Design of Linear Precoders for Correlated Sources in MIMO Multiple Access Channels

© 2018 IEEE. This version of the article has been accepted for publication, after peer review. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The Version of Record is available online at: https://doi.org/10.1109/TCOMM.2018.2863362[Abstract]: This paper focuses on distributed linear precoding when users transmit correlated information over a fading multiple-input and multiple-output multiple access channel. The precoders are optimized in order to minimize the sum-mean square error (MSE) between the source and the estimated symbols. When sources are correlated, minimizing the sum-MSE results in a non-convex optimization problem. The precoders for an arbitrary number of users and transmit and receive antennas are thus obtained via a projected steepest-descent algorithm and a low-complexity heuristic approach. For the more restrictive case of two single-antenna users, a closed-form expression for the minimum sum-MSE precoders is derived. Moreover, for the scenario with a single receive antenna and any number of users, a solution is obtained by means of a semi-definite relaxation. Finally, we also consider precoding schemes where the precoders are decomposed into complex scalars and unit norm vectors. Simulation results show a significant improvement when source correlation is exploited at precoding, especially for low signal-to-noise ratios and when the number of receive antennas is lower than the number of transmitting nodes.This work has been funded by Office of Naval Research Global of United States (N62909-15-1-2014), the Xunta de Galicia (ED431C 2016-045, ED341D R2016/012, ED431G/01), the Agencia Estatal de Investigación of Spain (TEC2015-69648-REDC, TEC2016-75067-C4-1-R) and ERDF funds of the EU (AEI/FEDER, UE).United States. Office of Naval Research Global of United States; N62909-15-1-2014Xunta de Galicia; ED431C 2016-045Xunta de Galicia; ED341D R2016/012Xunta de Galicia; ED431G/0

Advanced optimization algorithms for sensor arrays and multi-antenna communications

Optimization problems arise frequently in sensor array and multi-channel signal processing applications. Often, optimization needs to be performed subject to a matrix constraint. In particular, unitary matrices play a crucial role in communications and sensor array signal processing. They are involved in almost all modern multi-antenna transceiver techniques, as well as sensor array applications in biomedicine, machine learning and vision, astronomy and radars. In this thesis, algorithms for optimization under unitary matrix constraint stemming from Riemannian geometry are developed. Steepest descent (SD) and conjugate gradient (CG) algorithms operating on the Lie group of unitary matrices are derived. They have the ability to find the optimal solution in a numerically efficient manner and satisfy the constraint accurately. Novel line search methods specially tailored for this type of optimization are also introduced. The proposed approaches exploit the geometrical properties of the constraint space in order to reduce the computational complexity. Array and multi-channel signal processing techniques are key technologies in wireless communication systems. High capacity and link reliability may be achieved by using multiple transmit and receive antennas. Combining multi-antenna techniques with multicarrier transmission leads to high the spectral efficiency and helps to cope with severe multipath propagation. The problem of channel equalization in MIMO-OFDM systems is also addressed in this thesis. A blind algorithm that optimizes of a combined criterion in order to be cancel both inter-symbol and co-channel interference is proposed. The algorithm local converge properties are established as well

Smart-antenna techniques for energy-efficient wireless sensor networks used in bridge structural health monitoring

