocol optimization and so on. To this end, this study utilized the National Institute of Standard (NIST) framework for SG interoperability in the design of unified communication network architecture including implementation model for guaranteed quality of service (QoS) of smart grid applications. This involves virtualized network in form of multi-homing comprising low power wide area network (LPWAN) devices such as LTE CAT1/LTE-M, and TV white space band device (TVBD). Simulation and analysis show that the performance of the developed modules architecture outperforms the legacy wireless systems in terms of latency, blocking probability, and throughput in SG harsh environmental condition. In addition, the problem of multi correlation fading channels due to multi antenna channels of the sensor nodes in CRSN based SG has been addressed by the performance analysis of a moment generating function (MGF) based M-QAM error probability over Nakagami-q dual correlated fading channels with maximum ratio combiner (MRC) receiver technique which includes derivation and novel algorithmic approach. The results of the MATLAB simulation are provided as a guide for sensor node deployment in order to avoid the problem of multi correlation in CRSN based SGs. SGs application requires reliable and efficient communication with low latency in timely manner as well as adequate topology of sensor nodes deployment for guaranteed QoS. Another important requirement is the need for an optimized protocol/algorithms for energy efficiency and cross layer spectrum aware made possible for opportunistic spectrum access in the CRSN nodes. Consequently, an optimized cross layer interaction of the physical and MAC layer protocols using various novel algorithms and techniques was developed. This includes a novel energy efficient distributed heterogeneous clustered spectrum aware (EDHC- SA) multichannel sensing signal model with novel algorithm called Equilateral triangulation algorithm for guaranteed network connectivity in CRSN based SG. The simulation results further obtained confirm that EDHC-SA CRSN model outperforms conventional ZigBee WSN in terms of bit error rate (BER), end-to-end delay (latency) and energy consumption. This no doubt validates the suitability of the developed model in SG

Real-time spatial modeling to detect and track resources on construction sites

For more than 10 years the U.S. construction industry has experienced over 1,000 fatalities annually. Many fatalities may have been prevented had the individuals and equipment involved been more aware of and alert to the physical state of the environment around them. Awareness may be improved by automatic 3D (three-dimensional) sensing and modeling of the job site environment in real-time. Existing 3D modeling approaches based on range scanning techniques are capable of modeling static objects only, and thus cannot model in real-time dynamic objects in an environment comprised of moving humans, equipment, and materials. Emerging prototype 3D video range cameras offer another alternative by facilitating affordable, wide field of view, automated static and dynamic object detection and tracking at frame rates better than 1Hz (real-time). This dissertation presents an imperical work and methodology to rapidly create a spatial model of construction sites and in particular to detect, model, and track the position, dimension, direction, and velocity of static and moving project resources in real-time, based on range data obtained from a three-dimensional video range camera in a static or moving position. Existing construction site 3D modeling approaches based on optical range sensing technologies (laser scanners, rangefinders, etc.) and 3D modeling approaches (dense, sparse, etc.) that offered potential solutions for this research are reviewed. The choice of an emerging sensing tool and preliminary experiments with this prototype sensing technology are discussed. These findings led to the development of a range data processing algorithm based on three-dimensional occupancy grids which is demonstrated in detail. Testing and validation of the proposed algorithms have been conducted to quantify the performance of sensor and algorithm through extensive experimentation involving static and moving objects. Experiments in indoor laboratory and outdoor construction environments have been conducted with construction resources such as humans, equipment, materials, or structures to verify the accuracy of the occupancy grid modeling approach. Results show that modeling objects and measuring their position, dimension, direction, and speed had an accuracy level compatible to the requirements of active safety features for construction. Results demonstrate that video rate 3D data acquisition and analysis of construction environments can support effective detection, tracking, and convex hull modeling of objects. Exploiting rapidly generated three-dimensional models for improved visualization, communications, and process control has inherent value, broad application, and potential impact, e.g. as-built vs. as-planned comparison, condition assessment, maintenance, operations, and construction activities control. In combination with effective management practices, this sensing approach has the potential to assist equipment operators to avoid incidents that result in reduce human injury, death, or collateral damage on construction sites.Civil, Architectural, and Environmental Engineerin