35 research outputs found
Antenna array calibration in wireless communications
Imperial Users onl
Advanced array processing techniques and systems
Research and development on smart antennas, which are recognized as a promising technique to improve the performance of mobile communications, have been extensive in the recent years. Smart antennas combine multiple antenna elements with a signal processing capability in both space and time to optimize its radiation and reception pattern automatically in response to the signal environment. This paper concentrates on the signal processing aspects of smart antenna systems. Smart antennas are often classified as either switched-beam or adaptive-array systems, for which a variety of algorithms have been developed to enhance the signal of interest and reject the interference. The antenna systems need to differentiate the desired signal from the interference, and normally requires either a priori knowledge or the signal direction to achieve its goal. There exists a variety of methods for direction of arrival (DOA) estimation with conflicting demands of accuracy and computation. Similarly, there are many algorithms to compute array weights to direct the maximum radiation of the array pattern toward the signal and place nulls toward the interference, each with its convergence property and computational complexity. This paper discusses some of the typical algorithms for DOA estimation and beamforming. The concept and details of each algorithm are provided. Smart antennas can significantly help in improving the performance of communication systems by increasing channel capacity and spectrum efficiency, extending range coverage, multiplexing channels with spatial division multiple access (SDMA), and compensating electronically for aperture distortion. They also reduce delay spread, multipath fading, co-channel interference, system complexity, bit error rates, and outage probability. In addition, smart antennas can locate mobile units or assist the location determination through DOA and range estimation. This capability can support and benefit many location-based services including emergency assistance, tracking services, safety services, billing services, and information services such as navigation, weather, traffic, and directory assistance
Recommended from our members
Intelligent joint channel parameter estimation techniques for mobile wireless positioning applications
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Mobile wireless positioning has recently received great attention. For mobile wireless
communication networks, an inherently suitable approach is to obtain the parameters
that are used for positioning estimates from the radio signal measurements between a
mobile device and one or more xed base stations. However, obtaining accurate estimates of these location-dependent channel parameters is a challenging task. The focus of this thesis is on the estimation of these channel parameters for mobile wireless positioning
applications. In particular, we investigate novel estimators that jointly estimate
more than one type of channel parameters. We rst perform a comprehensive critical
review on the most recent and popular joint channel parameter estimation techniques.
Secondly, we improve a state-of-the-art technique, namely the Space Alternating Generalised Expectation maximisation (SAGE) algorithm by employing adaptive interference
cancellation to improve the estimation accuracy of weaker paths. Thirdly, a novel intelligent channel parameter estimation technique using Evolution Strategy (ES) is proposed to overcome the drawbacks of the existing iterative maximum likelihood methods. Furthermore, given that in reality it is di cult to obtain the number of multipath in advance, we propose a two tier Hierarchically Organised ES to jointly estimate the number of multipath as well as the channel parameters. Finally, we extend the proposed ES method to further estimate the Doppler shift in mobile environments. Our proposed intelligent joint channel estimation techniques are shown to exhibit excellent performance even with low Signal to Noise Ratio (SNR) channel conditions as well as robust against uncertainties in initialisations.EPSRC and Cambridge Silicon Radi
Optimizing Melodic Extraction Algorithm for Jazz Guitar Recordings Using Genetic Algorithms
(Abstract to follow
Formación de Haz Adaptativo para Objetos Móviles usando Algoritmos Genéticos
