117 research outputs found
Opportunistic Angle of Arrival Estimation in Impaired Scenarios
This work if focused on the analysis and the development of Angle of Arrival (AoA) radio localization methods. The radio positioning system considered is constituted by a radio source and by a receiving array of antennas. The positioning algorithms treated in this work are designed to have a passive and opportunistic approach. The opportunistic attribute implies that the radio localization algorithms are designed to provide the AoA estimation with nearly-zero information on the transmitted signals. No training sequences or waveforms custom designed for localization are taken into account. The localization is termed passive since there is no collaboration between the transmitter and the receiver during the localization process. Then, the algorithms treated in this work are designed to eavesdrop already existing communication signals and to locate their radio source with nearly-zero knowledge of the signal and without the collaboration of the transmitting node. First of all, AoA radio localization algorithms can be classified in terms of involved signals (narrowband or broadband), antenna array pattern (L-shaped, circular, etc.), signal structure (sinusoidal, training sequences, etc.), Differential Time of Arrival (D-ToA) / Differential Phase of Arrival (D-PoA) and collaborative/non collaborative. Than, the most detrimental effects for radio communications are treated: the multipath (MP) channels and the impaired hardware. A geometric model for the MP is analysed and implemented to test the robustness of the proposed methods. The effects of MP on the received signals statistics from the AoA estimation point-of-view are discussed. The hardware impairments for the most common components are introduced and their effects in the AoA estimation process are analysed. Two novel algorithms that exploits the AoA from signal snapshots acquired sequentially with a time division approach are presented. The acquired signals are QAM waveforms eavesdropped from a pre-existing communication. The proposed methods, namely Constellation Statistical Pattern IDentification and Overlap (CSP-IDO) and Bidimensional CSP-IDO (BCID), exploit the probability density function (pdf) of the received signals to obtain the D-PoA. Both CSP-IDO and BCID use the statistical pattern of received signals exploiting the transmitter statistical signature. Since the presence of hardware impairments modify the statistical pattern of the received signals, CSP-IDO and BCID are able to exploit it to improve the performance with respect to (w.r.t.) the ideal case. Since the proposed methods can be used with a switched antenna architecture they are implementable with a reduced hardware contrariwise to synchronous methods like MUltiple SIgnal Classification (MUSIC) that are not applicable. Then, two iterative AoA estimation algorithms for the dynamic tracking of moving radio sources are implemented. Statistical methods, namely PF, are used to implement the iterative tracking of the AoA from D-PoA measures in two different scenarios: automotive and Unmanned Aerial Vehicle (UAV). The AoA tracking of an electric car signalling with a IEEE 802.11p-like standard is implemented using a test-bed and real measures elaborated with a the proposed Particle Swarm Adaptive Scattering (PSAS) algorithm. The tracking of a UAV moving in the 3D space is investigated emulating the UAV trajectory using the proposed Confined Area Random Aerial Trajectory Emulator (CARATE) algorithm
1-D broadside-radiating leaky-wave antenna based on a numerically synthesized impedance surface
A newly-developed deterministic numerical technique for the automated design of metasurface antennas is applied here for the first time to the design of a 1-D printed Leaky-Wave Antenna (LWA) for broadside radiation. The surface impedance synthesis process does not require any a priori knowledge on the impedance pattern, and starts from a mask constraint on the desired far-field and practical bounds on the unit cell impedance values. The designed reactance surface for broadside radiation exhibits a non conventional patterning; this highlights the merit of using an automated design process for a design well known to be challenging for analytical methods. The antenna is physically implemented with an array of metal strips with varying gap widths and simulation results show very good agreement with the predicted performance
Beam scanning by liquid-crystal biasing in a modified SIW structure
A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium
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Design and Implementation of System Components for Radio Frequency Based Asset Tracking Devices to Enhance Location Based Services. Study of angle of arrival techniques, effects of mutual coupling, design of an angle of arrival algorithm, design of a novel miniature reconfigurable antenna optimised for wireless communication systems
The angle of arrival estimation of multiple sources plays a vital role in the field of array signal
processing as MIMO systems can be employed at both the transmitter and the receiver end
and the system capacity, reliability and throughput can be significantly increased by using array
signal processing. Almost all applications require accurate direction of arrival (DOA) estimation
to localize the sources of the signals. Another important parameter of localization systems is
the array geometry and sensor design which can be application specific and is used to
estimate the DOA.
