실제 전파 환경을 반영한 이동통신 시스템의 최적화 연구

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2016. 8. 김성철.The 4th generation cellular systems, such as LTE (Long-Term Evolution) or LTEAdvanced, significantly improve the speed and the quality of data service as compared to the previous generation systems. In this situation, many applications generating a huge amount of mobile traffic (e.g., high definition (HD) video streaming or cloudbased storage services) have been widely spread. For this reason, the amount of mobile data traffic keeps increasing and sometimes even exceeds the capacity of the system. In order to accommodate explosively increasing mobile data traffic, service providers try to enhance the spatial reuse of wireless resources by deploying more base stations (BSs). Furthermore, small-sized BSs, such as pico and femto BSs, draw much attention as an economical and easy to deploy solution for relieving the load of macro BSs. In this dissertation, I investigate several strategies for optimizing the utilization of cellular systems. Especially, load balancing algorithms, which forcibly redirect users associated with a congested BS thereby experiencing low service quality to nearby BSs, are proposed. As a first step, I propose methods for predicting the service quality (or equivalently the long-term average throughput) of each individual user when multiple users share the same BS. During developing these algorithms, the time-varying characteristic of wireless channel due to multi-path propagation environment is considered to reflect real propagation environments. To this end, the fluctuation phenomenon of the received signal strength is expressed by a random variable, and then, two types of user throughput estimation schemes are developed. The proposed algorithms can be easily implemented in a practical system, and prediction errors are less than 10% for almost every case. Based on the proposed throughput estimation methods, I deal with a user association problem in multi-cell environments. At first, a centralized user association algorithm is developed, where a central node collects all the channel information between every BS and every user and then assigns an optimal base station to each individual user. However, transferring a lot of information to the central node requires excessive uplink feedback and backhaul usage. In addition, such overheads are increased with the density of BSs. For this reason, I propose a decentralized version of user association algorithm, where users themselves choose an optimal BS by considering not only their service quality but also network-wide utilization. The proposed decentralized algorithm especially can be compatible with heterogeneous cellular networks, where there are abundant BSs in the vicinity of each user. Finally, I study an inter-tier interference management problem between macro and small cell BSs in heterogeneous cellular networks. As the name indicates, small cell BSs are designed to consume much less power as compared to conventional macro BSs. For this reason, users associated with small cell BSs experience severe interference from macro BSs. To mitigate inter-tier interference, the eICIC (enhanced Inter Cell Interference Coordination) method was proposed. In this scheme, macro BSs periodically mute data transmission in order to guarantee the signal quality of users at the small cell BSs. In this dissertation, I try to optimize both user association and inter-tier interference management problems. As a result, users change their association and the system alters data transmission strategies in order to optimize network-wide utilization.Chapter 1 INTRODUCTION 1 Chapter 2 USER THROUGHPUT ESTIMATION FOR THE PF SCHEDULING ALGORITHM 5 2.1 Motivation 5 2.2 System Model 6 2.3 Throughput Estimation for a Single Antenna Scenario under the Rayleigh Fading Environment 9 2.4 Throughput Estimation for General Cases 13 2.4.1 Single User MIMO Scheduling Scenario 13 2.4.2 Multiuser MIMO Scheduling Scenario 14 2.5 Implementation Issues 15 2.6 Performance Evaluation and Discussion 16 2.6.1 Simulation Setup 16 2.6.2 Single Antenna Scenario 17 2.6.3 Multiple Antenna Scenario 20 Chapter 3 DYNAMIC USER ASSOCIATION IN MULTI-CELL CELLULAR NETWORKS 24 3.1 Motivation 24 3.2 System Model 25 3.3 Problem Formulation 27 3.3.1 Objective and Optimal Algorithm 27 3.3.2 User Association Problem 29 3.4 Centralized Dynamic User Association Algorithm 31 3.5 Performance Evaluation and Discussion 34 3.5.1 Simulation Setup 34 3.5.2 Throughput Estimation Error in Multi-cell Environments 36 3.5.3 Load Balancing Effect 37 Chapter 4 DECENTRALIZED USER ASSOCIATION METHOD IN HETEROGENEOUS CELLULAR NETWORKS 40 4.1 Motivation 40 4.2 System Model 41 4.3 Problem Formulation 43 4.4 Decentralized User Association Algorithm 44 4.4.1 Overview 44 4.4.2 User Scheduling and Throughput Estimation 46 4.4.3 Broadcast Signal Design 46 4.5 Fully Decentralized Algorithm 52 4.6 Performance Evaluation and Discussion 53 4.6.1 Simulation Setup 53 4.6.2 Unbalanced Traffic Intensity 54 4.6.3 Equal Traffic Intensity 59 4.6.4 Dynamic Scenarios 64 Chapter 5 JOINT OPTIMIZATION OF USER ASSOCIATION & INTER-TIER INTERFERENCE MANAGEMENT IN HETEROGENEOUS CELLULAR NETWORKS 68 5.1 Motivation 68 5.2 System Model 69 5.3 Problem Formulation 70 5.4 Joint Optimization Algorithm 72 5.5 Performance Evaluation and Discussion 74 5.5.1 Simulation Setup 74 5.5.2 Simulation Results 74 Chapter 6 CONCLUSION 80 Appendix 82 Appendix A Proof of Proposition 5.1 82 Appendix B Proof of Proposition 5.3 83 Abstract (In Korean) 93Docto