Abstract: It is well known that wireless sensor networks differ from other computing platforms in that 1- they typically require a minimal amount of computing power at the nodes; 2- it is often desirable for sensor nodes to have drastically low power consumption. The main benefit of the this work is a substantial network life before batteries need to be replaced or, alternatively, the capacity to function off of modest environmental energy sources (energy harvesting). In the context of Structural Health Monitoring (SHM), battery replacement is particularly problematic since nodes can be in difficult to access locations. Furthermore, any intervention on a bridge may disrupt normal bridge operation, e.g. traffic may need to be halted. In this regard, switchbeam smart antennas in combination with wireless sensor networks (WSNs) have shown great potential in reducing implementation and maintenance costs of SHM systems. The main goal of implementing switch-beam smart antennas in our application is to reduce power consumption, by focusing the radiated energy only where it is needed. SHM systems capture the dynamic vibration information of a bridge structure in real-time in order to assess the health of the structure and to predict failures. Current SHM systems are based on piezoelectric patch sensors. In addition, the collection of data from the plurality of sensors distributed over the span of the bridge is typically performed through an expensive and bulky set of shielded wires which routes the information to a data sink at one end of the structure. The installation, maintenance and operational costs of such systems are extremely high due to high power consumption and the need for periodic maintenance. Wireless sensor networks represent an attractive alternative, in terms of cost, ease of maintenance, and power consumption. However, network lifetime in terms of node battery life must be very long (ideally 5–10 years) given the cost and hassle of manual intervention. In this context, the focus of this project is to reduce the global power consumption of the SHM system by implementing switched-beam smart antennas jointly with an optimized MAC layer. In the first part of the thesis, a sensor network platform for bridge SHM incorporating switched-beam antennas is modelled and simulated. where the main consideration is the joint optimization of beamforming parameters, MAC layer, and energy consumption. The simulation model, built within the Omnet++ network simulation framework, incorporates the energy consumption profiles of actual selected components (microcontroller, radio interface chip). The energy consumption and packet delivery ratio (PDR) of the network with switched-beam antennas is compared with an equivalent network based on omnidirectional antennas. In the second part of the thesis, this system model is leveraged to examine two distinct but interrelated aspects: Gallium Arsenide (GaAs) based solar energy harvesting and switched-beam antenna strategies. The main consideration here is the joint optimization of solar energy harvesting and switchedbeam directional antennas, where an equivalent network based on omnidirectional antennas acts as a baseline reference for comparison purposes.Il est bien connu que les réseaux de capteurs sans fils diffèrent des autres plateformes informatiques étant donné 1- qu’ils requièrent typiquement une puissance de calcul minimale aux noeuds du réseau ; 2- qu’il est souvent désirable que les noeuds capteurs aient une consommation d’énergie dramatiquement faible. La principale retombée de ce travail réside en la durée de vie allongée du réseau avant que les piles ne doivent être remplacées ou, alternativement, la capacité de fonctionner indéfiniment à partir de modestes sources d’énergie ambiente (glânage d’énergie). Dans le contexte du contrôle de la santé structurale (CSS), le remplacement de piles est particulièrement problématique puisque les noeuds peuvent se trouver en des endroits difficiles d’accès. De plus, toute intervention sur un pont implique une perturbation de l’opération normale de la structure, par exemple un arrêt du traffic. Dans ce contexte, les antennes intelligentes à commutation de faisceau en combinaison avec les réseaux de capteurs sans fils ont démontré un grand potentiel pour réduire les coûts de réalisation et d’entretien de systèmes de CSS. L’objectif principal de l’intégration d’antennes à commutation de faisceau dans notre application réside dans la réduction de la consommation énergétique, réalisée en concentrant l’énergie radiée uniquement là où elle est nécessaire. Les systèmes de CSS capturent l’information dynamique de vibration d’une structure de pont en temps réel de manière à évaluer la santé de la structure et prédire les failles. Les systèmes courants de CSS sont basés sur des senseurs piézoélectriques planaires. De plus, la collecte de données à partir de la pluralité de senseurs distribués sur l’étendue du pont est typiquement effectuée par le biais d’un ensemble coûteux et encombrant de câbles blindés qui véhiculent l’information jusqu’à un point de collecte à une extremité de la structure. L’installation, l’entretien, et les coûts opérationnels de tels systèmes sont extrêmement élevés étant donné la consommation de puissance élevée et le besoin d’entretien régulier. Les réseaux de capteurs sans fils représentent une alternative attrayante, en termes de coût, facilité d’entretien et consommation énergétique. Toutefois, la vie de réseau en termes de la durée de vie des piles doit être très longue (idéalement de 5 à 10 ans) étant donné le coût et les problèmes liés à l’intervention manuelle. Dans ce contexte, ce projet se concentre sur la réduction de la consommation de puissance globale d’un système de CSS en y intégrant des antennes intelligentes à commutation de faisceau conjointement avec une couche d’accès au médium (couche MAC) optimisée. Dans la première partie de la thèse, une plateforme de réseau de capteurs sans fils pour le CSS d’un pont incorporant des antennes à commutation de faisceaux est modélisé et simulé, avec pour considération principale l’optimisation des paramètres de sélection de faisceau, de la couche MAC et de la consommation d’énergie. Le modèle de simulation, construit dans le logiciel de simulation de réseaux Omnet++, incorpore les profils de consommation d’énergie de composants réels sélectionnés (microcontrôleur, puce d’interface radio). La consommation d’énergie et le taux de livraison de paquets du réseau avec antennes à commutation de faisceau est comparé avec un réseau équivalent basé sur des antennes omnidirectionnelles. Dans la deuxième partie de la thèse, le modèle système proposé est mis à contribution pour examiner deux aspects distrincts mais interreliés : le glânage d’énergie à partir de cellules solaire à base d’arséniure de Gallium (GaAs) et les stratégies liées aux antennes à commutation de faisceau. La considération principale ici est l’optimisation conjointe du glânage d’énergie et des antennes à commutation de faisceau, en ayant pour base de comparaison un réseau équivalent à base d’antennes omnidirectionnelles

