116 research outputs found
On Intercept Probability Minimization under Sparse Random Linear Network Coding
This paper considers a network where a node wishes to transmit a source
message to a legitimate receiver in the presence of an eavesdropper. The
transmitter secures its transmissions employing a sparse implementation of
Random Linear Network Coding (RLNC). A tight approximation to the probability
of the eavesdropper recovering the source message is provided. The proposed
approximation applies to both the cases where transmissions occur without
feedback or where the reliability of the feedback channel is impaired by an
eavesdropper jamming the feedback channel. An optimization framework for
minimizing the intercept probability by optimizing the sparsity of the RLNC is
also presented. Results validate the proposed approximation and quantify the
gain provided by our optimization over solutions where non-sparse RLNC is used.Comment: To appear on IEEE Transactions on Vehicular Technolog
Operating ITS-G5 DSRC over Unlicensed Bands: A City-Scale Performance Evaluation
Future Connected and Autonomous Vehicles (CAVs) will be equipped with a large
set of sensors. The large amount of generated sensor data is expected to be
exchanged with other CAVs and the road-side infrastructure. Both in Europe and
the US, Dedicated Short Range Communications (DSRC) systems, based on the IEEE
802.11p Physical Layer, are key enabler for the communication among vehicles.
Given the expected market penetration of connected vehicles, the licensed band
of 75 MHz, dedicated to DSRC communications, is expected to become increasingly
congested. In this paper, we investigate the performance of a vehicular
communication system, operated over the unlicensed bands 2.4 GHz - 2.5 GHz and
5.725 GHz - 5.875 GHz. Our experimental evaluation was carried out in a testing
track in the centre of Bristol, UK and our system is a full-stack ETSI ITS-G5
implementation. Our performance investigation compares key communication
metrics (e.g., packet delivery rate, received signal strength indicator)
measured by operating our system over the licensed DSRC and the considered
unlicensed bands. In particular, when operated over the 2.4 GHz - 2.5 GHz band,
our system achieves comparable performance to the case when the DSRC band is
used. On the other hand, as soon as the system, is operated over the 5.725 GHz
- 5.875 GHz band, the packet delivery rate is 30% smaller compared to the case
when the DSRC band is employed. These findings prove that operating our system
over unlicensed ISM bands is a viable option. During our experimental
evaluation, we recorded all the generated network interactions and the complete
data set has been publicly available.Comment: IEEE PIMRC 2019, to appea
High-Speed Data Dissemination over Device-to-Device Millimeter-Wave Networks for Highway Vehicular Communication
Gigabit-per-second connectivity among vehicles is expected to be a key
enabling technology for sensor information sharing, in turn, resulting in safer
Intelligent Transportation Systems (ITSs). Recently proposed millimeter-wave
(mmWave) systems appear to be the only solution capable of meeting the data
rate demand imposed by future ITS services. In this poster, we assess the
performance of a mmWave device-to-device (D2D) vehicular network by
investigating the impact of system and communication parameters on end-users.Comment: To appear in IEEE VNC 2017, Torino, I
Modeling and Design of Millimeter-Wave Networks for Highway Vehicular Communication
Connected and autonomous vehicles will play a pivotal role in future
Intelligent Transportation Systems (ITSs) and smart cities, in general.
High-speed and low-latency wireless communication links will allow
municipalities to warn vehicles against safety hazards, as well as support
cloud-driving solutions to drastically reduce traffic jams and air pollution.
To achieve these goals, vehicles need to be equipped with a wide range of
sensors generating and exchanging high rate data streams. Recently, millimeter
wave (mmWave) techniques have been introduced as a means of fulfilling such
high data rate requirements. In this paper, we model a highway communication
network and characterize its fundamental link budget metrics. In particular, we
specifically consider a network where vehicles are served by mmWave Base
Stations (BSs) deployed alongside the road. To evaluate our highway network, we
develop a new theoretical model that accounts for a typical scenario where
heavy vehicles (such as buses and lorries) in slow lanes obstruct Line-of-Sight
(LOS) paths of vehicles in fast lanes and, hence, act as blockages. Using tools
from stochastic geometry, we derive approximations for the
Signal-to-Interference-plus-Noise Ratio (SINR) outage probability, as well as
the probability that a user achieves a target communication rate (rate coverage
probability). Our analysis provides new design insights for mmWave highway
communication networks. In considered highway scenarios, we show that reducing
the horizontal beamwidth from to determines a minimal
reduction in the SINR outage probability (namely, at
maximum). Also, unlike bi-dimensional mmWave cellular networks, for small BS
densities (namely, one BS every m) it is still possible to achieve an
SINR outage probability smaller than .Comment: Accepted for publication in IEEE Transactions on Vehicular Technology
-- Connected Vehicles Serie
Agile Calibration Process of Full-Stack Simulation Frameworks for V2X Communications
Computer simulations and real-world car trials are essential to investigate
the performance of Vehicle-to-Everything (V2X) networks. However, simulations
are imperfect models of the physical reality and can be trusted only when they
indicate agreement with the real-world. On the other hand, trials lack
reproducibility and are subject to uncertainties and errors. In this paper, we
will illustrate a case study where the interrelationship between trials,
simulation, and the reality-of-interest is presented. Results are then compared
in a holistic fashion. Our study will describe the procedure followed to
macroscopically calibrate a full-stack network simulator to conduct
high-fidelity full-stack computer simulations.Comment: To appear in IEEE VNC 2017, Torino, I
Beam Alignment for Millimetre Wave Links with Motion Prediction of Autonomous Vehicles
Intelligent Transportation Systems (ITSs) require ultra-low end-to-end delays
and multi-gigabit-per-second data transmission. Millimetre Waves (mmWaves)
communications can fulfil these requirements. However, the increased mobility
of Connected and Autonomous Vehicles (CAVs), requires frequent beamforming -
thus introducing increased overhead. In this paper, a new beamforming algorithm
is proposed able to achieve overhead-free beamforming training. Leveraging from
the CAVs sensory data, broadcast with Dedicated Short Range Communications
(DSRC) beacons, the position and the motion of a CAV can be estimated and
beamform accordingly. To minimise the position errors, an analysis of the
distinct error components was presented. The network performance is further
enhanced by adapting the antenna beamwidth with respect to the position error.
Our algorithm outperforms the legacy IEEE 802.11ad approach proving it a viable
solution for the future ITS applications and services.Comment: Proc. of IET Colloquium on Antennas, Propagation & RF Technology for
Transport and Autonomous Platforms, to appea
Passive Radar for Opportunistic Monitoring in e-Health Applications
This paper proposes a passive Doppler radar as a non-contact sensing method to capture human body movements, recognize respiration, and physical activities in e-Health applications. The system uses existing in-home wireless signal as the source to interpret human activity. This paper shows that passive radar is a novel solution for multiple healthcare applications which complements traditional smart home sensor systems. An innovative two-stage signal processing framework is outlined to enable the multi-purpose monitoring function. The first stage is to obtain premier Doppler information by using the high speed passive radar signal processing. The second stage is the functional signal processing including micro Doppler extraction for breathing detection and support vector machine classifier for physical activity recognition. The experimental results show that the proposed system provides adequate performance for both purposes, and prove that non-contact passive Doppler radar is a complementary technology to meet the challenges of future healthcare applications
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