On the sparse beamformer design

In designing acoustic broadband beamformers, the complexity can grow significantly when the number of microphones and the filter length increase. It is advantageous if many of the filter coefficients are zeroes so that the implementation can be executed with less computation. Moreover, the size of the array can also be pruned to reduce complexity. These problems are addressed in this paper. A suitable optimization model is proposed. Both array pruning and filter thinning can be solved together as a two-stage optimization problem to yield the final sparse designs. Numerical results show that the complexity of the designed beamformers can be reduced significantly with minimal effect on performance

On the indoor beamformer design with reverberation

Beamforming remains to be an important technique for signal enhancement. For applications in open space, the transfer function describing waves propagation has an explicit expression, which can be employed for beamformer design. However, the function becomes very complex in an indoor environment due to the effects of reverberation. In this paper, this problem is discussed. A method based on the image source method (ISM) is applied to model the room impulse responses (RIRs), which will act as the transfer function between source and sensor. The indoor beamformer design problem is formulated as a minimax optimization problem. We propose and study several optimization models based on the -norm to design the beamformer. We found that it is advantageous to separate early and late reverberations in the design process and better designs can be achieved. Several numerical experiments are presented using both simulated data and real recordings to evaluate the proposed methods

A New Hybrid Descent Method with Application to the Optimal Design of Finite Precision FIR Filters

In this paper, the problem of the optimal design of discrete coefficient FIR filters is considered. A novelhybrid descent method, consisting of a simulated annealing algorithm and a gradient-based method, isproposed. The simulated annealing algorithm operates on the space of orthogonal matrices and is used tolocate descent points for previously converged local minima. The gradient-based method is derived fromconverting the discrete problem to a continuous problem via the Stiefel manifold, where convergence canbe guaranteed. To demonstrate the effectiveness of the proposed hybrid descent method, several numericalexamples show that better discrete filter designs can be sought via this hybrid descent method

A survey on hybrid beamforming techniques in 5G : architecture and system model perspectives

The increasing wireless data traffic demands have driven the need to explore suitable spectrum regions for meeting the projected requirements. In the light of this, millimeter wave (mmWave) communication has received considerable attention from the research community. Typically, in fifth generation (5G) wireless networks, mmWave massive multiple-input multiple-output (MIMO) communications is realized by the hybrid transceivers which combine high dimensional analog phase shifters and power amplifiers with lower-dimensional digital signal processing units. This hybrid beamforming design reduces the cost and power consumption which is aligned with an energy-efficient design vision of 5G. In this paper, we track the progress in hybrid beamforming for massive MIMO communications in the context of system models of the hybrid transceivers' structures, the digital and analog beamforming matrices with the possible antenna configuration scenarios and the hybrid beamforming in heterogeneous wireless networks. We extend the scope of the discussion by including resource management issues in hybrid beamforming. We explore the suitability of hybrid beamforming methods, both, existing and proposed till first quarter of 2017, and identify the exciting future challenges in this domain

Signal Subspace Processing in the Beam Space of a True Time Delay Beamformer Bank

A number of techniques for Radio Frequency (RF) source location for wide bandwidth signals have been described that utilize coherent signal subspace processing, but often suffer from limitations such as the requirement for preliminary source location estimation, the need to apply the technique iteratively, computational expense or others. This dissertation examines a method that performs subspace processing of the data from a bank of true time delay beamformers. The spatial diversity of the beamformer bank alleviates the need for a preliminary estimate while simultaneously reducing the dimensionality of subsequent signal subspace processing resulting in computational efficiency. The pointing direction of the true time delay beams is independent of frequency, which results in a mapping from element space to beam space that is wide bandwidth in nature. This dissertation reviews previous methods, introduces the present method, presents simulation results that demonstrate the assertions, discusses an analysis of performance in relation to the Cramer-Rao Lower Bound (CRLB) with various levels of noise in the system, and discusses computational efficiency. One limitation of the method is that in practice it may be appropriate for systems that can tolerate a limited field of view. The application of Electronic Intelligence is one such application. This application is discussed as one that is appropriate for a method exhibiting high resolution of very wide bandwidth closely spaced sources and often does not require a wide field of view. In relation to system applications, this dissertation also discusses practical employment of the novel method in terms of antenna elements, arrays, platforms, engagement geometries, and other parameters. The true time delay beam space method is shown through modeling and simulation to be capable of resolving closely spaced very wideband sources over a relevant field of view in a single algorithmic pass, requiring no course preliminary estimation, and exhibiting low computational expense superior to many previous wideband coherent integration techniques

Signal Subspace Processing in the Beam Space of a True Time Delay Beamformer Bank