Design and debugging of multi-step analog to digital converters

With the fast advancement of CMOS fabrication technology, more and more signal-processing functions are implemented in the digital domain for a lower cost, lower power consumption, higher yield, and higher re-configurability. The trend of increasing integration level for integrated circuits has forced the A/D converter interface to reside on the same silicon in complex mixed-signal ICs containing mostly digital blocks for DSP and control. However, specifications of the converters in various applications emphasize high dynamic range and low spurious spectral performance. It is nontrivial to achieve this level of linearity in a monolithic environment where post-fabrication component trimming or calibration is cumbersome to implement for certain applications or/and for cost and manufacturability reasons. Additionally, as CMOS integrated circuits are accomplishing unprecedented integration levels, potential problems associated with device scaling – the short-channel effects – are also looming large as technology strides into the deep-submicron regime. The A/D conversion process involves sampling the applied analog input signal and quantizing it to its digital representation by comparing it to reference voltages before further signal processing in subsequent digital systems. Depending on how these functions are combined, different A/D converter architectures can be implemented with different requirements on each function. Practical realizations show the trend that to a first order, converter power is directly proportional to sampling rate. However, power dissipation required becomes nonlinear as the speed capabilities of a process technology are pushed to the limit. Pipeline and two-step/multi-step converters tend to be the most efficient at achieving a given resolution and sampling rate specification. This thesis is in a sense unique work as it covers the whole spectrum of design, test, debugging and calibration of multi-step A/D converters; it incorporates development of circuit techniques and algorithms to enhance the resolution and attainable sample rate of an A/D converter and to enhance testing and debugging potential to detect errors dynamically, to isolate and confine faults, and to recover and compensate for the errors continuously. The power proficiency for high resolution of multi-step converter by combining parallelism and calibration and exploiting low-voltage circuit techniques is demonstrated with a 1.8 V, 12-bit, 80 MS/s, 100 mW analog to-digital converter fabricated in five-metal layers 0.18-µm CMOS process. Lower power supply voltages significantly reduce noise margins and increase variations in process, device and design parameters. Consequently, it is steadily more difficult to control the fabrication process precisely enough to maintain uniformity. Microscopic particles present in the manufacturing environment and slight variations in the parameters of manufacturing steps can all lead to the geometrical and electrical properties of an IC to deviate from those generated at the end of the design process. Those defects can cause various types of malfunctioning, depending on the IC topology and the nature of the defect. To relive the burden placed on IC design and manufacturing originated with ever-increasing costs associated with testing and debugging of complex mixed-signal electronic systems, several circuit techniques and algorithms are developed and incorporated in proposed ATPG, DfT and BIST methodologies. Process variation cannot be solved by improving manufacturing tolerances; variability must be reduced by new device technology or managed by design in order for scaling to continue. Similarly, within-die performance variation also imposes new challenges for test methods. With the use of dedicated sensors, which exploit knowledge of the circuit structure and the specific defect mechanisms, the method described in this thesis facilitates early and fast identification of excessive process parameter variation effects. The expectation-maximization algorithm makes the estimation problem more tractable and also yields good estimates of the parameters for small sample sizes. To allow the test guidance with the information obtained through monitoring process variations implemented adjusted support vector machine classifier simultaneously minimize the empirical classification error and maximize the geometric margin. On a positive note, the use of digital enhancing calibration techniques reduces the need for expensive technologies with special fabrication steps. Indeed, the extra cost of digital processing is normally affordable as the use of submicron mixed signal technologies allows for efficient usage of silicon area even for relatively complex algorithms. Employed adaptive filtering algorithm for error estimation offers the small number of operations per iteration and does not require correlation function calculation nor matrix inversions. The presented foreground calibration algorithm does not need any dedicated test signal and does not require a part of the conversion time. It works continuously and with every signal applied to the A/D converter. The feasibility of the method for on-line and off-line debugging and calibration has been verified by experimental measurements from the silicon prototype fabricated in standard single poly, six metal 0.09-µm CMOS process

