We describe a set of fundamental contributions to the design, analysis and implementation of distributed MIMO techniques in wireless networks. The main idea behind distributed MIMO is to organize groups of wireless transmitters and receivers into distributed antenna arrays to cooperatively achieve beamforming and spatial multiplexing gains in ad-hoc wireless networks. This technique promises orders-of-magnitude increases in wireless data rates, however it presupposes very stringent timing, carrier frequency and phase synchronization of the RF signals between the cooperating nodes in the array. Specifically in this dissertation, we consider a sub-class of distributed MIMO systems called distributed MISO systems. In other words, we focus on distributed transmit arrays, wherein a group of N transmitters organize themselves into a virtual antenna array (VAA) to talk to a single-antenna receiver. While distributed MIMO involves virtual arrays on both transmit and receive ends, transmit arrays require real-time coordination, and therefore present unique challenges as compared to receive arrays. We explore two specific MISO techniques: i) distributed beamforming and ii) distributed nullforming in this work. Beamforming involves focusing transmitted energy selectively in the direction of an intended receiver, and nullforming involves forming a "null" i.e. having the transmissions of the different array nodes cancel each other completely at a desired location. Beamforming has the potential of substantially increasing the energy efficiency of wireless communications, while nullforming allows multiple nodes to communicate simultaneously over the same frequency band by carefully canceling the resulting interference. Beamforming and nullforming can also be thought of as basic building blocks for more sophisticated MIMO techniques. In this work, we present a set of frequency synchronization and phase control algorithms to establish and maintain a VAA for distributed beamforming and nullforming. For frequency-locking, we propose a novel distributed consensus-based algorithm. For a VAA with two nodes, we show that our algorithm achieves frequency lock globally and exponentially with a residual phase disparity that is either 0 or pi. This is in contrast to PLL-like algorithms that only achieve lock locally. Next, we describe in detail the key ideas behind an implementation of distributed beamforming on a GNU-radio/USRP based software-defined radio (SDR) platform. We introduce a novel DSP-centric Master-Slave (MS) architecture that enables the use of low-rate DSP algorithms for synchronization of high frequency RF signals. We describe the evolution of our implementation from initially using analog signaling with Costas loops/PLLs for frequency offset estimation and compensation, to a digital signaling scheme that uses extended Kalman filters (EKF) to track and compensate for frequency offsets. The EKF-based frequency locking scheme is well-suited for packet wireless networks, e.g., WiFi, ZigBee. We next consider phase control algorithms for forming beams and nulls with a VAA. In our experimental implementation, we have used several variants of classical 1-bit feedback control algorithm during different stages of our work. 1-bit feedback algorithm is an iterative gradient-ascent algorithm which causes the VAA nodes' signals to add constructively at a designated receiver. We present results to demonstrate the gains in the RSS at the receiver due to beamforming in the real-time settings. We also describe a distributed gradient-descent based algorithm that causes VAA nodes to achieve a null at a designated null target. We provide detailed convergence analysis for the proposed null-steering algorithm. This analysis shows that the algorithm always achieves practical null at null-target; moreover, all the spurious stationary points are locally unstable. Finally, we conclude by providing suggestions for future work.

Distributed MIMO (DMIMO) communications and specifically the idea of distributed transmit beamforming involves multiple transmitters coordinating among themselves to form a virtual antenna array and steer a beam to one or more receivers. Recent works have successfully demonstrated this concept of beamforming with narrowband, frequency-flat wireless channels. We consider the generalization of this concept to wideband, frequency selective channels and propose two Figures of Merit (FOMs), namely, communication capacity and received power to measure the performance of beamforming. We formulate the precoder design that maximizes the two FOMs as optimization problems and derive general properties of the optimal precoders. The two metrics are equivalent with frequency-flat channels, whereas, they result in vastly different optimal criteria with wideband channels. The capacity maximizing solution also differs from classical water-filling due to the per-transmitter power constraints of the distributed beamforming setting, whereas, the power maximizing solution involves the array nodes concentrating their power in a small, finite set of frequencies resulting in an overall received signal consisting of a small number of sinusoidal tones. We have not been able to derive closed-form solutions for the optimal precoders, but we provide fixed point algorithms that efficiently computes these precoders numerically. We show using simulations that solution to both these maximization problems can yield substantially better performance as compared to simple alternatives such as equal power allocation. The fixed point algorithms also suggest a distributed implementation where each node can compute these precoders on their own iteratively using feedback from a cooperating receiver. We also establish the relationship between various precoders. The idea of maximizing received power suggests a natural application of wireless power transfer(WPT). However, the large-scale propagation losses associated with radiative fields makes antennas unattractive for WPT systems. Motivated by this observation, we also consider the problem of optimizing the efficiency of WPT to a receiver coil from multiple transmitters using near-field coupling. This idea of WPT using near-field coupling is not new; however, the difficulty of constructing tractable and realistic circuit models has limited the ability to accurately predicting and optimizing the performance of these systems. We present a new simple theoretical model and take the more abstract approach of modeling the WPT system as a linear circuit whose input-output relationship is expressed in terms of a small number of unknown parameters. We present a simple derivation of the optimal voltage excitations to be applied at the transmitters to maximize efficiency, and also some general properties of the optimal solution. Obviously, the optimal solution is a function of unknown parameters, and we describe a procedure to estimate these parameters using a set of direct measurements. We also present a series of experimental results, first, with two transmitter coils and a receiver coil in a variety of configurations and then with four transmitter coils and two receiver coils to illustrate our approach and the efficiency increase achieved by using the calculated optimal solution from our model.