In this work, various array geometries and arrival estimation algorithms are studied and then a
new scheme for multiple source estimation is proposed and evaluated based on the
performance of subspace and non-subspace decomposition methods. The proposed scheme
has shown to outperform the conventional Multiple Signal Classification (MUSIC) estimation
and Bartlett estimation techniques. The new scheme has a better performance advantage at
low and high signal to noise ratio values (SNRs).
The research work also studies different array geometries for both single and multiple incident
sources and proposes a geometry which is cost effective and efficient for 3, 4, and 5 antenna
array elements. This research also considers the shape of the ground plane and its effects on
the angle of arrival estimation and in addition it shows how the mutual couplings between the
elements effect the overall estimation and how this error can be minimised by using a decoupling
matrix.
At the end, a novel miniaturised multi element reconfigurable antenna to represent the receiver
base station is designed and tested. The antenna radiation patterns in the azimuth angle are
almost omni-directional with linear polarisation. The antenna geometry is uniplanar printed logspiral
with striplines feeding network and biased components to improve the impedance
bandwidth. The antenna provides the benefit of small size, and re-configurability and is very
well suited for the asset tracking applications
Design of Reconfigurable Intelligent Surfaces for Wireless Communication: A Review
Existing literature reviews predominantly focus on the theoretical aspects of
reconfigurable intelligent surfaces (RISs), such as algorithms and models,
while neglecting a thorough examination of the associated hardware components.
To bridge this gap, this research paper presents a comprehensive overview of
the hardware structure of RISs. The paper provides a classification of RIS cell
designs and prototype systems, offering insights into the diverse
configurations and functionalities. Moreover, the study explores potential
future directions for RIS development. Notably, a novel RIS prototype design is
introduced, which integrates seamlessly with a communication system for
performance evaluation through signal gain and image formation experiments. The
results demonstrate the significant potential of RISs in enhancing
communication quality within signal blind zones and facilitating effective
radio wave imaging
Applications of Antenna Technology in Sensors
During the past few decades, information technologies have been evolving at a tremendous rate, causing profound changes to our world and to our ways of living. Emerging applications have opened u[ new routes and set new trends for antenna sensors. With the advent of the Internet of Things (IoT), the adaptation of antenna technologies for sensor and sensing applications has become more important. Now, the antennas must be reconfigurable, flexible, low profile, and low-cost, for applications from airborne and vehicles, to machine-to-machine, IoT, 5G, etc. This reprint aims to introduce and treat a series of advanced and emerging topics in the field of antenna sensors
The electronically steerable parasitic array radiator antenna for wireless communications : signal processing and emerging techniques
Smart antenna technology is expected to play an important role in future wireless
communication networks in order to use the spectrum efficiently, improve the
quality of service, reduce the costs of establishing new wireless paradigms and
reduce the energy consumption in wireless networks. Generally, smart antennas
exploit multiple widely spaced active elements, which are connected to separate
radio frequency (RF) chains. Therefore, they are only applicable to base stations
(BSs) and access points, by contrast with modern compact wireless terminals with
constraints on size, power and complexity. This dissertation considers an alternative
smart antenna system the electronically steerable parasitic array radiator
(ESPAR) which uses only a single RF chain, coupled with multiple parasitic elements.
The ESPAR antenna is of significant interest because of its
flexibility in beamforming by tuning a number of easy-to-implement reactance loads connected
to parasitic elements; however, parasitic elements require no expensive RF circuits.
This work concentrates on the study of the ESPAR antenna for compact
transceivers in order to achieve some emerging techniques in wireless communications.
