A Study on MIMO Wireless Communication Channel Performance in Correlated Channels

MIMO wireless communication system is gaining popularity by days due to its versatility and wide applicability. When signal travels through wireless link it gets affected due to the disturbances present in the channel i.e. different sorts of interference and noise. Plus because there may or may not be a Line of sight (LOS) path between transmitter and receiver signal copies leaving the transmitter at the same time reaches the receiver with different delays and attenuation due to multiple reflections and interfere with each other at the receiver. Therefore fading of received signal power is also observed in case of a wireless MIMO link. In case of wireless two most important objectives can be channel estimation and signal detection. The importance of the wireless channel estimation can be attributed to faithful signal detection and transmit beam forming, power allocation etc. when Channel state information (CSI) is communicated to the transmitter via feedback loop in case of uni-directional channel or by simultaneous estimation by the transmitter itself in case of bi-directional channel. This text introduces some aspects of signal detection and mostly different aspects of channel estimation and explains why it is important in context of signal detection, beam forming etc. A brief introduction to antenna arrays and beam forming procedures have been given here. The cause of occurrence of spatial and temporal correlations have been discussed and different ways of modelling the spatial and temporal correlations involved are also briefly introduced in this text. How different link and link-end properties e.g. antenna spacing, angular spread of radiation beam, mean angle of radiation, mutual coupling present between elements of an antenna array etc. affects the channel correlations thereby affecting the performance of the MIMO wireless communication channel. Modelling of antenna mutual coupling and different estimation and compensation techniques are also discussed here

Performances of conformal and planar arrays

Static and dynamic deformations can have a severe impact on the performance of conformal antennas on aircrafts and other vehicles. Therefore it is essential to study the different deformation and vibration mechanisms and their influence on the antenna's radiation pattern. This presentation gives an overview of different approaches concerning electromagnetic modelling of array antennas and investigations on antenna deformations presented in the scope of TG20

Beamforming and time reversal imaging for near-field electromagnetic localisation using planar antenna arrays

University of Technology, Sydney. Faculty of Engineering and Information Technology.The localisation of radiating sources of electromagnetic waves in the near-field of a receiver antenna array are of use in a vast range of applications, such as in microwave imaging, wireless communications, RFID, real time localisation systems and remote sensing etc. Localisation of targets embedded in a background dielectric medium, which is usually the case in Radar, UWB imaging and remote sensing, can be done using the scattered response received at the antennas. In this thesis, we investigate methods for localisation of both near-field radiating as well as scattering sources of electromagnetic waves. For localisation of near-field radiating sources, planar antenna arrays such as concentric circular ring array (CCRA), uniform rectangular array (URA), uniform circular array (UCA) and elliptic array are employed. The thesis employs beamforming and parameter estimation methods for localisation and proposes novel algorithms that are based on standard Capon beamformer (SCB), subspace based superresolution algorithms (MUSIC and ESPRIT) and maximum likelihood (ML) methods. Complex array geometries can suffer from severe mutual coupling and are susceptible to array modelling errors. These errors impair the performance of algorithms that are used for beamforming and parameter estimation for localisation. To overcome the limitations of standard Capon beamformer (SCB), a modified capon beamforming method is proposed to make SCB robust against both array modelling error and mutual coupling effects. The proposed method is applied with planar antenna arrays for localisation of near-field sources. Planar arrays are also used with MUSIC and ESPRIT superreso lution algorithms for performance investigation in a near-field source localisation. Here, to reduce the computational burden of standard MUSIC and ESPRIT algorithms, a novel method to estimate the range using the time-delay is proposed. Lastly, to overcome the performance limitations of superresolution algorithms with planar arrays, the ML estimation is investigated for the localisation of near-field sources using planar arrays. Since ML method cannot automatically detect the number of sources, a novel method is proposed here for detecting the number of sources. Finally, performance comparisons of all the methods under investigation have been presented using computer simulations. In order to localise targets embedded either in homogeneous or in heterogeneous background medium, we employ time reversal (TR) techniques that localise based on the received scattering responses from the embedded targets. We propose a novel beamspace- TR technique that can achieve efficient focusing on targets embedded in both a homogeneous and heterogeneous dielectric background media. It is shown that prior to back propagation, applying beamspace processing to the TR operation in the receiving mode helps achieve a reduced dimensional computation and achieves selective focusing. We have also proposed beamspace-TR-MUSIC algorithm for improving the resolution of standard TR-MUSIC algorithm. Performance of these techniques is investigated for localising the target embedded in a clutter rich dielectric background where the dielectric contrast between the target and the background medium is very low. We also propose to extend the maximum likelihood based TR (TR-ML) to improve the focusing ability and to help to localise dielectric targets embedded in a highly cluttered dielectric medium. To prove the ability of the proposed algorithms, they are applied to the problem of UWB radar imaging for the detection of early stage breast cancer. Computer simulations are used for the investigation of the imaging performance of TR, beamspace-TR, TR-MUSIC, beamspace-TR-MUSIC and TR-ML methods on a two-dimensional electromagnetic heterogeneous dielectric scattering model of the breast

DOA Estimation in Partially Correlated Noise Using Low-Rank/Sparse Matrix Decomposition

We consider the problem of direction-of-arrival (DOA) estimation in unknown partially correlated noise environments where the noise covariance matrix is sparse. A sparse noise covariance matrix is a common model for a sparse array of sensors consisted of several widely separated subarrays. Since interelement spacing among sensors in a subarray is small, the noise in the subarray is in general spatially correlated, while, due to large distances between subarrays, the noise between them is uncorrelated. Consequently, the noise covariance matrix of such an array has a block diagonal structure which is indeed sparse. Moreover, in an ordinary nonsparse array, because of small distance between adjacent sensors, there is noise coupling between neighboring sensors, whereas one can assume that nonadjacent sensors have spatially uncorrelated noise which makes again the array noise covariance matrix sparse. Utilizing some recently available tools in low-rank/sparse matrix decomposition, matrix completion, and sparse representation, we propose a novel method which can resolve possibly correlated or even coherent sources in the aforementioned partly correlated noise. In particular, when the sources are uncorrelated, our approach involves solving a second-order cone programming (SOCP), and if they are correlated or coherent, one needs to solve a computationally harder convex program. We demonstrate the effectiveness of the proposed algorithm by numerical simulations and comparison to the Cramer-Rao bound (CRB).Comment: in IEEE Sensor Array and Multichannel signal processing workshop (SAM), 201

Antenna array calibration in wireless communications

Imperial Users onl

Microwave detection of buried mines using non-contact, synthetic near-field focusing

Existing ground penetrating radars (GPR) are limited in their 3-D resolution. For the detection of buried land-mines, their performance is also seriously restricted by `clutter'. Previous work by the authors has concentrated on removing these limitations by employing multi-static synthetic focusing from a 2-D real aperture. This contribution presents this novel concept, describes the proposed implementation, examines the influence of clutter and of various ground features on the system's performance, and discusses such practicalities as digitisation and time-sharing of a single transmitter and receiver. Experimental results from a variety of scenarios are presented