• 제목/요약/키워드: LTE Positioning

검색결과 20건 처리시간 0.023초

PS-LTE 환경에서 최적기지국 위치 선정 (Optimal Positioning of the Base Stations in PS-LTE Systems)

  • 김현우;이상훈;윤현구;최용훈
    • 한국통신학회논문지
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    • 제41권4호
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    • pp.467-478
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    • 2016
  • 본 논문에서는 PS-LTE(Public Safety-Long Term Evolution) 환경에서 단독기지국의 설치에 있어서 전체 사용자의 데이터 처리량을 최대화하는 PSO(Particle Swarm Optimization)기반의 최적기지국 위치 선정 방법을 제안한다. 또한 전체 재난 지역을 탐색하여 최적의 위치를 찾는 완전탐색(Exhaustive Search) 방법, 임의보행(Random Walk) 이동모형을 적용하여 위치를 선정하는 방법, 기지국 균일 배치방법과의 성능을 비교하였다. 제안하는 방법의 경우 모든 지역을 탐색하여 최적위치를 찾는 완전탐색 방법과 유사한 최적위치 및 전체 사용자의 데이터 처리량(Throughput)을 갖지만, 최적해 수렴시간에 있어서 완전탐색의 경우 재난지역의 크기가 커질수록 증가하지만, 제안하는 방법 경우 빠른 수렴 시간 및 거의 일정한 수렴시간을 갖는 것을 알 수 있다.

도심 지역 LTE 측위 기반 무인항공기 안전거리 생성 알고리즘 연구 및 시각화 도구 개발 (Safety Distance Visualization Tool for LTE-Based UAV Positioning in Urban Areas)

  • 이하림;강태원;서지원
    • 한국항행학회논문지
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    • 제23권5호
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    • pp.408-414
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    • 2019
  • 본 연구에서는 도심지역의 무인항공기 충돌 방지를 위한 관제 도구를 개발하였다. 개발된 도구에서 사용자는 실제 도심지역 3D 지도상에 기지국과 무인항공기를 배치한 뒤, 안전 거리를 가시화할 수 있다. 이 때, 무인항공기의 위치는 long-term evolution(LTE) 신호를 기반으로 계산된다고 가정하였다. 또한, 무인항공기의 안전 거리는 거리 측정 오차의 바이어스가 발생한 신호를 포함하도록 정의되었다. 이러한 안전거리 계산 방식은 다중 경로에 의해 바이어스 신호가 빈번히 발생하는 실제 도심환경의 특성을 반영한다. 개발된 도구 상에서 실측값을 바탕으로 파라미터를 설정하고 고장 신호 개수에 따른 안전거리의 변화를 시뮬레이션하였다. 그 결과 고장 신호의 개수가 증가함에 따라 안전거리가 증가하는 정상적인 결과가 출력됨을 확인하였다.

Performance Comparison of Machine Learning Algorithms for Received Signal Strength-Based Indoor LOS/NLOS Classification of LTE Signals

  • Lee, Halim;Seo, Jiwon
    • Journal of Positioning, Navigation, and Timing
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    • 제11권4호
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    • pp.361-368
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    • 2022
  • An indoor navigation system that utilizes long-term evolution (LTE) signals has the benefit of no additional infrastructure installation expenses and low base station database management costs. Among the LTE signal measurements, received signal strength (RSS) is particularly appealing because it can be easily obtained with mobile devices. Propagation channel models can be used to estimate the position of mobile devices with RSS. However, conventional channel models have a shortcoming in that they do not discriminate between line-of-sight (LOS) and non-line-of-sight (NLOS) conditions of the received signal. Accordingly, a previous study has suggested separated LOS and NLOS channel models. However, a method for determining LOS and NLOS conditions was not devised. In this study, a machine learning-based LOS/NLOS classification method using RSS measurements is developed. We suggest several machine-learning features and evaluate various machine-learning algorithms. As an indoor experimental result, up to 87.5% classification accuracy was achieved with an ensemble algorithm. Furthermore, the range estimation accuracy with an average error of 13.54 m was demonstrated, which is a 25.3% improvement over the conventional channel model.

