Mobile Positioning Technology

2011 ◽  
pp. 2595-2603
Author(s):  
Nikos Deligiannis ◽  
Spiros Louvros ◽  
Stavros Kotsopoulos
Keyword(s):  
Cellular Networks ◽  
Mobile Terminal ◽  
Base Stations ◽  
Fourth Generation ◽  
Time Of Arrival ◽  
Core Network ◽  
Angle Of Arrival ◽  
The Core ◽  
Air Interface ◽  
Radio Signals

A radio mobile-position system operates by measuring, processing, and storing physical quantities related to radio signals travelling between a mobile terminal and a set of transceivers, for example, satellites or Base Stations (BSs). Positioning techniques in cellular networks are of great importance for supporting emerging services that require a sufficient, precise estimation of the position of the mobile terminal (MT) associated with a number of given base stations. The ability to support position location within wireless networks provides network operators with valuable services, as well as users with a host of new applications. This includes navigation, location-based services, network management, and security applications. Nowadays in GSM networks, there is no specific algorithm included in the software to locate subscribers. The only possibility to locate a subscriber is accomplished by using GPS technology or special firmware. An innovative development should be the design and implementation of certain location positioning techniques, as Time of Arrival (ToA) and Angle of Arrival (AoA), over the existing GSM network. Although there are already next generation networks in use nowadays (UMTS, GPRS, WLAN), and there also is extensive research towards the fourth generation cellular networks, GSM seems to be the most popular network so far. GPRS network is a data network over GSM platform and it exists only with GSM architecture. The reason is that GPRS uses the GSM air interface (Radio Network Part) and it only diverts in the core network where it transmits the data packets towards a different switch. UMTS, on the other hand, is a unique network supporting cellular and voice-data applications, and is the evolution of GSM towards IP applications. Although it could be implemented separately from GSM, most of the operators preferred to implement it in a GSM convergence mode towards the core network for eliminating the investment. As a result, in most countries GSM is the major network with full geographical coverage and network location positioning techniques are most implemented in a network environment with a satisfactory number of Base Stations.

scholarly journals Non-Line-of-Sight Error Mitigation in Wireless Communication Systems

2011 ◽  
Vol 1 ◽  
pp. 173-177
Author(s):  
Szu Lin Su ◽  
Yi Wen Su ◽  
Ho Nien Shou ◽  
Chien Sheng Chen
Keyword(s):  
Communication Systems ◽  
Hybrid Methods ◽  
Mobile Station ◽  
Base Stations ◽  
Superior Performance ◽  
Line Of Sight ◽  
Time Of Arrival ◽  
Angle Of Arrival ◽  
Error Statistics ◽  
Non Line Of Sight

When there is non-line-of-sight (NLOS) path between the mobile station (MS) and base stations (BSs), it is possible to integrate many kinds of measurements to achieve more accurate measurements of the MS location. This paper proposed hybrid methods that utilize time of arrival (TOA) at five BSs and angle of arrival (AOA) information at the serving BS to determine the MS location in NLOS environments. The methods mitigate the NLOS effect simply by the weighted sum of the intersections between five TOA circles and the AOA line without requiring priori knowledge of NLOS error statistics. Simulation results show that the proposed methods always give superior performance than Taylor series algorithm (TSA) and the hybrid lines of position algorithm (HLOP).

scholarly journals KUNCI TEKNOLOGI 5G

2018 ◽  
Vol 4 (2) ◽  
Author(s):  
Ulil Surtia Zulpratita
Keyword(s):  
Base Station ◽  
Base Stations ◽  
Core Network ◽  
Access Technology ◽  
Radio Access Technology ◽  
Radio Access ◽  
Air Interface ◽  
Large Numbers ◽  
5G Network ◽  
High Carrier