Context: This works investigates the use of Genetic Algorithm (GA) for beamforming on a Code Division Multiple Access (CDMA) environment under different Signal-to-Noise Ratios (SNR), assuming a reference signal is known.Method: The GA is a method inspired in evolutionary principles to optimize an objective function by choosing the best candidates of a population. The population is randomly generated to ensure high diversity and get a global optimization. On the other hand, the Least Means squares (LMS) algorithm is an adaptive algorithm with guaranteed convergence as long as a reference signal is known.Results: The GA converged faster than the LMS in all tested scenarios. Besides, GA achieved best results in pointing the beam for uncorrelated static sources. Additionally, proper tuning of GA parameters allowed fast convergence and improved tracking of moving targets.Conclusions: The simulation results confirm that the GA is able to obtain a convergent and accurate tool for beamforming and tracking of moving targets, given a reference signal. Hence, GA turns to be promising in replacing LMS on Smart Antenna Systems for increasing channel capacity.Contexto: En este trabajo se investiga el uso de un Algoritmo Genético (GA) para la conformación del haz de un arreglo de antenas en ambientes de Acceso Múltiple por División de Código (CDMA) bajo diferentes relaciones Señal a Ruido, asumiendo que la señal de referencia es conocida.Método: El Algoritmo Genético es un método inspirado en principios evolutivos, usado para optimizar una función objetivo seleccionando los mejores candidatos de una población. La población es generada aleatoriamente para asegurar alta diversidad y conseguir una optimación global. Por otro lado, el algoritmo LMS es un algoritmo que garantiza la convergencia siempre y cuando la señal de referencia sea conocida.Resultados: El GA converge más rápidamente en que el algoritmo LMS en todos los escenarios probados. Además, el GA consiguió mejores resultados apuntando el haz para fuentes estáticas descorrelacionadas. Adicionalmente, una apropiada selección de los parámetros del GA permite una mayor velocidad de convergencia y un mejorado rastreamiento de fuentes en movimiento.Conclusiones: Los resultados de las simulaciones confirman que el GA es una herramienta capaz de obtener una convergencia y precisión en la conformación del haz y el rastreamiento de fuentes en movimiento dada una señal de referencia. Por lo tanto, el GA resulta prometedor para sustituir el algoritmo LMS en sistemas de antenas inteligentes y aumentar la capacidad del canal
Radio resource scheduling and smart antennas in cellular CDMA communication systems
This thesis discusses two important subjects in multi-user wireless communication systems, radio resource scheduler (RRS) and smart antenna. RRS optimizes the available resources among users to increase the capacity and enhance the system performance. The RRS optimization procedure is based on the network conditions (link gain, interference, …) and the required quality of service (QoS) of each user. The CDMA system capacity and performance can be greatly enhanced by reducing the interferences. One of the techniques to reduce the interferences is by exploiting the spatial structure of the interferences. This could be done by using smart antennas which are the second subject of this thesis. The joining procedures of the smart antennas and RRS are discussed as well.
Multi-Objective optimization approach is proposed to solve the radio resource scheduler problems. New algorithms are derived namely the Multi-Objective Distributed Power Control (MODPC) algorithm, Multi-Objective Distributed Power and Rate Control (MODPRC) algorithm, and Maximum Throughput and Minimum Power Control (MTMPC) algorithm. Other modified versions of these algorithms have been obtained such as Multi-Objective Totally Distributed Power and Rate Control (MOTDPRC) algorithm, which can be used when only one-bit quantized Carrier to Interference Ratio (CIR) is available.
Kalman filter is proposed as a second technique to solve the RRS problem. The motivation to use Kalman filter is the known fact that Kalman filter is the optimum linear tracking device on the basis of second order statistics. The RRS is formulated in state space form. Two different formulations are introduced.
New simple and efficient estimation of the CIR is presented. The method is used to construct a novel power control algorithm called Estimated Step Power Control (ESPC) algorithm.
The smart antenna concepts and algorithms are discussed. New adaptation algorithm is proposed. It is called General Minimum Variance Distortionless Response (GMVDR) algorithm.
