Antenna array calibration in wireless communications

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Signal Processing in Arrayed MIMO Systems

Multiple-Input Multiple-Output (MIMO) systems, using antenna arrays at both receiver and transmitter, have shown great potential to provide high bandwidth utilization efficiency. Unlike other reported research on MIMO systems which often assumes independent antennas, in this thesis an arrayed MIMO system framework is proposed, which provides a richer description of the channel charac- teristics and additional degrees of freedom in designing communication systems. Firstly, the spatial correlated MIMO system is studied as an array-to-array system with each array (Tx or Rx) having predefined constrained aperture. The MIMO system is completely characterized by its transmit and receive array man- ifolds and a new spatial correlation model other than Kronecker-based model is proposed. As this model is based on array manifolds, it enables the study of the effect of array geometry on the capacity of correlated MIMO channels. Secondly, to generalize the proposed arrayed MIMO model to a frequency selective fading scenario, the framework of uplink MIMO DS-CDMA (Direct- Sequence Code Division Multiple Access) systems is developed. DOD estimation is developed based on transmit beamrotation. A subspace-based joint DOA/TOA estimation scheme as well as various spatial temporal reception algorithms is also proposed. Finally, the downlink MIMO-CDMA systems in multiple-access multipath fading channels are investigated. Linear precoder and decoder optimization problems are studied under different criterions. Optimization approaches with different power allocation schemes are investigated. Sub-optimization approaches with close-form solution and thus less computation complexity are also proposed

Channel estimation method with improved performance for the UMTS-TDD mode

Channel estimation is an essential building block for UTRA-TDD high performance receivers. Once the performance of the channel estimator algorithm proposed by 3GPP is highly dependent on the time spreading between consecutive multi-path components, a Successive Multi-path channel Estimation Technique (SMET) that improves the time resolution is proposed in this paper. A SMET based maximum likelihood approach for vectorial channel estimation, to include the estimation of the direction-of-arrival, is also proposed. This algorithm solves efficiently the complex problem of DOA estimation of multiple users in a multi path propagation environment even when the number of required DOA's exceeds the number of antenna array elements. Another property of the proposed algorithm is its ability to resolve signals from different users arriving from the same direction. This is due to processing in both time and space dimensions. The performance of these algorithms is assessed by resorting to simulations in multi-path environments using the UMTS-TDD specifications, and also by comparing the rms estimation errors against the Crámer-Rao Bound. The effect of imperfect channel estimation on the performance of RAKE and Hard-Decision Parallel Interference Canceller receivers is also analysed. The results show that a good performance can be achieved with SMET, from low to high values of Eb/n0

Cyclic Prefix-Free MC-CDMA Arrayed MIMO Communication Systems

The objective of this thesis is to investigate MC-CDMA MIMO systems where the antenna array geometry is taken into consideration. In most MC-CDMA systems, cyclic pre xes, which reduce the spectral e¢ ciency, are used. In order to improve the spectral efficiency, this research study is focused on cyclic pre x- free MC-CDMA MIMO architectures. Initially, space-time wireless channel models are developed by considering the spatio-temporal mechanisms of the radio channel, such as multipath propaga- tion. The spatio-temporal channel models are based on the concept of the array manifold vector, which enables the parametric modelling of the channel. The array manifold vector is extended to the multi-carrier space-time array (MC-STAR) manifold matrix which enables the use of spatio-temporal signal processing techniques. Based on the modelling, a new cyclic pre x-free MC- CDMA arrayed MIMO communication system is proposed and its performance is compared with a representative existing system. Furthermore, a MUSIC-type algorithm is then developed for the estimation of the channel parameters of the received signal. This proposed cyclic pre x-free MC-CDMA arrayed MIMO system is then extended to consider the effects of spatial diffusion in the wireless channel. Spatial diffusion is an important channel impairment which is often ignored and the failure to consider such effects leads to less than satisfactory performance. A subspace-based approach is proposed for the estimation of the channel parameters and spatial spread and reception of the desired signal. Finally, the problem of joint optimization of the transmit and receive beam- forming weights in the downlink of a cyclic pre x-free MC-CDMA arrayed MIMO communication system is investigated. A subcarrier-cooperative approach is used for the transmit beamforming so that there is greater flexibility in the allocation of channel symbols. The resulting optimization problem, with a per-antenna transmit power constraint, is solved by the Lagrange multiplier method and an iterative algorithm is proposed