[Id] Proses kelengkapan standarisasi teknologi 5G diharapkan akan selesai sebelum Oktober 2020. Resminya standarisasi ini akan menjadi hal penting untuk komersialisasi jaringan 5G. Teknologi 5G diprediksi akan membutuhkan transformasi akan kebutuhan frekuensi carrier yang sangat tinggi dengan bandwidth yang sangat lebar, densitas ekstrim untuk berbagai divais dan base station, serta sejumlah besar antena. 5G tidak akan menjadi antarmuka udara tunggal sebagaimana pada model generasi sebelumnya. 5G diprediksi akan sangat integratif: jalinan koneksi antarmuka udara dan spektrum 5G bersama-sama dengan teknologi nirkabel yang sudah ada (misalnya: LTE dan WiFi) akan memberikan layanan dengan pesat data tinggi dan cakupan luas, serta menjamin terwujudnya pengalaman pengguna tanpa hambatan. Untuk mendukung hal tersebut, di bagian core network harus berevolusi untuk mencapai tingkat belum pernah terjadi sebelumnya dalam hal fleksibilitas dan kecerdasan, regulasi spektrum perlu dikaji kembali dan direvisi, masalah energi dan efisiensi biaya juga akan menjadi pertimbangan yang penting. Berdasarkan studi literatur yang telah dilakukan, artikel ini akan mengidentifikasi dan merumuskan empat kunci penting implementasi teknologi 5G. Kata kunci : implementasi 5G, massive MIMO, jaringan hybrid, mmWave, unified air interface [En] 5G standardization process is expected to be finished before October 2020. This standardization is essential for making 5G network commercial deployment. The 5G technology is forecasted to demand a transformation in the need for very high carrier frequencies with very extensive bandwidth, extreme density for devices and base stations, as well as large numbers of antennas. 5G will not be a distinct air interface based on Radio Access Technology as in former generation models. 5G is predicted to be immensely collaborative: the linkage of air interface and 5G spectrum together with existing wireless technologies (for example: LTE and WiFi) will provide services with universal high-rates coverage and ensure seamless user experience. To support this, the core network must also evolve to achieve an extraordinary level of adjustability and intelligence, spectral standardization needs to be reviewed and revised, energy issues and cost efficiency will also be an important attention. Based on studies that had been done, this article will discuss and identify the four significant keys to the implementation of 5G technology.

Radio-over-Fibre Networks for 4G

2010 ◽  
pp. 268-291
Author(s):  
Roberto Llorente ◽  
Maria Morant ◽  
Javier Martí
Keyword(s):  
Optical Fibre ◽  
Antenna System ◽  
Base Stations ◽  
Fourth Generation ◽  
60 Ghz ◽  
Communication Technique ◽  
Processing Power ◽  
Radio Signals ◽  
Network Flexibility ◽  
Radio Over Fibre

Radio-over-Fibre (RoF) is an optical communication technique based on the transmission of standard wireless radio signals though optical fibre in their native format. This technique is an enabling step in the deployment of dense fourth generation (4G) cellular and pico-cellular wireless networks. The optical fibre provides a huge bandwidth that can support a variety of wireless systems, regardless of their frequency bands, being protocol-transparent which is reflected in an great network flexibility. Radio-over-fibre techniques enables a high user capacity by frequency reuse, simplifies the network operation as the signals are distribute in their native format, and permits to transfer signal part of the processing power from the base station units to the central control station, thus reducing the overall deployment cost and complexity. The principles of radio-over-fibre are presented in this chapter, including the key transmission impairments and the expected performance. The main application scenarios are discussed. These include the backhaul of 4G or base-stations, addressing 4G and 3G compatibility issues, and distributed-antenna system (DAS). Finally, emerging applications like radio-over-fibre in beyond-3G scenarios and transmission of 60 GHz wireless are also described in this chapter.