A Distributed Multi-Input Multi-Output (DMIMO) system consists of many transceivers coordinating themselves into a "virtual antenna array" in order to emulate MIMO capabilities. In recent years, the field of research investigating DMIMO Communications has grown substantially. DMIMO systems offer all of the same benefits of standard MIMO systems on a larger scale because arrays are not limited by the physical constraint of placing many antennas on a single transceiver. This additional benefit does come at a cost, however. Since nodes are distributed and run from independent clock signals and with unknown geometry, each one must its own obtain channel state information (CSI) to the target nodes. In existing DMIMO architectures, array nodes depend on feedback from target nodes to properly synchronize. This means that target nodes must be cooperative and are responsible for the overhead calculating and transmitting CSI feedback to each node in the array. Within this work, we develop a set of techniques for Retrodirective Distributed Antenna Arrays. Retrodirective arrays have traditionally been used to direct a beam towards a target node, but the work in this thesis seeks to develop a more generalized definition of retrodirectivity. By our definition, a retrodirective array is one that acquires CSI to one or more intended targets simply by listening to the incoming transmissions of those targets; the array may subsequently use this information to do any number of typical MIMO tasks (i.e., beamforming, nullforming, spatial multiplexing, etc.). We explore two primary techniques: i) distributed beamforming and ii) distributed nullforming. Beamforming involves focusing transmitted power towards a specific target node and nullforming involves directing transmissions of array nodes to cancel one another at a specific target node. We focus on these techniques because they can be thought of as basic building blocks for more sophisticated DMIMO techniques. We first develop the theory for retrodirective arrays. Then, we present an architecture for the implementation of this theory. Specifically, we focus on the pre-synchronization of the array, which involves use of a master/slave architecture and a timeslotted message exchange among the array nodes. Finally, developing algorithms to make these arrays both robust and scalable is the focus of this thesis.

In many engineering applications, including radar, sonar, communications and seismology, the direction of impinging signal wavefronts can be used to discriminate between competing sources. Often these source signals cover a wide bandwidth and conventional narrowband beamforming techniques are ineffective, since spatial resolution varies significantly across the band. In this thesis we consider the problem of beamforming for broadband signals, primarily when the spatial response remains constant as a function of frequency. This is called a frequency invariant beamformer (FIB).¶ Rather than applying the numerical technique of multi-parameter optimisation to solve for the beamformer parameters, we attempt to address the fundamental nature of the FIB problem. The general philosophy is to use a theoretical continuous sensor to derive relationships between a desired FI beampattern and the required signal processing structure. Beamforming using an array of discrete sensors can then be formulated as an approximation problem. This approach reveals a natural structure to the FIB which is otherwise buried in a numerical optimisation procedure.¶ Measured results from a microphone array are presented to verify that the simple FIB structure can be successfully implemented. We then consider imposing broadband pattern nulls in the FI beampattern, and show that (i) it is possible to impose an exact null which is present over all frequencies, and (ii) it is possible to calculate a priori how many constraints are required to achieve a null of a given depth in a FIB. We also show that the FIB can be applied to the problem of broadband direction of arrival (DOA) estimation and provides computational advantages over other broadband DOA estimators.¶ Through the theoretical continuous sensor approach, we show that the FIB theory can be generalised to the problem of designing a general broadband beamformer (GBB) which realizes a broadband angle-versus-frequency beampattern specification. Coupled with a technique for radial beampattern transformation, the GBB can be applied to a wide class of problems covering both nearfield beamforming (in which the shape of the impinging wavefront must be considered and farfield beamforming (which is simplified by the assumption of planar wavefronts) for a broadband beampattern specified over both angle and frequency.

