3,344 research outputs found
Software-only TDOA/RTF positioning for 3G WCDMA wireless network
A hybrid location finding technique based oil time difference of arrival (TDOA) with round-trip time (RTT) measurements is proposed for a wideband code division Multiple access (WCDMA) network. In this technique, a mobile station measures timing from at least three base stations using user equipment receive-transmit (UE Rx-Tx) time difference and at least three base stations measure timing from the mobile station using RTT. The timing measurements of mobile and base stations are then combined to solve for both the location of the mobile and the synchronization offset between base stations. A software-only geolocation system based on the above mobile/base stations timing measurements is implemented in Matlab platform and the performance of the system is investigated using large-scale propagation models
Multi-Channel Two-way Time of Flight Sensor Network Ranging
Two-way time of flight (ToF) ranging is one of the most interesting approaches for localization in wireless sensor networking since previous ToF ranging approaches using commercial off-the-shelf (COTS) devices have achieved good accuracy. The COTS-based approaches were, however, evaluated only in line-of-sight conditions. In this paper, we extend ToF ranging using multiple IEEE 802.15.4 channels. Our results demonstrate that with multiple channels we can achieve good accuracy even in non line-of-sight conditions. Furthermore, our measurements suggest that the variance between different channels serves as a good estimate of the accuracy of the measurements, which can be valuable information for applications that require localization information
Wireless distance estimation with low-power standard components in wireless sensor nodes
In the context of increasing use of moving wireless sensor nodes the interest
in localizing these nodes in their application environment is strongly rising.
For many applications, it is necessary to know the exact position of the nodes
in two- or three-dimensional space. Commonly used nodes use state-of-the-art
transceivers like the CC430 from Texas Instruments with integrated signal
strength measurement for this purpose. This has the disadvantage, that the
signal strength measurement is strongly dependent on the orientation of the
node through the antennas inhomogeneous radiation pattern as well as it has a
small accuracy on long ranges. Also, the nodes overall attenuation and output
power has to be calibrated and interference and multipath effects appear in
closed environments. Another possibility to trilaterate the position of a
sensor node is the time of flight measurement. This has the advantage, that the
position can also be estimated on long ranges, where signal strength methods
give only poor accuracy. In this paper we present an investigation of the
suitability of the state-of-the-art transceiver CC430 for a system based on
time of flight methods and give an overview of the optimal settings under
various circumstances for the in-field application. For this investigation, the
systematic and statistical errors in the time of flight measurements with the
CC430 have been investigated under a multitude of parameters. Our basic system
does not use any additional components but only the given standard hardware,
which can be found on the Texas Instruments evaluation board for a CC430. Thus,
it can be implemented on already existent sensor node networks by a simple
software upgrade.Comment: 8 pages, Proceedings of the 14th Mechatronics Forum International
Conference, Mechatronics 201
Software Defined Media: Virtualization of Audio-Visual Services
Internet-native audio-visual services are witnessing rapid development. Among
these services, object-based audio-visual services are gaining importance. In
2014, we established the Software Defined Media (SDM) consortium to target new
research areas and markets involving object-based digital media and
Internet-by-design audio-visual environments. In this paper, we introduce the
SDM architecture that virtualizes networked audio-visual services along with
the development of smart buildings and smart cities using Internet of Things
(IoT) devices and smart building facilities. Moreover, we design the SDM
architecture as a layered architecture to promote the development of innovative
applications on the basis of rapid advancements in software-defined networking
(SDN). Then, we implement a prototype system based on the architecture, present
the system at an exhibition, and provide it as an SDM API to application
developers at hackathons. Various types of applications are developed using the
API at these events. An evaluation of SDM API access shows that the prototype
SDM platform effectively provides 3D audio reproducibility and interactiveness
for SDM applications.Comment: IEEE International Conference on Communications (ICC2017), Paris,
France, 21-25 May 201
Promoting the use of reliable rate based transport protocols: the Chameleon protocol
Rate-based congestion control, such as TFRC, has not been designed to enable reliability. Indeed, the birth of TFRC protocol has resulted from the need for a congestion-controlled transport protocol in order to carry multimedia traffic. However, certain applications still prefer the use of UDP in order to implement their own congestion control on top of it. The present contribution proposes to design and validate a reliable rate-based protocol based on the combined use of TFRC, SACK and an adapted flow control. We argue that rate-based congestion control is a perfect alternative to window-based congestion control as most of today applications need to interact with the transport layer and should not be only limited to unreliable services. In this paper, we detail the implementation of a reliable rate-based protocol named Chameleon and bring out to the networking community an ns-2 implementation for evaluation purpose
Mobility-Induced Graph Learning for WiFi Positioning
A smartphone-based user mobility tracking could be effective in finding
his/her location, while the unpredictable error therein due to low
specification of built-in inertial measurement units (IMUs) rejects its
standalone usage but demands the integration to another positioning technique
like WiFi positioning. This paper aims to propose a novel integration technique
using a graph neural network called Mobility-INduced Graph LEarning (MINGLE),
which is designed based on two types of graphs made by capturing different user
mobility features. Specifically, considering sequential measurement points
(MPs) as nodes, a user's regular mobility pattern allows us to connect neighbor
MPs as edges, called time-driven mobility graph (TMG). Second, a user's
relatively straight transition at a constant pace when moving from one position
to another can be captured by connecting the nodes on each path, called a
direction-driven mobility graph (DMG). Then, we can design graph convolution
network (GCN)-based cross-graph learning, where two different GCN models for
TMG and DMG are jointly trained by feeding different input features created by
WiFi RTTs yet sharing their weights. Besides, the loss function includes a
mobility regularization term such that the differences between adjacent
location estimates should be less variant due to the user's stable moving pace.
Noting that the regularization term does not require ground-truth location,
MINGLE can be designed under semi- and self-supervised learning frameworks. The
proposed MINGLE's effectiveness is extensively verified through field
experiments, showing a better positioning accuracy than benchmarks, say root
mean square errors (RMSEs) being 1.398 (m) and 1.073 (m) for self- and
semi-supervised learning cases, respectively.Comment: submitted to a possible IEEE journa
A New RSSI-based Centroid Localization Algorithm by Use of Virtual Reference Tags
A good design of node location is critical for efficient
and effective wireless communications. This paper presents an
improved algorithm, in order to solve the low localization
accuracy caused by traditional centroid algorithm. The
improved algorithm combined with VIRE system and
traditional centroid algorithm. The VIRE algorithm is
introduced and the signal propagation model is utilized to
construct virtual reference tags in the location area. Simulation shows that this further developed algorithm has further improved the accuracy of positioning up to 35.12% compared
to the traditional centroid algorithm. It is concluded that this algorithm can further improve the locating accuracy in comparison with the original centroid algorithm
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