Localization Experiments Based on Inertial Sensors for Navigation Applications

2015 ◽  
Vol 764-765 ◽  
pp. 550-554
Author(s):  
Yih Shyh Chiou ◽  
Fuan Tsai
Keyword(s):  
Inertial Sensors ◽  
Dead Reckoning ◽  
Mobile Terminal ◽  
Difficult Problem ◽  
Location Estimation ◽  
Base Stations ◽  
Measurement Unit ◽  
Positioning Systems ◽  
Short Period ◽  
Radio Signals

Robust and accurate positioning systems with seamless outdoor and indoor coverage have been receiving a great deal of attention. In outdoor environments, as radio signals transmitted from base stations or satellites are jammed or shielded, to estimate an accurate location using only the absolute positioning scheme remains a difficult problem regarding location accuracy. In order to overcome the drawback of the ranging scheme based on the radio signals, this paper presents a positioning approach based on inertial-measurement-unit (IMU) observations to estimate the location of a mobile terminal (MT). For the location-estimation technique, the positioning experiment is handled by the dead-reckoning (DR) algorithm. By processing the observations from the IMU, it is possible to estimate the movement of an MT (car). In terms of the IMU-based approach, although the experimental results demonstrate that the positioning scheme using the DR algorithm causes the error propagation, the approach can work in short period of time for navigation applications.

scholarly journals Combination linear lines of position and neural network for mobile station location estimation

2017 ◽  
Vol 13 (7) ◽  
pp. 155014771771738 ◽  
Author(s):  
Chien-Sheng Chen
Keyword(s):  
Mobile Station ◽  
Base Station ◽  
Location Estimation ◽  
Base Stations ◽  
Line Of Sight ◽  
Time Of Arrival ◽  
Angle Of Arrival ◽  
Marquardt Algorithm ◽  
Station Location ◽  
Non Line Of Sight

To enhance the effectiveness and accuracy of mobile station location estimation, author utilizes time of arrival measurements from three base stations and one angle of arrival information at the serving base station to locate mobile station in non-line-of-sight environments. This article makes use of linear lines of position, rather than circular lines of position, to give location estimation of the mobile station. It is much easier to solve two linear line equations rather than nonlinear circular ones. Artificial neural networks are widely used techniques in various areas due to overcoming the problem of exclusive and nonlinear relationships. The proposed algorithms employ the intersections of three linear lines of position and one angle of arrival line, based on Levenburg–Marquardt algorithm, to determine the mobile station location without requiring a priori information about the non-line-of-sight error. The simulation results show that the proposed algorithms can always provide much better location estimation than Taylor series algorithm, hybrid lines of position algorithm as well as the geometrical positioning methods for different levels of biased, unbiased, and distance-dependent non-line-of-sight errors.

scholarly journals Modified Least Squares Algorithm for Three-Dimensional Target Location Based on Wireless Communication Base Stations

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Zhaohui Zhang ◽  
Jing Li ◽  
Qian Liu
Keyword(s):  
Wireless Communication ◽  
Least Squares ◽  
Clustering Algorithm ◽  
Target Location ◽  
Three Dimensional ◽  
Base Station ◽  
Base Stations ◽  
Selection Strategy ◽  
Time Of Arrival ◽  
Radio Signals

The observed values of time of arrival (TOA) for the radio signals between the target and the wireless communication base stations are mainly affected by signal non-line-of-sight (NLOS) propagation in target location. TOA with NLOS makes a lot of signal noises and propagation delays, that is, location errors. For the first time, this paper focuses on the problem of modifying the Z-axis location coordinates in three-dimensional (3D) target location. A novel algorithm is proposed by establishing the modified least squares 3D location model for the accurate target location. Meanwhile, an optimal base station selection strategy is proposed by using the spectral clustering algorithm, which is based on the spatial distribution of the base stations. Compared with the existing algorithms, the proposed algorithm in this paper has better performance on the accurate target 3D location in real scenes, which has a high value of practical application. The simulations illustrate that the location error of the proposed algorithm is smaller than those of other existing algorithms based on the same simulation data and conditions.

scholarly journals Hybrid TOA/AOA Approximate Maximum Likelihood Mobile Localization