This thesis investigates the design and the analysis of acoustic signal processing algorithms in reverberant rooms. Reverberation poses a major challenge to acoustic signal processing problems. It degrades speech intelligibility and causes many acoustic algorithms that process sound to perform poorly. Current solutions to the reverberation problem frequently only work in lightly reverberant environments. There is need to improve the reverberant performance of acoustic algorithms.¶ The approach of this thesis is to explore how the intrinsic properties of reverberation can be exploited to improve acoustic signal processing algorithms. A general approach to soundfield modelling using statistical room acoustics is applied to analyze the reverberant performance of several acoustic algorithms. A model of the underlying structure of reverberation is incorporated to create a new method of soundfield reproduction.¶ Several outcomes resulting from this approach are: (i) a study of how more sound capture with directional microphones and beamformers can improve the robustness of acoustic equalization, (ii) an assessment of the extent to which source tracking can improve accuracy of source localization, (iii) a new method of soundfield reproduction for reverberant rooms, based upon a parametrization of the acoustic transfer function and (iv) a study of beamforming to directional sources, specifically exploiting the directionality of human speech.¶ The approach to soundfield modelling has permitted a study of algorithm performance on important parameters of the room acoustics and the algorithm design. The performance of acoustic equalization and source tracking have been found to depend not only on the levels of reverberation but also on the correlation of pressure between points in reverberant soundfields. This correlation can be increased by sound capture with directional capture devices. Work on soundfield reproduction has shown that, though reverberation significantly degrades the performance of conventional techniques, by accounting for the reverberation it is possible to design reproduction methods that function well in reverberant environments.

This thesis describes a blind beamforming technique for GPS receivers. It improves the performance of a GPS receiver by mitigating interference and enhancing GPS signals separately and has a three-stage structure. The technique is based on a linear antenna array and integrates the eigendecomposition based subspace and multiple independent beamforming techniques. A signal model is carefully constructed. Particular emphasis is placed upon the projection matrix derived from the subspace technique. The effect of interference and phase error on this technique is discussed. This technique is tested and compared to null steering and MMSE technique using simulated data for a number of interference environments. Furthermore, the proposed technique is applied to real data and shows several advantages over simple null steering. / Thesis (M.Eng.Sc.) - University of Adelaide, School of Electrical and Electronic Engineering, 2008

<p>Adaptive antenna arrays have a great importance in reduction of the effect of interference and increase the capacity for the mobile satellite communication. Interference and multipath fading remain a main problem for reception of signals. These two problems obviously affect the overall capacity.  Adaptive antenna arrays in the handheld mobile apparatus will be the solution for the above two problems.</p><p> </p><p>Satellite mobile communication is one of the growing fields in the communication area where terrestrial infrastructures are unable or ineffective to supply. Maritime, aeronautical and land mobile are some of the applications. During natural disasters where ground services are stopped, mobile satellite communications has great importance. Following the hurricane season, the Asian Tsunami and the devastating Haiti earthquake, mobile satellite communications had played a great role to fill the communication gaps.  The satellites can be tracked automatically by adaptive antenna array when it moves in its orbital plane.</p><p> </p><p>In this thesis the methods that how the adaptive antenna array combats interferers is presented and simulated using MATLAB software. The performance of the adaptive antenna array is evaluated by simulating the directivity pattern of the antenna and Mean Square Error (MSE) graph for different scenario like Signal to Interference Noise ratio (SINR), number of iterations, antenna array elements and convergence factor (μ), assuming the signals are coming from different Direction of Arrival (DOA).</p><p> </p><p> </p>

This thesis studies a two-way relay network (TWRN), which consists of two single antenna source nodes and a multi-antenna relay node. The source nodes exchange information via the assistance of the relay node in the middle. The relay scheme in this TWRN is amplify-and-forward (AF) based analog network coding (ANC). A robust beamforming matrix optimization algorithm is presented here with the objective to minimize the transmit power at the relay node under given signal to interference and noise ratio (SINR) requirements of source nodes. This problem is first formulated as a non-convex optimization problem, and it is next relaxed to a semi-definite programming (SDP) problem by utilizing the S-procedure and rank-one relaxation. This robust beamforming optimization algorithm is further validated in a MATLAB-based orthogonal frequency-division multiplexing (OFDM) MIMO two-way relay simulation system. To better investigate the performance of this beamforming algorithm in practical systems, synchronization issues such as standard timing offset (STO) and carrier frequency offset (CFO) are considered in simulation. The transmission channel is modeled as a frequency selective fading channel, and the source nodes utilize training symbols to perform minimum mean-square error (MMSE) channel estimation. BER curves under perfect and imperfect synchronization are presented to show the performance of TWRN with ANC. It is shown that the outage probability of robust beamforming algorithm is tightly related to the SINR requirements at the source nodes, and the outage probability increases significantly when the SINR requirements are high.