Blind iterative multiuser detection for error coded CDMA systems.

Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2005.Mobile communications have developed since the radio communications that were in use 50 years ago. With the advent of GSM, mobile communications was brought to the average citizen. More recently, COMA technology has provided the user with higher data rates and more reliable service, and it is apparent that it is the future of wireless communication. With the introduction of 3G technology in South Africa, it is becoming clear that it is the solution to the country's wireless communication requirements. The 3G and next-generation technologies could provide reliable communications to areas where it has proven difficult to operate and maintain communications effectively, such as rural locations. It is therefore important that the se technologies continue to be researched in order to enhance their capabilities to provide a solution to the wireless needs of the local and global community. Whilst COMA is proving to be a reliable communications technology, it is still susceptible to the effects of the near-far problem and multiple-access interference. A number of multiuser detectors have been proposed in literature that attempt to mitigate the effects of multiple-access interference. A notable detector is the blind MOE detector, which requires only the desired user 's spreading sequence , and it exhibits performance approximating that of other linear multiuser detectors. Another promising class of multiuser detector operate using an iterative principle and have a joint multiuser detection and error-correcting coding scheme. The aim of this research is to develop a blind iterative detector with FEC coding as a potential solution to the need for a detector that can mitigate the effects of interfering users operating on the channel. The proposed detector has the benefits of both the blind and iterative schemes: it only requires the knowledge of the desired user ' s signature, and it has integrated error-correcting abilities. The simulation results presented in this dissertation show that the proposed detector exhibits superior performance over the blind MOE detector for various channel conditions. An overview of spread-spectrum technologies is presented, and the operation of OS-COMA is described in more detail. A history and overview of existing COMA standards is also given . The need for multiuser detection is explained, and a description and comparison of various detection methods that have appeared in literature is given. An introduction to error coding is given , with convolutional code s, the turbo coding concept and method s of iterative detection are described in more detail and compared, as iterat ive decoding is fundamental to the operation of an iterative COMA detector. An overview of iterative multiuser detection is given , and selected iterative methods are described in more detail. A blind iterative detector is proposed and analysed. Simulation results for the propo sed detector, and a comparison to the blind MOE detector is presented, showing performance characteristics and the effects of various channel parameters on performance. From these results it can be seen that the proposed detector exhibits a superior performance compared to that of the blind MOE detector for various channel conditions. The dissertation is concluded, and possible future directions of research are given