The joining of MIMO smart antennas and radio resource scheduler is investigated. Kalman filter is suggested as a simple algorithm to join smart antenna and multi-rate power control in a new way. The performance of the RRS of CDMA cellular communication systems in the presence of smart antenna is studied.reviewe
Development of new array signal processing techniques using swarm intelligence
Ankara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent University, 2010.Thesis (Ph. D.) -- Bilkent University, 2010.Includes bibliographical references leaves 144-158.In this thesis, novel array signal processing techniques are proposed for identifi-
cation of multipath communication channels based on cross ambiguity function
(CAF) calculation, swarm intelligence and compressed sensing (CS) theory. First
technique detects the presence of multipath components by integrating CAFs of
each antenna output in the array and iteratively estimates direction-of-arrivals
(DOAs), time delays and Doppler shifts of a known waveform. Second technique
called particle swarm optimization-cross ambiguity function (PSO-CAF) makes
use of the CAF calculation to transform the received antenna array outputs to
delay-Doppler domain for efficient exploitation of the delay-Doppler diversity of
the multipath components. Clusters of multipath components are identified by
using a simple amplitude thresholding in the delay-Doppler domain. PSO is
used to estimate parameters of the multipath components in each cluster. Third
proposed technique combines CS theory, swarm intelligence and CAF computation.
Performance of standard CS formulations based on discretization of the
multipath channel parameter space degrade significantly when the actual channel
parameters deviate from the assumed discrete set of values. To alleviate this
“off-grid”problem, a novel technique by making use of the PSO, that can also be
used in applications other than the multipath channel identification is proposed.
Performances of the proposed techniques are verified both on sythetic and real
data.Güldoğan, Mehmet BurakPh.D
Smart-antenna techniques for energy-efficient wireless sensor networks used in bridge structural health monitoring
Abstract: It is well known that wireless sensor networks differ from other computing platforms in that 1- they typically require a minimal amount of computing power at the nodes; 2- it is often desirable for sensor nodes to have drastically low power consumption. The main benefit of the this work is a substantial network life before batteries need to be replaced or, alternatively, the capacity to function off of modest environmental energy sources (energy harvesting). In the context of Structural Health Monitoring (SHM), battery replacement is particularly problematic since nodes can be in difficult to access locations. Furthermore, any intervention on a bridge may disrupt normal bridge operation, e.g. traffic may need to be halted. In this regard, switchbeam smart antennas in combination with wireless sensor networks (WSNs) have shown great potential in reducing implementation and maintenance costs of SHM systems. The main goal of implementing switch-beam smart antennas in our application is to reduce power consumption, by focusing the radiated energy only where it is needed. SHM systems capture the dynamic vibration information of a bridge structure in real-time in order to assess the health of the structure and to predict failures. Current SHM systems are based on piezoelectric patch sensors. In addition, the collection of data from the plurality of sensors distributed over the span of the bridge is typically performed through an expensive and bulky set of shielded wires which routes the information to a data sink at one end of the structure. The installation, maintenance and operational costs of such systems are extremely high due to high power consumption and the need for periodic maintenance. Wireless sensor networks represent an attractive alternative, in terms of cost, ease of maintenance, and power consumption. However, network lifetime in terms of node battery life must be very long (ideally 5–10 years) given the cost and hassle of manual intervention. In this context, the focus of this project is to reduce the global power consumption of the SHM system by implementing switched-beam smart antennas jointly with an optimized MAC layer. In the first part of the thesis, a sensor network platform for bridge SHM incorporating switched-beam antennas is modelled and simulated. where the main consideration is the joint optimization of beamforming parameters, MAC layer, and energy consumption. The simulation model, built within the Omnet++ network simulation