Applications of Intelligent Radio Technologies in Unlicensed Cellular Networks - A Survey

  • Huang, Yi-Feng;Chen, Hsiao-Hwa
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권7호
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    • pp.2668-2717
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    • 2021
  • Demands for high-speed wireless data services grow rapidly. It is a big challenge to increasing the network capacity operating on licensed spectrum resources. Unlicensed spectrum cellular networks have been proposed as a solution in response to severe spectrum shortage. Licensed Assisted Access (LAA) was standardized by 3GPP, aiming to deliver data services through unlicensed 5 GHz spectrum. Furthermore, the 3GPP proposed 5G New Radio-Unlicensed (NR-U) study item. On the other hand, artificial intelligence (AI) has attracted enormous attention to implement 5G and beyond systems, which is known as Intelligent Radio (IR). To tackle the challenges of unlicensed spectrum networks in 4G/5G/B5G systems, a lot of works have been done, focusing on using Machine Learning (ML) to support resource allocation in LTE-LAA/NR-U and Wi-Fi coexistence environments. Generally speaking, ML techniques are used in IR based on statistical models established for solving specific optimization problems. In this paper, we aim to conduct a comprehensive survey on the recent research efforts related to unlicensed cellular networks and IR technologies, which work jointly to implement 5G and beyond wireless networks. Furthermore, we introduce a positioning assisted LTE-LAA system based on the difference in received signal strength (DRSS) to allocate resources among UEs. We will also discuss some open issues and challenges for future research on the IR applications in unlicensed cellular networks.

다중 안테나 기반 위상 차이를 이용한 AOA 측위 기법 (Multi-Antenna based AOA Positioning using Phase Difference)

  • 박익현;유국열;박용완
    • 대한임베디드공학회논문지
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    • 제8권2호
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    • pp.95-102
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    • 2013
  • In this paper, we have studied the performance of the AOA (Angle of Arrival) in multi-antenna systems for LBS (Location Based Services) and we also analyzed the performance of the AOA in SISO (Single Input Single Output) in multipath environments and their differences. The adequacy of AOA positioning in new communication environments was determined. Currently used positioning methods in 3G communication environment has been developed based on SISO. However, the accuracy of SISO-based TOA (Time of Arrival), TDOA (Time Difference of Arrival), AOA positioning techniques degraded in multipath environments. The communication system will be changed and developed. According to enhanced positioning techniques are required. Using antenna characteristics and the phase difference between antennas of LTE-Advanced standard's key technique MIMO system AOA positioning, and SISO based AOA positioning performance were analyzed. We found that AOA technique potential for use based on Multiple antenna systems by computer simulations.

Performance Enhancement of Emergency Rescue System using Surface Correlation Technology

  • Shin, Beomju;Lee, Jung Ho;Shin, Donghyun;Yu, Changsu;Kyung, Hankyeol;Lee, Taikjin
    • Journal of Positioning, Navigation, and Timing
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    • 제9권3호
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    • pp.183-189
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    • 2020
  • In emergency rescue situations, the localization accuracy of the rescue requestor is a very important factor in determining the success or failure of the rescue. Indoors where Global Navigation Satellite System (GNSS) is not operated, there is no choice but to use Wi-Fi or LTE signals. However, the performance of the current emergency rescue system utilizing those RF signals is exceedingly low. In this study, the effectiveness of the surface correlation technology using the accumulated signal pattern of RF signals was verified in relation to the emergency localization technology. To validate the proposed system, we configured and tested an emergency rescue scenario in multi-floors building. When the emergency rescue was requested, it was confirmed that the initial localization error was large owing to the short length of the accumulated signal pattern. However, the localization error decreased over time, which eventually led to the accurate location information being delivered to the rescuer.

정밀 위치 측위를 위한 LTE-M 기반의 저가형 RTK 단말 개발 (Development of Low-cost RTK Device base on LTE-M for Precise Location Positioning)

  • 박철순;박승권
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2018년도 추계학술대회
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    • pp.565-567
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    • 2018
  • 이동국은 최소 4개 이상의 인공위성에서 제공하는 신호를 이용하여 자신의 위치 정보를 획득한다. 현대에 들어 위성항법시스템은 다양한 분야에서 널리 사용되고 있다. 그러나 이동국과 위성 사이에는 측위 시, 정확도 오차를 발생 시키는 많은 요인이 존재한다. 위성 시간 오차, 궤도 오차, 전리층/대류층 굴절, 다중 경로 등의 원인으로 이동국은 정밀한 위치 정보 획득이 불가능 하다. 이러한 오차 발생을 줄이기 위한 보정 기법으로 Differential GPS(DGPS)와 Real-Time Kinematic(RTK)가 개발되었다. 따라서 본 논문에서는 이동국이 정밀한 위치 정보를 획득하기 위해서 RTK 기법이 적용된 단말을 개발하고자 한다.

