The Optimum Location for Access Point Deployment based on RSS for Indoor Communication

YesIn indoor wireless communication networks, the optimal locations had been known to deploy the access points (AP's) which has a significant impact on improving various aspects of network operation, management, and coverage. In addition, develop the behavioral characteristics of the wireless network. The most used approach for localization purposes was based on Received Signal Strength (RSS) measurements, which is widely used in the wireless network. As well as, it can be easily accessed from different operating systems. In this paper, we proposed an optimal AP localization algorithm based on RSS measurement obtained from different received points. This localization algorithm works as a complementary to the 3D Ray tracing model based REMCOM wireless InSite software and considered two-step localization approach, data collection phase, and localization phase. Obtained result give relatively high accuracy to select the optimum location for AP compare with other selected locations. It is worth to mention that effect of different building materials on signal propagation has been considered with specifying the optimum location of deployment. Furthermore, channel characterizations that based on path losses have been considered as a confirmation for the optimum location being selected

Modeling and Performance Evaluation of Bicycle-to-X Communication Networks

The growing connectivity of vehicles and Vulnerable Road Users, i.e., pedestrians and cyclists, allows to explore solutions based on wireless communication to support safety, efficiency and infotainment applications.However, there are few communication technologies that enjoy similar penetration ratios on cars, bicycles and pedestrians.WiFi is one of such technologies, as can be found in smart phones and in on-board hotspots.This thesis aims to characterize experimentally the wireless link performance and develop a model to estimate the received signal strength (RSS) between WiFi devices installed on bicycles and cars equipped with built-in WiFi APs.The RSS estimation model extends existing empirical models (e.g., the Log-Distance Path Loss model) by including the shadowing of the bicycle-and-cyclist system and of a vehicle.We first characterize the radiation pattern of antennas installed in several mounting points of a bicycle, in order to reduce the set of mounting points to be explored in future measurements.We then measured the radiation pattern of the bicycle and cyclist system, and the radiation pattern of a car with built-in and dedicated WiFi access points.Finally, we evaluate the performance of the model by comparing RSS estimates and measurements collected in selected interaction scenarios between bicycles and car: (i) bicycle overtaking a parked car, (ii) perpendicular crossing with LOS, and (iii) without LOS. We observed that 50% of the RSS estimates our model underestimates by less than are within 10 dBs of measured values about 50% of the RSSI values for the scenarios in LOS, and overestimates the RSSI values by more than 5 DBs about 75% of the RSSI values for the scenario containing obstructions

Experimental and analytical evaluation of multi-user beamforming in wireless LANs

Adaptive beamforming is a. powerful approach to receive or transmit signals of interest in a spatially selective way in the presence of interference and noise. Recently, there has been renewed interest in adaptive beamforming driven by applications in wireless communications, where multiple-input multiple-output (MEMO) techniques have emerged as one of the key technologies to accommodate the high number of users as well as the increasing demand for new high data rate services. Beamforming techniques promise to increase the spectral efficiency of next generation wireless systems and are currently being incorporated in future industry standards. Although a significant amount of research has focused on theoretical capacity analysis, little is known about the performance of such systems in practice. In thesis, I experimentally and analytically evaluate the performance of adaptive beamforming techniques on the downlink channel of a wireless LAN. To this end. I present the design and implementation of the first multi-user beam-forming system and experimental framework for wireless LANs. Next, I evaluate the benefits of such system in two applications. First, I investigate the potential of beamforming to increase the unicast throughput through spatial multiplexing. Using extensive measurements in an indoor environment, I evaluate the impact of user separation distance, user selection, and user population size on the multiplexing gains of multi-user beamforming. I also evaluate the impact of outdated channel information due to mobility and environmental variation on the multiplexing gains of multi-user beamforming. Further, I investigate the potential of beamforming to eliminate interference at unwanted locations and thus increase spatial reuse. Second, I investigate the potential of adaptive beamforming for efficient wireless multicasting. I address the joint problem of adaptive beamformer design at the PHY layer and client scheduling at the MAC layer by proposing efficient algorithms that are amenable to practical implementation. Next, I present the implementation of the beamforming based multicast system on the WARP platform and compare its performance against that of omni-directional and switched beamforming based multicast. Finally, I evaluate the performance of multicast beamforming under client mobility and infrequent channel feedback, and propose solutions that increase its robustness to channel dynamics

A Study about Heterogeneous Network Issues Management based on Enhanced Inter-cell Interference Coordination and Machine Learning Algorithms

