Space time transceiver design over multipath fading channels

Imperial Users onl

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

Twenty-five years of sensor array and multichannel signal processing: a review of progress to date and potential research directions

In this article, a general introduction to the area of sensor array and multichannel signal processing is provided, including associated activities of the IEEE Signal Processing Society (SPS) Sensor Array and Multichannel (SAM) Technical Committee (TC). The main technological advances in five SAM subareas made in the past 25 years are then presented in detail, including beamforming, direction-of-arrival (DOA) estimation, sensor location optimization, target/source localization based on sensor arrays, and multiple-input multiple-output (MIMO) arrays. Six recent developments are also provided at the end to indicate possible promising directions for future SAM research, which are graph signal processing (GSP) for sensor networks; tensor-based array signal processing, quaternion-valued array signal processing, 1-bit and noncoherent sensor array signal processing, machine learning and artificial intelligence (AI) for sensor arrays; and array signal processing for next-generation communication systems

Development of a Resource Manager Framework for Adaptive Beamformer Selection

Adaptive digital beamforming (DBF) algorithms are designed to mitigate the effects of interference and noise in the electromagnetic (EM) environment encountered by modern electronic support (ES) receivers. Traditionally, an ES receiver employs a single adaptive DBF algorithm that is part of the design of the receiver system. While the traditional form of receiver implementation is effective in many scenarios it has inherent limitations. This dissertation proposes a new ES receiver framework capable of overcoming the limitations of traditional ES receivers. The proposed receiver framework is capable of forming multiple, independent, simultaneous adaptive digital beams toward multiple signals of interest in an electromagnetic environment. The main contribution of the research is the development, validation, and verification of a resource manager (RM) algorithm. The RM estimates a set of parameters that characterizes the electromagnetic environment and selects an adaptive digital beam forming DBF algorithm for implementation toward all each signal of interest (SOI) in the environment. Adaptive DBF algorithms are chosen by the RM based upon their signal to interference plus noise ratio (SINR) improvement ratio and their computational complexity. The proposed receiver framework is demonstrated to correctly estimate the desired electromagnetic parameters and select an adaptive DBF from the LUT

Joint Communication and Positioning based on Channel Estimation

Mobile wireless communication systems have rapidly and globally become an integral part of everyday life and have brought forth the internet of things. With the evolution of mobile wireless communication systems, joint communication and positioning becomes increasingly important and enables a growing range of new applications. Humanity has already grown used to having access to multimedia data everywhere at every time and thereby employing all sorts of location-based services. Global navigation satellite systems can provide highly accurate positioning results whenever a line-of-sight path is available. Unfortunately, harsh physical environments are known to degrade the performance of existing systems. Therefore, ground-based systems can assist the existing position estimation gained by satellite systems. Determining positioning-relevant information from a unified signal structure designed for a ground-based joint communication and positioning system can either complement existing systems or substitute them. Such a system framework promises to enhance the existing systems by enabling a highly accurate and reliable positioning performance and increased coverage. Furthermore, the unified signal structure yields synergetic effects. In this thesis, I propose a channel estimation-based joint communication and positioning system that employs a virtual training matrix. This matrix consists of a relatively small training percentage, plus the detected communication data itself. Via a core semi- blind estimation approach, this iteratively includes the already detected data to accurately determine the positioning-relevant parameter, by mutually exchanging information between the communication part and the positioning part of the receiver. Synergy is created. I propose a generalized system framework, suitable to be used in conjunction with various communication system techniques. The most critical positioning-relevant parameter, the time-of-arrival, is part of a physical multipath parameter vector. Estimating the time-of-arrival, therefore, means solving a global, non-linear, multi-dimensional optimization problem. More precisely, it means solving the so-called inverse problem. I thoroughly assess various problem formulations and variations thereof, including several different measurements and estimation algorithms. A significant challenge, when it comes to solving the inverse problem to determine the positioning-relevant path parameters, is imposed by realistic multipath channels. Most parameter estimation algorithms have proven to perform well in moderate multipath environments. It is mathematically straightforward to optimize this performance in the sense that the number of observations has to exceed the number of parameters to be estimated. The typical parameter estimation problem, on the other hand, is based on channel estimates, and it assumes that so-called snapshot measurements are available. In the case of realistic channel models, however, the number of observations does not necessarily exceed the number of unknowns. In this thesis, I overcome this problem, proposing a method to reduce the problem dimensionality via joint model order selection and parameter estimation. Employing the approximated and estimated parameter covariance matrix inherently constrains the estimation problem’s model order selection to result in optimal parameter estimation performance and hence optimal positioning performance. To compare these results with the optimally achievable solution, I introduce a focused order-related lower bound in this thesis. Additionally, I use soft information as a weighting matrix to enhance the positioning algorithm positioning performance. For demonstrating the feasibility and the interplay of the proposed system components, I utilize a prototype system, based on multi-layer interleave division multiple access. This proposed system framework and the investigated techniques can be employed for multiple existing systems or build the basis for future joint communication and positioning systems. The assessed estimation algorithms are transferrable to all kinds of joint communication and positioning system designs. This thesis demonstrates their capability to, in principle, successfully cope with challenging estimation problems stemming from harsh physical environments

Estimation efficace des paramètres de signaux d'usagers radio-mobile par traitement avec antenne-réseau