2010 ◽  
Vol 2010 ◽  
pp. 1-5 ◽  
Author(s):  
Mohamed Zhaounia ◽  
Mohamed Adnan Landolsi ◽  
Ridha Bouallegue
Keyword(s):  
Maximum Likelihood ◽  
Communication Systems ◽  
Base Stations ◽  
Time Of Arrival ◽  
Angle Of Arrival ◽  
Arrival Angle ◽  
Wireless Location ◽  
Approximate Maximum Likelihood ◽  
Mobile Localization ◽  
Location Algorithm

This letter deals with a hybrid time-of-arrival/angle-of-arrival (TOA/AOA) approximate maximum likelihood (AML) wireless location algorithm. Thanks to the use of both TOA/AOA measurements, the proposed technique can rely on two base stations (BS) only and achieves better performance compared to the original approximate maximum likelihood (AML) method. The use of two BSs is an important advantage in wireless cellular communication systems because it avoids hearability problems and reduces network signaling burden. Simulation results show that, for certain scenarios, the proposed hybrid TOA/AOA AML with two BSs can outperform the AML with up to six BSs.

scholarly journals Machine Learning for the Dynamic Positioning of UAVs for Extended Connectivity

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4618
Author(s):  
Francisco Oliveira ◽  
Miguel Luís ◽  
Susana Sargento
Keyword(s):  
Machine Learning ◽  
Cellular Networks ◽  
Real Data ◽  
Emerging Technology ◽  
Machine Learning Algorithms ◽  
Base Stations ◽  
Aerial Vehicle ◽  
Positioning Algorithm ◽  
The Military ◽  
Better Than

Unmanned Aerial Vehicle (UAV) networks are an emerging technology, useful not only for the military, but also for public and civil purposes. Their versatility provides advantages in situations where an existing network cannot support all requirements of its users, either because of an exceptionally big number of users, or because of the failure of one or more ground base stations. Networks of UAVs can reinforce these cellular networks where needed, redirecting the traffic to available ground stations. Using machine learning algorithms to predict overloaded traffic areas, we propose a UAV positioning algorithm responsible for determining suitable positions for the UAVs, with the objective of a more balanced redistribution of traffic, to avoid saturated base stations and decrease the number of users without a connection. The tests performed with real data of user connections through base stations show that, in less restrictive network conditions, the algorithm to dynamically place the UAVs performs significantly better than in more restrictive conditions, reducing significantly the number of users without a connection. We also conclude that the accuracy of the prediction is a very important factor, not only in the reduction of users without a connection, but also on the number of UAVs deployed.

scholarly journals Adaptive offloading in mobile-edge computing for ultra-dense cellular networks based on genetic algorithm

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Zhuofan Liao ◽  
Jingsheng Peng ◽  
Bing Xiong ◽  
Jiawei Huang
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Cellular Networks ◽  
Physical Distance ◽  
Edge Computing ◽  
Base Stations ◽  
Mobile Edge Computing ◽  
Total Energy Consumption ◽  
Average Delay ◽  
Server Selection

AbstractWith the combination of Mobile Edge Computing (MEC) and the next generation cellular networks, computation requests from end devices can be offloaded promptly and accurately by edge servers equipped on Base Stations (BSs). However, due to the densified heterogeneous deployment of BSs, the end device may be covered by more than one BS, which brings new challenges for offloading decision, that is whether and where to offload computing tasks for low latency and energy cost. This paper formulates a multi-user-to-multi-servers (MUMS) edge computing problem in ultra-dense cellular networks. The MUMS problem is divided and conquered by two phases, which are server selection and offloading decision. For the server selection phases, mobile users are grouped to one BS considering both physical distance and workload. After the grouping, the original problem is divided into parallel multi-user-to-one-server offloading decision subproblems. To get fast and near-optimal solutions for these subproblems, a distributed offloading strategy based on a binary-coded genetic algorithm is designed to get an adaptive offloading decision. Convergence analysis of the genetic algorithm is given and extensive simulations show that the proposed strategy significantly reduces the average latency and energy consumption of mobile devices. Compared with the state-of-the-art offloading researches, our strategy reduces the average delay by 56% and total energy consumption by 14% in the ultra-dense cellular networks.

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