framework, incorporates the energy consumption profiles of actual selected components (microcontroller, radio interface chip). The energy consumption and packet delivery ratio (PDR) of the network with switched-beam antennas is compared with an equivalent network based on omnidirectional antennas. In the second part of the thesis, this system model is leveraged to examine two distinct but interrelated aspects: Gallium Arsenide (GaAs) based solar energy harvesting and switched-beam antenna strategies. The main consideration here is the joint optimization of solar energy harvesting and switchedbeam directional antennas, where an equivalent network based on omnidirectional antennas acts as a baseline reference for comparison purposes.Il est bien connu que les réseaux de capteurs sans fils diffèrent des autres plateformes informatiques
étant donné 1- qu’ils requièrent typiquement une puissance de calcul minimale aux
noeuds du réseau ; 2- qu’il est souvent désirable que les noeuds capteurs aient une consommation
d’énergie dramatiquement faible. La principale retombée de ce travail réside en la durée
de vie allongée du réseau avant que les piles ne doivent être remplacées ou, alternativement,
la capacité de fonctionner indéfiniment à partir de modestes sources d’énergie ambiente (glânage
d’énergie). Dans le contexte du contrôle de la santé structurale (CSS), le remplacement de
piles est particulièrement problématique puisque les noeuds peuvent se trouver en des endroits
difficiles d’accès. De plus, toute intervention sur un pont implique une perturbation de l’opération
normale de la structure, par exemple un arrêt du traffic. Dans ce contexte, les antennes
intelligentes à commutation de faisceau en combinaison avec les réseaux de capteurs sans fils
ont démontré un grand potentiel pour réduire les coûts de réalisation et d’entretien de systèmes
de CSS. L’objectif principal de l’intégration d’antennes à commutation de faisceau dans notre
application réside dans la réduction de la consommation énergétique, réalisée en concentrant
l’énergie radiée uniquement là où elle est nécessaire. Les systèmes de CSS capturent l’information
dynamique de vibration d’une structure de pont en temps réel de manière à évaluer la santé
de la structure et prédire les failles. Les systèmes courants de CSS sont basés sur des senseurs
piézoélectriques planaires. De plus, la collecte de données à partir de la pluralité de senseurs
distribués sur l’étendue du pont est typiquement effectuée par le biais d’un ensemble coûteux
et encombrant de câbles blindés qui véhiculent l’information jusqu’à un point de collecte à une
extremité de la structure. L’installation, l’entretien, et les coûts opérationnels de tels systèmes
sont extrêmement élevés étant donné la consommation de puissance élevée et le besoin d’entretien
régulier. Les réseaux de capteurs sans fils représentent une alternative attrayante, en termes
de coût, facilité d’entretien et consommation énergétique. Toutefois, la vie de réseau en termes
de la durée de vie des piles doit être très longue (idéalement de 5 à 10 ans) étant donné le coût
et les problèmes liés à l’intervention manuelle. Dans ce contexte, ce projet se concentre sur la
réduction de la consommation de puissance globale d’un système de CSS en y intégrant des
antennes intelligentes à commutation de faisceau conjointement avec une couche d’accès au
médium (couche MAC) optimisée. Dans la première partie de la thèse, une plateforme de réseau
de capteurs sans fils pour le CSS d’un pont incorporant des antennes à commutation de faisceaux
est modélisé et simulé, avec pour considération principale l’optimisation des paramètres
de sélection de faisceau, de la couche MAC et de la consommation d’énergie. Le modèle de
simulation, construit dans le logiciel de simulation de réseaux Omnet++, incorpore les profils
de consommation d’énergie de composants réels sélectionnés (microcontrôleur, puce d’interface
radio). La consommation d’énergie et le taux de livraison de paquets du réseau avec antennes
à commutation de faisceau est comparé avec un réseau équivalent basé sur des antennes omnidirectionnelles.
Dans la deuxième partie de la thèse, le modèle système proposé est mis à
contribution pour examiner deux aspects distrincts mais interreliés : le glânage d’énergie à partir
de cellules solaire à base d’arséniure de Gallium (GaAs) et les stratégies liées aux antennes
à commutation de faisceau. La considération principale ici est l’optimisation conjointe du glânage d’énergie et des antennes à commutation de faisceau, en ayant pour base de comparaison
un réseau équivalent à base d’antennes omnidirectionnelles
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