The work begins by presenting the work principle and modeling of the ESPAR
antenna and describes the reactance-domain signal processing that is suited to the
single active antenna array, which are fundamental factors throughout this thesis.
The major contribution in this chapter is the adaptive beamforming method
based on the ESPAR antenna. In order to achieve fast convergent beamforming
for the ESPAR antenna, a modified minimum variance distortionless response
(MVDR) beamfomer is proposed. With reactance-domain signal processing, the
ESPAR array obtains a correlation matrix of receive signals as the input to the
MVDR optimization problem. To design a set of feasible reactance loads for a desired
beampattern, the MVDR optimization problem is reformulated as a convex
optimization problem constraining an optimized weight vector close to a feasible
solution. Finally, the necessary reactance loads are optimized by iterating the convex problem and a simple projector. In addition, the generic algorithm-based
beamforming method has also studied for the ESPAR antenna.
Blind interference alignment (BIA) is a promising technique for providing an optimal
degree of freedom in a multi-user, multiple-inputsingle-output broadcast
channel, without the requirements of channel state information at the transmitters.
Its key is antenna mode switching at the receive antenna. The ESPAR
antenna is able to provide a practical solution to beampattern switching (one
kind of antenna mode switching) for the implementation of BIA. In this chapter,
three beamforming methods are proposed for providing the required number of
beampatterns that are exploited across one super symbol for creating the channel
fluctuation patterns seen by receivers. These manually created channel
fluctuation
patterns are jointly combined with the designed spacetime precoding in order to
align the inter-user interference. Furthermore, the directional beampatterns designed
in the ESPAR antenna are demonstrated to improve the performance of
BIA by alleviating the noise amplification.
The ESPAR antenna is studied as the solution to interference mitigation in small
cell networks. Specifically, ESPARs analog beamforming presented in the previous
chapter is exploited to suppress inter-cell interference for the system scenario,
scheduling only one user to be served by each small BS at a single time. In
addition, the ESPAR-based BIA is employed to mitigate both inter-cell and intracell
interference for the system scenario, scheduling a small number of users to be
simultaneously served by each small BS for a single time.
In the cognitive radio (CR) paradigm, the ESPAR antenna is employed for spatial
spectrum sensing in order to utilize the new angle dimension in the spectrum
space besides the conventional frequency, time and space dimensions. The twostage
spatial spectrum sensing method is proposed based on the ESPAR antenna
being targeted at identifying white spectrum space, including the new angle dimension.
At the first stage, the occupancy of a specific frequency band is detected
by conventional spectrum-sensing methods, including energy detector and
eigenvalue-based methods implemented with the switched-beam ESPAR antenna. With the presence of primary users, their directions are estimated at the second
stage, by high-resolution angle-of-arrival (AoA) estimation algorithms. Specifically, the compressive sensing technology has been studied for AoA detection with
the ESPAR antenna, which is demonstrated to provide high-resolution estimation
results and even to outperform the reactance-domain multiple signal classification
The 1st International Conference on Computational Engineering and Intelligent Systems
Computational engineering, artificial intelligence and smart systems constitute a hot multidisciplinary topic contrasting computer science, engineering and applied mathematics that created a variety of fascinating intelligent systems. Computational engineering encloses fundamental engineering and science blended with the advanced knowledge of mathematics, algorithms and computer languages. It is concerned with the modeling and simulation of complex systems and data processing methods. Computing and artificial intelligence lead to smart systems that are advanced machines designed to fulfill certain specifications. This proceedings book is a collection of papers presented at the first International Conference on Computational Engineering and Intelligent Systems (ICCEIS2021), held online in the period December 10-12, 2021. The collection offers a wide scope of engineering topics, including smart grids, intelligent control, artificial intelligence, optimization, microelectronics and telecommunication systems. The contributions included in this book are of high quality, present details concerning the topics in a succinct way, and can be used as excellent reference and support for readers regarding the field of computational engineering, artificial intelligence and smart system
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