Space time transceiver design over multipath fading channels

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D2D communications in 5G mobile cellular networks : we propose and validate a novel approach to mobility management

University of Technology Sydney. Faculty of Engineering and Information Technology.Fifth Generation (5G) stands for future fitness combined with flexible technical solutions that combine with the latest wireless technology. 5G is expected to multiply a thousand times (1000x) in data speed with 20.4 billion devices (IoT) connected to the network by 2020. This literally means everything connecting to everything. From the network point of view, lower latency along with high flexibility is not limited just to 5G. It is already being implemented in real networks. The number of wireless devices connected to networks has increased remarkably over the last couple of decades. Ubiquitous voice and data connections are the fundamental requirements for the next generation of wireless technology. Device-to-Device communication is widely known as D2D. It is a new paradigm for cellular communication. It was initially proposed to boost network performance. It is considered to be an integral part of the next generation (5G) of telecommunications networks. It takes place when two devices communicate directly without significant help from the base station. In a cellular network, Device-to-Device communication has been viewed as a promising technology overcoming many existing problems. These include capacity, quality and scarce spectrum resources. However, this comes at the price of increased interference and complex mobility issues, even though it was proposed as a new paradigm to enhance network performance. Nevertheless, it is still a challenge to manage devices that are moving. Cellular devices without well-managed mobility are hardly acceptable. Considering in-band underlay D2D communication, a well-managed mobility system in cellular communication should have lower latency, lower power consumption and higher data rates. In this dissertation, we review existing mobility management systems for LTE-Advanced technology and propose an algorithm to be used over the current system so that lower signalling overheads and less delay, along with uninterrupted D2D communication, are guaranteed. We model and simulate our algorithm, comparing the results with mathematical models based on Markov theory. As in other similar communication systems, mobility management for D2D communication is yet to be explored fully. There are few research papers published so far. What we can say is that the intention of such systems in cellular networks are to enable lower latency, lower power consumption, less complexity and, last but not least, uninterrupted data connections. Our simulation results validate our proposed model and highlight D2D communication and its mobility issues. An essential element of our proposal is to estimate the user’s location. We can say that a mobility management system for D2D communication is hardly workable if the location of the users is not realisable. This dissertation also shows some latest techniques for estimating the direction of arrival (DOA) with mathematical models and simulation results. Smart antenna systems are proposed. It is possible to determine the location of a user by considering the uplink transmission system. Estimating the channel and actual path delay is also an important task, which might be done by using 1D uniform linear array (ULA) or 2D Uniform Rectangular (URA) array antenna systems. In this chapter, 1D ULA is described utilising some well-known techniques. The channel characteristics largely determine the performance of an end-to-end communication system. It determines the signal transformation while propagating through the channel between receivers and transmitters. Accurate channel information is crucial for both the transmitter and receiver ends to perform at their best. The ultimate focus of this part is to estimate the channel based on 2D parameter estimation. Uniform Rectangular Array (URA) is used to perform the 2D parameter estimation. It is possible to estimate azimuth and elevation of a source by using the URA model. The problem of mobility in this context has been investigated in few papers, with no reliable solutions as yet. We propose a unique algorithm for mobility management for D2D communications. In this dissertation, we highlight and explain the mobility model mathematically and analytically, along with the simulation of the Markovian model. A Markov model is essentially a simplified approach to describing a system that occupies a discrete state at any point in time. We also make a bridge between our mobility algorithm and a Markovian model

Array communications in wireless sensor networks

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Estimating the time and angle of arrivals in mobile communications

