744 research outputs found
Will the Proliferation of 5G Base Stations Increase the Radio-Frequency "Pollution"?
A common concern among the population is that installing new 5G Base Stations
(BSs) over a given geographic region may result in an uncontrollable increase
of Radio-Frequency "Pollution" (RFP). To face this dispute in a way that can be
understood by the layman, we develop a very simple model, which evaluates the
RFP at selected distances between the user and the 5G BS locations. We then
obtain closed-form expressions to quantify the RFP increase/decrease when
comparing a pair of alternative 5G deployments. Results show that a dense 5G
deployment is beneficial to the users living in proximity to the 5G BSs, with
an abrupt decrease of RFP (up to three orders of magnitude) compared to a
sparse deployment. We also analyze scenarios where the user equipment minimum
detectable signal threshold is increased, showing that in such cases a (slight)
increase of RFP may be experienced.Comment: Cite as: Luca Chiaraviglio, Giuseppe Bianchi, Nicola Blefari-Melazzi,
Marco Fiore, Will the Proliferation of 5G Base Stations Increase the
Radio-Frequency "Pollution"?, IEEE 91st Vehicular Technology Conference
(VTC-Spring), Antwerp, Belgium, May 202
Will the Proliferation of 5G Base Stations Increase the Radio-Frequency 'Pollution'?
A common concern among the population is that installing new 5G Base Stations (BSs) over a given geographic region may result in an uncontrollable increase of Radio-Frequency 'Pollution' (RFP). To face this dispute in a way that can be understood by the layman, we develop a very simple model, which evaluates the RFP at selected distances between the user and the 5G BS locations. We then obtain closed-form expressions to quantify the RFP increase/decrease when comparing a pair of alternative 5G deployments. Results show that a dense 5G deployment is beneficial to the users living in proximity to the 5G BSs, with an abrupt decrease of RFP (up to three orders of magnitude) compared to a sparse deployment. We also analyze scenarios where the user equipment minimum detectable signal threshold is increased, showing that in such cases a (slight) increase of RFP may be experienced
Analysis of electromagnetic pollution by means of geographic information system
Currently, telecommunications systems have become more widespread and there is still a discrepancy between whether or not non-ionizing radiation produces health problems in living beings at cellular level. From an experimental point of view, it is interesting to raise the correlation of high levels of electromagnetic pollution with health problems in urban populations which would make it possible to clearly determine the effects of this type of radiation on human health and the environment. By means of remote sensing, a geographic information system (GIS) has been developed for the analysis of electromagnetic pollution levels generated by emissions from non-ionizing radiation (NIR) sources in a city. A method for measuring electromagnetic pollution was applied, which allows the generation of a table of attributes of the GIS that is the input to generate by inverse distance weighting (IDW), the layer of electromagnetic pollution. The method, as a case study, was applied in the city of Manizales, located in Colombia, obtaining as a result a layer that allows evidence that the highest levels of electromagnetic pollution are concentrated in the most central area of the city. In this way, the effects of NIR on public health can be analyzed by means of correlations
"5G Densification Increases Human Exposure to Radio-Frequency Pollution": True or False?
A very popular theory circulating among non-scientific communities claims
that the massive deployment of 5G base stations over the territory, a.k.a. 5G
densification, always triggers an uncontrolled and exponential increase of
human exposure to Radio Frequency "Pollution" (RFP). To face such concern in a
way that can be understood by the layman, in this work we develop a very simple
model to compute the RFP, based on a set of worst-case and conservative
assumptions. We then provide closed-form expressions to evaluate the RFP
variation in a pair of candidate 5G deployments, subject to different
densification levels. Results, obtained over a wide set of representative 5G
scenarios, dispel the myth: 5G densification triggers an RFP decrease when the
radiated power from the 5G base stations is adjusted to ensure a minimum
sensitivity at the cell edge. Eventually, we analyze the conditions under which
the RFP may increase when the network is densified (e.g., when the radiated
power does not scale with the cell size), proving that the amount of RFP is
always controlled. Finally, the results obtained by simulation confirm the
outcomes of the RFP model
The Use of Camouflaged Cell Phone Towers for a Quality Urban Environment
The widespread use of cell phones has led to cell phone towers being located in many communities. These towers, also called base stations, incorporate electronic equipment and antennas that receive and transmit radiofrequency signals. Along with the towers, used for TV and line of sight microwave communication, the proliferation of these base stations is having a detrimental effect on urban esthetics. It is highly recommended for developing urban areas to consider the problem of these unsightly towers as a form of visual pollution, which increases in parallel with the rise of human population density, and also, the possible electromagnetic field (EMF) hazard due to the existence of the cell phone towers in the residential areas. This paper presents the feasibility of using camouflaged cell phone towers to improve the quality of the urban environment. Cell phone towers disguised as trees might address the visual pollution, while, at the same time, might also mitigate the possible EMF hazard by installing these disguised towers in free spaces, rather than on the roof of buildings, schools, hospitals, etc. The feasibility of implementing such a scenario for a quality urban environment in Koya city is discussed
Resource and power management in next generation networks
The limits of today’s cellular communication systems are constantly being tested by
the exponential increase in mobile data traffic, a trend which is poised to continue
well into the next decade. Densification of cellular networks, by overlaying smaller
cells, i.e., micro, pico and femtocells, over the traditional macrocell, is seen as an
inevitable step in enabling future networks to support the expected increases in data
rate demand. Next generation networks will most certainly be more heterogeneous
as services will be offered via various types of points of access (PoAs). Indeed, besides
the traditional macro base station, it is expected that users will also be able to
access the network through a wide range of other PoAs: WiFi access points, remote
radio-heads (RRHs), small cell (i.e., micro, pico and femto) base stations or even
other users, when device-to-device (D2D) communications are supported, creating
thus a multi-tiered network architecture. This approach is expected to enhance the
capacity of current cellular networks, while patching up potential coverage gaps.