Cette thèse aborde le problème d’estimation des paramètres de signaux d’usagers radio-mobile par traitement avec antenne-réseau. On adopte une approche de traitement théorique rigoureuse au problème en tentant de pallier aux limitations et désavantages des méthodes d’estimation existantes en ce domaine. Les chapitres principaux ont été rédigés en couvrant uniquement les aspects théoriques en lien aux contributions principales, tout en présentant une revue de littérature adéquate sur les sujets concernés. La thèse présente essentiellement trois volets distincts en lien à chacune des contributions en question. Suite à une revue des notions de base, on montre d’abord comment une méthode d’estimation exploitant des statistiques d’ordre supérieur a pu être développée à partir de l’amélioration d’un algorithme existant en ce domaine. On présente ensuite le cheminement qui a conduit à l’élaboration d’une technique d’estimation non linéaire exploitant les propriétés statistiques spécifiques des enveloppes complexes reçues, et ne possédant pas les limitations des algorithmes du second et quatrième ordre. Finalement, on présente le développement relatif à un algorithme d’estimation exploitant le caractère cyclostationnaire intrinsèque des signaux de communication dans un environnement asynchrone naturel. On montre comment un tel algorithme parvient à estimer la matrice de canal des signaux incidents indépendamment du caractère de corrélation spatiotemporel du bruit, et permettant de ce fait même une pleine exploitation du degré de liberté du réseau. La procédure d’estimation consiste en la résolution d’un problème de diagonalisation conjointe impliquant des matrices cibles issues d’une opération différentielle entre des matrices d’autocorrélation obtenues uniquement à partir de statistiques d’ordre deux. Pour chacune des contributions, des résultats de simulations sont présentés afin de confirmer l’efficacité des méthodes proposées.This thesis addresses the problem of parameter estimation of radio signals from mobile users using an antenna array. A rigorous theoretical approach to the problem is adopted in an attempt to overcome the limitations and disadvantages of existing estimation methods in this field. The main chapters have been written covering only the theoretical aspects related to the main contributions of the thesis, while at the same time providing an appropriate literature review on the considered topics. The thesis is divided into three main parts related to the aforesaid contributions. Following a review of the basics concepts in antenna array processing techniques for signal parameter estimation, we first present an improved version of an existing estimation algorithm expoiting higher-order statistics of the received signals. Subsequently, we show how a nonlinear estimation technique exploiting the specific statistical distributions of the received complex envelopes at the array can be developed in order to overcome the limitations of second and fourth-order algorithms. Finally, we present the development of an estimation algorithm exploiting the cyclostationary nature of communication signals in a natural asynchronous environment. We show how such an algorithm is able to estimate the channel matrix of the received signals independently of the spatial or temporal correlation structure of the noise, thereby enabling a full exploitation of the array’s degree of freedom. The estimation process is carried out by solving a joint diagonalization problem involving target matrices computed by a differential operation between autocorrelation matrices obtained by the sole use of second-order statistics. Various simulation experiments are presented for each contribution as a means of supporting and evidencing the effectiveness of the proposed methods

Characterisation of MIMO radio propagation channels

Due to the incessant requirement for higher performance radio systems, wireless designers have been constantly seeking ways to improve spectrum efficiency, link reliability, service quality, and radio network coverage. During the past few years, space-time technology which employs multiple antennas along with suitable signalling schemes and receiver architectures has been seen as a powerful tool for the implementation of the aforementioned requirements. In particular, the concept of communications via Multiple-Input Multiple-Output (MIMO) links has emerged as one of the major contending ideas for next generation ad-hoc and cellular systems. This is inherently due to the capacities expected when multiple antennas are employed at both ends of the radio link. Such a mobile radio propagation channel constitutes a MIMO system. Multiple antenna technologies and in particular MIMO signalling are envisaged for a number of standards such as the next generation of Wireless Local Area Network (WLAN) technology known as 802.1 ln and the development of the Worldwide Interoperability for Microwave Access (WiMAX) project, such as the 802.16e. For the efficient design, performance evaluation and deployment of such multiple antenna (space-time) systems, it becomes increasingly important to understand the characteristics of the spatial radio channel. This criterion has led to the development of new sounding systems, which can measure both spatial and temporal channel information. In this thesis, a novel semi-sequential wideband MIMO sounder is presented, which is suitable for high-resolution radio channel measurements. The sounder produces a frequency modulated continuous wave (FMCW) or chirp signal with variable bandwidth, centre frequency and waveform repetition rate. It has programmable bandwidth up to 300 MHz and waveform repetition rates up to 300 Hz, and could be used to measure conventional high- resolution delay/Doppler information as well as spatial channel information such as Direction of Arrival (DOA) and Direction of Departure (DOD). Notably the knowledge of the angular information at the link ends could be used to properly design and develop systems such as smart antennas. This thesis examines the theory of multiple antenna propagation channels, the sounding architecture required for the measurement of such spatial channel information and the signal processing which is used to quantify and analyse such measurement data. Over 700 measurement files were collected corresponding to over 175,000 impulse responses with different sounder and antenna array configurations. These included measurements in the Universal Mobile Telecommunication Systems Frequency Division Duplex (UMTS-FDD) uplink band, the 2.25 GHz and 5.8 GHz bands allocated for studio broadcast MIMO video links, and the 2.4 GHz and 5.8 GHz ISM bands allocated for Wireless Local Area Network (WLAN) activity as well as for a wide range of future systems defined in the WiMAX project. The measurements were collected predominantly for indoor and some outdoor multiple antenna channels using sounding signals with 60 MHz, 96 MHz and 240 MHz bandwidth. A wide range of different MIMO antenna array configurations are examined in this thesis with varying space, time and frequency resolutions. Measurements can be generally subdivided into three main categories, namely measurements at different locations in the environment (static), measurements while moving at regular intervals step by step (spatial), and measurements while the receiver (or transmitter) is on the move (dynamic). High-scattering as well as time-varying MIMO channels are examined for different antenna array structures