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자율협력주행을 위한 하이브리드 V2X 통신모듈 설계 (Design of Hybrid V2X Communication Module for Cooperative Automated Driving)

  • 임기택;진성근;곽재민
    • 한국항행학회논문지
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    • 제22권3호
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    • pp.213-219
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    • 2018
  • 본 논문에서는 차량 환경에 적합하게 설계된 C-ITS 통신프로토콜과 이동 통신 프로토콜인 Legacy LTE 통신 기술을 함께 지원하는 하이브리드 V2X 통신모듈의 하드웨어 및 소프트웨어에 대한 설계 방안을 제안하고 설계과정을 제시한다. C-ITS는 저 지연 특성으로 인해 안전 서비스 어플리케이션에 적합하며, Legacy LTE는 고지연, 고용량 특성으로 인해 교통정보, 인포테인먼트와 같은 비 안전 어플리케이션에 적합한 기술이다. 하이브리드 V2X 통신 모듈은 복수의 통신기술로 WAVE와 LTE를 지원하고, WAVE에 대해서는 복수채널 통신을 지원하여, 자율주행 차량에 LDM, 측위보정정보 등의 도로정보를 실시간으로 전달하기 위한 목적으로 설계된다. 본 논문에 제시된 주요 설계 결과는 향후 차량용 하이브리드 V2X 통신 단말기 구현에 적용될 예정이다.

Improved LTE Fingerprint Positioning Through Clustering-based Repeater Detection and Outlier Removal

  • Kwon, Jae Uk;Chae, Myeong Seok;Cho, Seong Yun
    • Journal of Positioning, Navigation, and Timing
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    • 제11권4호
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    • pp.369-379
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    • 2022
  • In weighted k-nearest neighbor (WkNN)-based Fingerprinting positioning step, a process of comparing the requested positioning signal with signal information for each reference point stored in the fingerprint DB is performed. At this time, the higher the number of matched base station identifiers, the higher the possibility that the terminal exists in the corresponding location, and in fact, an additional weight is added to the location in proportion to the number of matching base stations. On the other hand, if the matching number of base stations is small, the selected candidate reference point has high dependence on the similarity value of the signal. But one problem arises here. The positioning signal can be compared with the repeater signal in the signal information stored on the DB, and the corresponding reference point can be selected as a candidate location. The selected reference point is likely to be an outlier, and if a certain weight is applied to the corresponding location, the error of the estimated location information increases. In order to solve this problem, this paper proposes a WkNN technique including an outlier removal function. To this end, it is first determined whether the repeater signal is included in the DB information of the matched base station. If the reference point for the repeater signal is selected as the candidate position, the reference position corresponding to the outlier is removed based on the clustering technique. The performance of the proposed technique is verified through data acquired in Seocho 1 and 2 dongs in Seoul.

Neural Networks Based Modeling with Adaptive Selection of Hidden Layer's Node for Path Loss Model

  • Kang, Chang Ho;Cho, Seong Yun
    • Journal of Positioning, Navigation, and Timing
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    • 제8권4호
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    • pp.193-200
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    • 2019
  • The auto-encoder network which is a good candidate to handle the modeling of the signal strength attenuation is designed for denoising and compensating the distortion of the received data. It provides a non-linear mapping function by iteratively learning the encoder and the decoder. The encoder is the non-linear mapping function, and the decoder demands accurate data reconstruction from the representation generated by the encoder. In addition, the adaptive network width which supports the automatic generation of new hidden nodes and pruning of inconsequential nodes is also implemented in the proposed algorithm for increasing the efficiency of the algorithm. Simulation results show that the proposed method can improve the neural network training surface to achieve the highest possible accuracy of the signal modeling compared with the conventional modeling method.