The IPIN 2019 Indoor Localisation Competition—Description and Results

IPIN 2019 Competition, sixth in a series of IPIN competitions, was held at the CNR Research Area of Pisa (IT), integrated into the program of the IPIN 2019 Conference. It included two on-site real-time Tracks and three off-site Tracks. The four Tracks presented in this paper were set in the same environment, made of two buildings close together for a total usable area of 1000 m 2 outdoors and and 6000 m 2 indoors over three floors, with a total path length exceeding 500 m. IPIN competitions, based on the EvAAL framework, have aimed at comparing the accuracy performance of personal positioning systems in fair and realistic conditions: past editions of the competition were carried in big conference settings, university campuses and a shopping mall. Positioning accuracy is computed while the person carrying the system under test walks at normal walking speed, uses lifts and goes up and down stairs or briefly stops at given points. Results presented here are a showcase of state-of-the-art systems tested side by side in real-world settings as part of the on-site real-time competition Tracks. Results for off-site Tracks allow a detailed and reproducible comparison of the most recent positioning and tracking algorithms in the same environment as the on-site Tracks

Steric effects on controlling of photoinduced electron transfer action of anthracene modified benzo-15-crown-5 by complexation with Mg2+ and Ca2+

Benzo-crown ether based chemosensors linked by an amide bond at the 1-, 2- or 9-positions of anthracene rings were synthesized. Their complexation behavior with alkaline earth metal ions in acetonitrile was investigated using fluorescence, UV, and 1H-NMR spectroscopy. In the absence of a metal ion, all compounds showed only very slight fluorescence emissions (fluorescence ‘off’ state) because of intramolecular charge/electron transfer process. After the complex formation with Mg2+ and Ca2+, however, only the 2-position analogue gave a fluorescence ‘on’ response by inhibiting the photoinduced electron transfer. Because 2- positioned anthracene was free from steric hindrance of the crown ether ring, a strongly bent complex structure was formed with Mg2+ and Ca2+, which induced a breakdown of π- conjugation between the amide moiety and the benzene ring

NLOS Identification in WLANs Using Deep LSTM with CNN Features

Identifying channel states as line-of-sight or non-line-of-sight helps to optimize location-based services in wireless communications. The received signal strength identification and channel state information are used to estimate channel conditions for orthogonal frequency division multiplexing systems in indoor wireless local area networks. This paper proposes a joint convolutional neural network and recurrent neural network architecture to classify channel conditions. Convolutional neural networks extract the feature from frequency-domain characteristics of channel state information data and recurrent neural networks extract the feature from time-varying characteristics of received signal strength identification and channel state information between packet transmissions. The performance of the proposed methods is verified under indoor propagation environments. Experimental results show that the proposed method has a 2% improvement in classification performance over the conventional recurrent neural network model

Arabidopsis ABCG34 contributes to defense against necrotrophic pathogens by mediating the secretion of camalexin

Plant pathogens cause huge yield losses. Plant defense often depends on toxic secondary metabolites that inhibit pathogen growth. Because most secondary metabolites are also toxic to the plant, specific transporters are needed to deliver them to the pathogens. To identify the transporters that function in plant defense, we screened Arabidopsis thaliana mutants of full-size ABCG transporters for hypersensitivity to sclareol, an antifungal compound. We found that atabcg34 mutants were hypersensitive to sclareol and to the necrotrophic fungi Alternaria brassicicola and Botrytis cinereaAtABCG34 expression was induced by Abrassicicola inoculation as well as by methyl-jasmonate, a defense-related phytohormone, and AtABCG34 was polarly localized at the external face of the plasma membrane of epidermal cells of leaves and roots. atabcg34 mutants secreted less camalexin, a major phytoalexin in Athaliana, whereas plants overexpressing AtABCG34 secreted more camalexin to the leaf surface and were more resistant to the pathogen. When treated with exogenous camalexin, atabcg34 mutants exhibited hypersensitivity, whereas BY2 cells expressing AtABCG34 exhibited improved resistance. Analyses of natural Arabidopsis accessions revealed that AtABCG34 contributes to the disease resistance in naturally occurring genetic variants, albeit to a small extent. Together, our data suggest that AtABCG34 mediates camalexin secretion to the leaf surface and thereby prevents Abrassicicola infection

Joint Vehicle Tracking and RSU Selection for V2I Communications with Extended Kalman Filter

IEEEWe develop joint vehicle tracking and road side unit (RSU) selection algorithms suitable for vehicle-to-infrastructure (V2I) communications. We first design an analytical framework for evaluating vehicle tracking systems based on the extended Kalman filter. A simple, yet effective, metric that quantifies the vehicle tracking performance is derived in terms of the angular derivative of a dominant spatial frequency. Second, an RSU selection algorithm is proposed to select a proper RSU that enhances the vehicle tracking performance. A joint vehicle tracking algorithm is also developed to maximize the tracking performance by considering sounding samples at multiple RSUs while minimizing the amount of sample exchange. The numerical results verify that the proposed vehicle tracking algorithms give better performance than conventional signal-to-noise ratio-based tracking systems.N