A number of techniques for Radio Frequency (RF) source location for wide bandwidth signals have been described that utilize coherent signal subspace processing, but often suffer from limitations such as the requirement for preliminary source location estimation, the need to apply the technique iteratively, computational expense or others. This dissertation examines a method that performs subspace processing of the data from a bank of true time delay beamformers. The spatial diversity of the beamformer bank alleviates the need for a preliminary estimate while simultaneously reducing the dimensionality of subsequent signal subspace processing resulting in computational efficiency. The pointing direction of the true time delay beams is independent of frequency, which results in a mapping from element space to beam space that is wide bandwidth in nature. This dissertation reviews previous methods, introduces the present method, presents simulation results that demonstrate the assertions, discusses an analysis of performance in relation to the Cramer-Rao Lower Bound (CRLB) with various levels of noise in the system, and discusses computational efficiency. One limitation of the method is that in practice it may be appropriate for systems that can tolerate a limited field of view. The application of Electronic Intelligence is one such application. This application is discussed as one that is appropriate for a method exhibiting high resolution of very wide bandwidth closely spaced sources and often does not require a wide field of view. In relation to system applications, this dissertation also discusses practical employment of the novel method in terms of antenna elements, arrays, platforms, engagement geometries, and other parameters. The true time delay beam space method is shown through modeling and simulation to be capable of resolving closely spaced very wideband sources over a relevant field of view in a single algorithmic pass, requiring no course preliminary estimation, and exhibiting low computational expense superior to many previous wideband coherent integration techniques

Rate-Optimum Beamforming Transmission in MIMO Rician Fading Channels

Η παρούσα διδακτορική διατριβή επικεντρώνεται στη δυνατότητα που έχουν τα συστήματα ΜΙΜΟ να επιτυγχάνουν υψηλότερη χωρητικότητα από ένα συμβατικά συστήματα SISO. Όμως η χωρητικότητα που επιτυγχάνουν τα συστήματα MIMO σχετίζεται με τη γνώση/πληροφορία την οποία έχουν ο πομπός και ο δέκτης για το κανάλι. Θεωρώντας εργοδικό κανάλι με μιγαδική κανονική κατανομή, στο οποίο ο δέκτης έχει πλήρη γνώση του καναλιού και ο πομπός γνωρίζει μόνο την κατανομή αυτού, επιδιώκεται η μεγιστοποίηση της μέσης αμοιβαία πληροφορίας. Στην περίπτωση εκπομπής beamforming, τη μέγιστη μέση αμοιβαία πληροφορία μεταξύ πομπού-δέκτη επιτυγχάνει ο «βέλτιστος beamformer» και η επιτυγχανόμενη μέγιστη τιμή αναφέρεται ως «εργοδική beamforming χωρητικότητα». Στα πλαίσια της παρούσας διατριβής μελετάται ο τρόπος υπολογισμού του «βέλτιστου beamformer» για την περίπτωση χωρικώς συσχετισμένων καναλιών ΜΙΜΟ με κατανομή Rice και αποδεικνύεται ότι, ο υπόψη υπολογισμός προκύπτει από την επίλυση ενός απλού, μονοδιάστατου (1-Δ) προβλήματος βελτιστοποίησης. Η ανωτέρω απόδειξη βασίζεται σε γεωμετρικές ιδιότητες, κατάλληλους μετασχηματισμούς βάσης και στις συνθήκες Karush-Kuhn-Tucker. Στη συνέχεια υλοποιήθηκε πληθώρα προσομοιώσεων η οποία ανέδειξε την χαμηλή πολυπλοκότητα της προτεινόμενης μονοδιάστατης μεθόδου, καθώς και την υψηλή απόδοση του «βέλτιστου beamformer» ως πολιτική εκπομπής. Επιπρόσθετα, εφαρμόστηκε το μοντέλο προσομοίωσης καναλιών ΜΙΜΟ της 3GPP, με σκοπό την περαιτέρω μελέτη της απόδοσης του «βέλτιστου beamformer» σε πρακτικά λειτουργικά σενάρια. Τα αποτελέσματα επιβεβαίωσαν εκ νέου την υψηλή απόδοση του «βέλτιστου beamformer» και τη σημασία της προτεινόμενης μεθόδου υπολογισμού του.In this doctoral thesis, the focus is on the capability of MIMO systems to achieve much higher capacity than SISO systems. However, the capacity achieved by MIMO systems is closely related to the “channel knowledge” model which is assumed at both ends of the MIMO link. Considering the case of MIMO complex Gaussian ergodic channels, where the receiver has perfect Channel State Information (CSI) whereas the transmitter has Channel Distribution Information (CDIT), we aim at the maximization of the average mutual information between them. For the case of beamforming transmission, the maximum average mutual information is achieved by the “optimum beamformer” and is referred to as “ergodic beamforming capacity”. In this work, the calculation of the optimum beamformer is studied for spatially correlated MIMO Rician fading channels and it is proven that this calculation is achieved by solving a simple 1-D optimization problem. The proof was based on geometrical properties, basis transformations and the Karush-Kuhn-Tucker (KKT) conditions. Extended simulations were performed which demonstrated the low computational complexity of the proposed method as well as the high performance of the optimum beamformer. Additionally the 3GPP MIMO channel model was employed in order to study further the performance of the optimum beamformer in practical operational scenarios. The results confirmed the high performance of the optimum beamformer and the significance of the proposed solutions

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