Wireless communication links with multiple antennas at both the transmitter and the receiver sides, so-called multiple-input-multiple-output (MIMO)systems, are attracting much interest since they can significantly increase the capacity of band-limited wireless channels to meet the requirements of the future high data rate wireless communications. The treatment of channel state information (CSI) is critical in the design of MIMO systems. Accurate CSI at the transmitter is often not possible or may require high feedback rates, especially in multi-user scenarios. Herein, we consider the robust design of linear transceivers with imperfect CSI either at the transmitter or at both sides of the link. The framework considers the design problem where the imperfect CSI consists of a channel mean and an channel covariance matrix or, equivalently, a channel estimate and an estimation error covariance matrix. For single-user systems, the proposed robust transceiver designs are based on a general cost function of the average mean square errors. Under different CSI conditions, our robust designs exhibit a similar structure to the transceiver designs for perfect CSI, but with a different equivalent channel and/or noise covariance matrix. Utilizing majorization theory, the robust linear transceiver design can be readily solved by convex optimization approaches in practice. For multi-user systems, we consider both the communication link from the users to the access point (up-link) as well as the reverse link from the access point to the users (down-link). For the up-link channel, it is possible to optimally design robust linear transceivers minimizing the average sum mean square errors of all the data streams for the users. Our robust linear transceivers are designed either by reformulating the optimization problem as a semidefinite program or by extending the design of a single-user system in an iterative manner. Under certain channel conditions, we show that the up-link design problem can even be solved partly in a distributed fashion. For the down-link channel, a system with one receive antenna per user is considered. A robust system design is obtained by reducing the feedback load from all users to allow only a few selected users to feed back accurate CSI to the access point. We study the properties of four typical user selection algorithms in conjunction with beamforming that guarantee certain signal-to-interference-plus-noise ratio (SINR) requirements under transmit power minimization. Specifically, we show that norm-based user selection is asymptotically optimal in the number of transmitter antennas and close-to-optimal in the number of users. Rooted in the practical significance of this result, a simpler down-link system design with reduced feedback requirements is proposed. / QC 20100922

The concept of cooperation in communications has drawn a lot of research attention in recent years due to its potential to improve the efficiency of wireless networks. This new form of communications allows some users to act as relays and assist the transmission of other users' information signals. The aim of this thesis is to apply optimization techniques in the design of multi-relay wireless networks employing cooperative communications. In general, the thesis is organized into two parts: ``Distributed space-time coding' (DSTC) and ``Distributed beamforming', which cover two main approaches in cooperative communications over multi-relay networks. <br><br> In Part I of the thesis, various aspects of distributed implementation of space-time coding in a wireless relay network are treated. First, the thesis proposes a new fully-diverse distributed code which allows noncoherent reception at the destination. Second, the problem of coordinating the power allocation (PA) between source and relays to achieve the optimal performance of DSTC is studied and a novel PA scheme is developed. It is shown that the proposed PA scheme can obtain the maximum diversity order of DSTC and significantly outperform other suboptimal PA schemes. Third, the thesis presents the optimal PA scheme to minimize the mean-square error (MSE) in channel estimation during training phase of DSTC. The effect of imperfect channel estimation to the performance of DSTC is also thoroughly studied. <br><br> In Part II of the thesis, optimal distributed beamforming designs are developed for a wireless multiuser multi-relay network. Two design criteria for the optimal distributed beamforming at the relays are considered: (i) minimizing the total relay power subject to a guaranteed Quality of Service (QoS) measured in terms of signal-to-noise-ratio (SNR) at the destinations, and (ii) jointly maximizing the SNR margin at the destinations subject to power constraints at the relays. Based on convex optimization techniques, it is shown that these problems can be formulated and solved via second-order conic programming (SOCP). In addition, this part also proposes simple and fast iterative algorithms to directly solve these optimization problems.