Site-Specific Propagation Loss Prediction in 4.9 GHz Band Outdoor-to-Indoor Scenario

Owing to the widespread use of smartphones and various cloud services, user traffic in cellular networks is rapidly increasing. Especially, the traffic congestion is severe in urban areas, and effective service-cell planning is required in the area for efficient radio resource usage. Because many users are also inside high buildings in the urban area, the knowledge of propagation loss characteristics in the outdoor-to-indoor (O2I) scenario is indispensable for the purpose. The ray-tracing simulation has been widely used for service-cell planning, but it has a problem that the propagation loss tends to be underestimated in a typical O2I scenario in which the incident radio waves penetrate indoors through building windows. In this paper, we proposed the extension method of the ray-tracing simulation to solve the problem. In the proposed method, the additional loss factors such as the Fresnel zone shielding loss and the transmission loss by the equivalent dielectric plate were calculated for respective rays to eliminate the penetration loss prediction error. To evaluate the effectiveness of the proposed method, we conducted radio propagation measurements in a high-building environment by using the developed unmanned aerial vehicle (UAV)-based measurement system. The results showed that the penetration loss of direct and reflection rays was significantly underestimated in the ray-tracing simulation and the proposed method could correct the problem. The mean prediction error was improved from 7.0 dB to &minus 0.5 dB, and the standard deviation was also improved from 8.2 dB to 5.3 dB. The results are expected to be utilized for actual service-cell planning in the urban environment. Document type: Articl

Indoor Localization based on Time-of-Flight Fingerprinting

학위논문 (석사)-- 서울대학교 대학원 : 컴퓨터공학과, 2015. 2. 김종권.The emerging of a positioning/localization system allows user to track their position in real-time by using a knowledge of radio frequency signal (RF). Global Positioning System (GPS) is the most famous outdoor localization system with leveraging RF signal from satellites. Even though it has been widely used in many applications, it is not be able to localize in indoor environment such as building because the signal from satellite cannot penetrate inside and if it does, the signal power is not strong enough to maintain the connection. Many researchers have found a way to solve this issue by deliberately makes use of off-the-shelf wireless infrastructures such as Wi-Fi, and named these applications as Indoor Positioning System (IPS). IPS has been currently researched in a way that it should provide higher accuracy, centimeter to a few meter-scale, than outdoor system and more reliable. Ranging-based localization technique that is mainly used in GPS, turns out to be inapplicable in IPS because this technique relies on signal propagation time to estimate user’s location which is hardly to accurately measure in indoor environment due to strong multipath and hardware limitation of wireless devices, which is not optimized for specific purpose. Therefore, the feasible method goes to RSS-based fingerprinting where location is estimated by matching Received Signal Strength (RSS) profile with a database that contains the known locations with its profiles. However RSS profile is not robust and time-varying, causing large error in some scenario. This work presented a new way of fingerprinting–based localization by using Time-of-Flight (ToF) as a reference information instead of RSS. Theoretically speaking, ToF is better than RSS in term of reliability and accuracy because they are less time-varying and more robust than RSS. Moreover, measuring ToF does not require synchronization between access point and user device, thus it provides this system less complexity. Although, it is not a famous measurement when ToF is used in ranging-based localization where hardware limitation reduces accuracy significantly to 10 meters error, our approach has shown that it provides precisely localization when combining with fingerprinting technique. We have experimented various estimation method in order to find a better solution than basic fingerprinting algorithm where accuracy is limited by a gap between fingerprinting. We found that by using a knowledge of neighbor fingerprinting, it can achieve sub-optimal resolution than the basic algorithm. We evaluated the performance, and the result has shown that our work outperformed previous works.Abstract i Contents iv List of Figures vi 1. Chapter 1 Introduction 1 1.1 Background 1 1.2 Contribution 4 1.3 Thesis organization 5 2. Chapter 2 Related work 6 2.1 Fingerprinting approach 6 2.2 Ranging approach 7 3. Chapter 3 Indoor positioning system overview 9 3.1 Localization techniques 9 3.2 The Universal Software Radio Peripheral 18 3.3 GNU Radio 19 4. Chapter 4 System design 22 4.1 Motivation and goal 22 4.2 Design requirements 24 4.3 System overview 28 4.4 Time-of-Flight Measurement 30 4.5 Localization algorithm 36 5. Chapter 5 Evaluation 40 5.1 Simulation 40 5.2 Implementation 48 Chapter 6 Conclusion 52 Bibliography 54Maste