However, since available radio resources will be fully shared, the inter-cell interference
as well as the interference between the different tiers will pose a significant
challenge. To avoid severe degradation of network performance, properly managing
the interference is essential. In particular, techniques that mitigate interference such
Inter Cell Interference Coordination (ICIC) and enhanced ICIC (eICIC) have been
proposed in the literature to address the issue. In this thesis, we argue that interference
may be also addressed during radio resource scheduling tasks, by enabling
the network to make interference-aware resource allocation decisions.
Carrier aggregation technology, which allows the simultaneous use of several
component carriers, on the other hand, targets the lack of sufficiently large portions
of frequency spectrum; a problem that severely limits the capacity of wireless networks.
The aggregated carriers may, in general, belong to different frequency bands,
and have different bandwidths, thus they also may have very different signal propagation
characteristics. Integration of carrier aggregation in the network introduces
additional tasks and further complicates interference management, but also opens
up a range of possibilities for improving spectrum efficiency in addition to enhancing
capacity, which we aim to exploit. In this thesis, we first look at the resource allocation in problem in dense multitiered
networks with support for advanced features such as carrier aggregation and
device-to-device communications. For two-tiered networks with D2D support, we
propose a centralised, near optimal algorithm, based on dynamic programming principles,
that allows a central scheduler to make interference and traffic-aware scheduling
decisions, while taking into consideration the short-lived nature of D2D links.
As the complexity of the central scheduler increases exponentially with the number
of component carriers, we further propose a distributed heuristic algorithm to tackle
the resource allocation problem in carrier aggregation enabled dense networks. We
show that the solutions we propose perform significantly better than standard solutions
adopted in cellular networks such as eICIC coupled with Proportional Fair
scheduling, in several key metrics such as user throughput, timely delivery of content
and spectrum and energy efficiency, while ensuring fairness for backward compatible
devices.
Next, we investigate the potentiality to enhance network performance by enabling
the different nodes of the network to reduce and dynamically adjust the
transmit power of the different carriers to mitigate interference. Considering that
the different carriers may have different coverage areas, we propose to leverage this
diversity, to obtain high-performing network configurations. Thus, we model the
problem of carrier downlink transmit power setting, as a competitive game between
teams of PoAs, which enables us to derive distributed dynamic power setting algorithms.
Using these algorithms we reach stable configurations in the network,
known as Nash equilibria, which we show perform significantly better than fixed
power strategies coupled with eICIC
Artificial Intelligence-based Cybersecurity for Connected and Automated Vehicles
The damaging effects of cyberattacks to an industry like the Cooperative Connected and Automated Mobility (CCAM) can be tremendous. From the least important to the worst ones, one can mention for example the damage in the reputation of vehicle manufacturers, the increased denial of customers to adopt CCAM, the loss of working hours (having direct impact on the European GDP), material damages, increased environmental pollution due e.g., to traffic jams or malicious modifications in sensors’ firmware, and ultimately, the great danger for human lives, either they are drivers, passengers or pedestrians.
Connected vehicles will soon become a reality on our roads, bringing along new services and capabilities, but also technical challenges and security threats. To overcome these risks, the CARAMEL project has developed several anti-hacking solutions for the new generation of vehicles.
CARAMEL (Artificial Intelligence-based Cybersecurity for Connected and Automated Vehicles), a research project co-funded by the European Union under the Horizon 2020 framework programme, is a project consortium with 15 organizations from 8 European countries together with 3 Korean partners. The project applies a proactive approach based on Artificial Intelligence and Machine Learning techniques to detect and prevent potential cybersecurity threats to autonomous and connected vehicles. This approach has been addressed based on four fundamental pillars, namely: Autonomous Mobility, Connected Mobility, Electromobility, and Remote Control Vehicle. This book presents theory and results from each of these technical directions
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