Dans ce projet, nous présentons une méthode nouvelle et précise d’estimation de la direction et des délais d’arrivée dans un environnement à trajets multiples, à des fins d’estimation de canal. Récemment, les méthodes de super-résolution ont été largement utilisées pour l’estimation à haute-résolution de la direction d’arrivée (DOA) ou de la différence de temps d’arrivée (TDOA). L’algorithme proposé dans ce travail est applicable à l’estimation d’un canal espace-temps pour des systèmes de traitement spatio-temporel qui emploient la technologie hybride DOA / TDOA. L’estimateur est basé sur l’algorithme MUSIC classique pour trouver la DOA et en profitant d’un simple corrélateur, il est possible de trouver le retard de chaque arrivée. Il est pertinent d’associer chaque angle à son propre retard pour être capable d’estimer les caractéristiques du canal quand nous ne connaissons pas la séquence transmise par l’émetteur. Pour ce faire, nous proposons une formation de faisceaux (voix) très simple et optimale par l’application du MVDR (Maximum Variance Distortion-less Response). Cette formation de faisceaux maximise le signal desiré par rapport aux autres signaux. Après détermination de l’angle d’arrivée par l’algorithme MUSIC, nous appliquons l’algorithme de formation de faisceaux MVDR pour obtenir le signal qui est reçu par le réseau d’antennes pour une direction. Ce signal est corrélé avec les autres signaux correspondants aux autres directions d’arrivée. Les pics dans les figures ainsi obtenues montrent le décalage temporel de chaque source par rapport à celle obtenue par la formation de faisceaux MVDR. La soustraction du plus petit décalage, correspondant au premier signal reçu à chaque décalage temporel, nous donne le temps d’arrivée de chaque source. Pour être plus précis, nous pouvons choisir la moyenne des vecteurs des délais estimés, chacun étant obtenu à partir d’une angle pour l’algorithme MVDR.In this project, we present a novel and precise way of estimating the direction and delay of arrivals in multipath environment for channel estimation purposes. Recently, super-resolution methods have been widely used for high resolution Direction Of Arrival (DOA) or Time Difference Of Arrival (TDOA) estimation. The proposed algorithm in this work is applicable to space-time channel estimation for space-time processing systems that employ hybrid DOA/TDOA technology. The estimator is based on the conventional MUSIC algorithm to find the DOA and by using a simple correlator it is possible to find the delay of each arrival. It is of interest to associate each angle to its proper delay to be able to estimate the characteristics of the channel when we have no knowledge about the transmitted sequence. To do this, we suggest a very simple and optimal beamforming method by performing Maximum Variance Distortion-less Response (MVDR). This beamforming maximizes the desired signal in the desired direction compare to the other signals that come from other directions. After finding the DOAs by MUSIC algorithm and selecting our desired direction, we obtain the signal from this direction by applying MVDR beamforming. Then, we perform a correlation between this signal and the others incoming signals from other directions. The peaks in the simulation figures illustrate the delay between each source with the obtained signal from MVDR. If we subtract the delay of the first arrival (the smallest delay in time), from the delays indicated in the figures, we can obtain the delay of each arrival. To be more precise, the mean of these estimated TOAs vector follows the exact TOA of each source

Spatiotemporal-MIMO channel estimator and beamformer for 5G

With requirements of spiraling data rates and limited spectrum availability, there is an increased interest in mm-wave beamformer-based communications for 5G. For upcoming cellular networks, the critical point is to exploit the increased number of employable antennas at both Tx and Rx to: 1) combat increased path loss; 2) tackle higher interference due to higher user density; and 3) handle multipath effects in frequency selective channels. Toward this, a multi-beam spatiotemporal superresolution beamforming framework is proposed in this paper as a promising candidate to design beampatterns that mitigate/suppress co-channel interference and deliver massive gain in the desired directions. Initially, channel and signal models suitable for the mm-wave MIMO system are presented using the manifold vectors of both Tx and Rx antenna arrays. Based on these models, a novel subspace-based channel estimator is employed, which estimates delays, directions, velocities, and fading coefficients of the desired signal paths. This information is then exploited by the proposed spatiotemporal beamformer to provide a massive array gain that combats path loss without increasing the number of antenna array elements and to be tolerant to the near-far problem in a high interference environment. The performance of the proposed channel estimator and beamformer is examined using computer simulation studies

A New Combination of RAKE Receiver and Adaptive Antenna Array Beamformer for Multiuser Detection in WCDMA Systems

The aim of this paper is to combine smart antenna beamforming and RAKE receiver in wideband code division multiple access (WCDMA). The proposed method combines spatial diversity as well as temporal diversity to improve the performance and overcome both interferences and multipath fading. This investigation has focused on one of the new proposed blind beamforming algorithms. It is based on constrained constant modulus (CCM) algorithm which is used for deriving a recursive-least-squares (RLS-) type optimization algorithm. We illustrate the comparison of bit error rate (BER) of the proposed receiver with simple correlator and also 1D-RAKE receiver in multiuser detection (MUD) WCDMA. The simulation results show that the proposed 2D-RAKE receiver offers lower BER rather than conventional ones, that is, it is an effective solution for decreasing the effect of interference and increasing the capacity, in a joint state