Under the circumstance of fast growing demands for mobile data, Heterogeneous Networks (HetNets) has been considered as one of the key technologies to solve 1000 times mobile data challenge in the coming decade. Although the unique multi-tier topology of HetNets has achieved high spectrum efficiency and enhanced Quality of Service (QoS), it also brings a series of critical issues. In this thesis, we present an investigation on understanding the cause of HetNets challenges and provide a research on state of arts techniques to solve three major issues: interference, offloading and handover. The first issue addressed in the thesis is the cross-tier interference of HetNets. We introduce Almost Blank Subframes (ABS) to free small cell UEs from cross-tier interference, which is the key technique of enhanced Inter-Cell Interference Coordination (eICIC). Nash Bargain Solution (NBS) is applied to optimize ABS ratio and UE partition. Furthermore, we propose a power based multi-layer NBS Algorithm to obtain optimal parameters of Further enhanced Inter-cell Interference Coordination (FeICIC), which significantly improve macrocell efficiency compared to eICIC. This algorithm not only introduces dynamic power ratio but also defined opportunity cost for each layer instead of conventional zero-cost partial fairness. Simulation results show the performance of proposed algorithm may achieve up to 31.4% user throughput gain compared to eICIC and fixed power ratio FeICIC. This thesis’ second focusing issue is offloading problem of HetNets. This includes (1) UE offloading from macro cell and (2) small cell backhaul offloading. For first aspect, we have discussed the capability of machine learning algorithms tackling this challenge and propose the User-Based K-means Algorithm (UBKCA). The proposed algorithm establishes a closed loop Self-Organization system on our HetNets scenario to maintain desired offloading factor of 50%, with cell edge user factor 17.5% and CRE bias of 8dB. For second part, we further apply machine learning clustering method to establish cache system, which may achieve up to 70.27% hit-ratio and reduce request latency by 60.21% for Youtube scenario. K-Nearest Neighbouring (KNN) is then applied to predict new users’ content preference and prove our cache system’s suitability. Besides that, we have also proposed a system to predict users’ content preference even if the collected data is not complete. The third part focuses on offloading phase within HetNets. This part detailed discusses CRE’s positive effect on mitigating ping-pong handover during UE offloading, and CRE’s negative effect on increasing cross-tier interference. And then a modified Markov Chain Process is established to map the handover phases for UE to offload from macro cell to small cell and vice versa. The transition probability of MCP has considered both effects of CRE so that the optimal CRE value for HetNets can be achieved, and result for our scenario is 7dB. The combination of CRE and Handover Margin is also discussed

Improving the Performance of Wireless LANs

This book quantifies the key factors of WLAN performance and describes methods for improvement. It provides theoretical background and empirical results for the optimum planning and deployment of indoor WLAN systems, explaining the fundamentals while supplying guidelines for design, modeling, and performance evaluation. It discusses environmental effects on WLAN systems, protocol redesign for routing and MAC, and traffic distribution; examines emerging and future network technologies; and includes radio propagation and site measurements, simulations for various network design scenarios, numerous illustrations, practical examples, and learning aids

Hybrid Marker-less Camera Pose Tracking with Integrated Sensor Fusion

This thesis presents a framework for a hybrid model-free marker-less inertial-visual camera pose tracking with an integrated sensor fusion mechanism. The proposed solution addresses the fundamental problem of pose recovery in computer vision and robotics and provides an improved solution for wide-area pose tracking that can be used on mobile platforms and in real-time applications. In order to arrive at a suitable pose tracking algorithm, an in-depth investigation was conducted into current methods and sensors used for pose tracking. Preliminary experiments were then carried out on hybrid GPS-Visual as well as wireless micro-location tracking in order to evaluate their suitability for camera tracking in wide-area or GPS-denied environments. As a result of this investigation a combination of an inertial measurement unit and a camera was chosen as the primary sensory inputs for a hybrid camera tracking system. After following a thorough modelling and mathematical formulation process, a novel and improved hybrid tracking framework was designed, developed and evaluated. The resulting system incorporates an inertial system, a vision-based system and a recursive particle filtering-based stochastic data fusion and state estimation algorithm. The core of the algorithm is a state-space model for motion kinematics which, combined with the principles of multi-view camera geometry and the properties of optical flow and focus of expansion, form the main components of the proposed framework. The proposed solution incorporates a monitoring system, which decides on the best method of tracking at any given time based on the reliability of the fresh vision data provided by the vision-based system, and automatically switches between visual and inertial tracking as and when necessary. The system also includes a novel and effective self-adjusting mechanism, which detects when the newly captured sensory data can be reliably used to correct the past pose estimates. The corrected state is then propagated through to the current time in order to prevent sudden pose estimation errors manifesting as a permanent drift in the tracking output. Following the design stage, the complete system was fully developed and then evaluated using both synthetic and real data. The outcome shows an improved performance compared to existing techniques, such as PTAM and SLAM. The low computational cost of the algorithm enables its application on mobile devices, while the integrated self-monitoring, self-adjusting mechanisms allow for its potential use in wide-area tracking applications

Integrated Scheduling and Beam Steering for Spatial Reuse

This document describes an approach to integrating antenna selection and control into a time-division MAC scheduling process. I argue that through such integration it is possible to achieve greater spatial reuse and interference mitigation than by solving the two problems separately. Without coupling between the MAC scheduling and physical antenna configuration processes, a \u22chicken-and-egg\u22 problem exists: If antenna decisions are made before scheduling, they cannot be optimized for the communication that will actually occur. If, on the other hand, the scheduling decisions are made first, the scheduler cannot know what the actual interference and communications properties of the network will be. This dissertation presents algorithms for optimal spatial reuse TDMA scheduling with reconfigurable antennas. I present and solve the joint beam steering and scheduling problem for spatial reuse TDMA and describe an implemented system based on the algorithms developed. The algorithms described achieve up to a 600% speedup over TDMA in the experiments performed. This is based on using an optimization decomposition approach to arrive at a working distributed protocol which is equivalent to the original problem statement while also producing optimal solutions in an amount of time that is at worst linear in the size of the input. This is, to the best of my knowledge, the first actually implemented STDMA scheduling system based on dual decomposition. This dissertation identifies and briefly address some of the challenges that arise in taking such a system from theory to reality