Convex Optimisation for Communication Systems

In this thesis new robust methods for the efficient sharing of the radio spectrum for underlay cognitive radio (CR) systems are developed. These methods provide robustness against uncertainties in the channel state information (CSI) that is available to the cognitive radios. A stochastic approach is taken and the robust spectrum sharing methods are formulated as convex optimisation problems. Three efficient spectrum sharing methods; power control, cooperative beamforming and conventional beamforming are studied in detail. The CR power control problem is formulated as a sum rate maximisation problem and transformed into a convex optimisation problem. A robust power control method under the assumption of partial CSI is developed and also transformed into a convex optimisation problem. A novel method of detecting and removing infeasible constraints from the power allocation problem is presented that results in considerably improved performance. The performance of the proposed methods in Rayleigh fading channels is analysed by simulations. The concept of cooperative beamforming for spectrum sharing is applied to an underlay CR relay network. Distributed single antenna relay nodes are utilised to form a virtual antenna array that provides increased gains in capacity through cooperative beamforming. It is shown that the cooperative beamforming problems can be transformed into convex optimisation problems. New robust cooperative beamformers under the assumption of partial and imperfect CSI are developed and also transformed into convex optimisation problems. The performance of the proposed methods in Rayleigh fading channels is analysed by simulations. Conventional beamforming to allow efficient spectrum sharing in an underlay CR system is studied. The beamforming problems are formulated and transformed into convex optimisation problems. New robust beamformers under the assumption of partial and imperfect CSI are developed and also transformed into convex optimisation problems. The performance of the proposed methods in Rayleigh fading channels is analysed by simulations

Optics for AI and AI for Optics

Artificial intelligence is deeply involved in our daily lives via reinforcing the digital transformation of modern economies and infrastructure. It relies on powerful computing clusters, which face bottlenecks of power consumption for both data transmission and intensive computing. Meanwhile, optics (especially optical communications, which underpin today’s telecommunications) is penetrating short-reach connections down to the chip level, thus meeting with AI technology and creating numerous opportunities. This book is about the marriage of optics and AI and how each part can benefit from the other. Optics facilitates on-chip neural networks based on fast optical computing and energy-efficient interconnects and communications. On the other hand, AI enables efficient tools to address the challenges of today’s optical communication networks, which behave in an increasingly complex manner. The book collects contributions from pioneering researchers from both academy and industry to discuss the challenges and solutions in each of the respective fields

A two phase framework for visible light-based positioning in an indoor environment: performance, latency, and illumination

Recently with the advancement of solid state lighting and the application thereof to Visible Light Communications (VLC), the concept of Visible Light Positioning (VLP) has been targeted as a very attractive indoor positioning system (IPS) due to its ubiquity, directionality, spatial reuse, and relatively high modulation bandwidth. IPSs, in general, have 4 major components (1) a modulation, (2) a multiple access scheme, (3) a channel measurement, and (4) a positioning algorithm. A number of VLP approaches have been proposed in the literature and primarily focus on a fixed combination of these elements and moreover evaluate the quality of the contribution often by accuracy or precision alone. In this dissertation, we provide a novel two-phase indoor positioning algorithmic framework that is able to increase robustness when subject to insufficient anchor luminaries and also incorporate any combination of the four major IPS components. The first phase provides robust and timely albeit less accurate positioning proximity estimates without requiring more than a single luminary anchor using time division access to On Off Keying (OOK) modulated signals while the second phase provides a more accurate, conventional, positioning estimate approach using a novel geometric constrained triangulation algorithm based on angle of arrival (AoA) measurements. However, this approach is still an application of a specific combination of IPS components. To achieve a broader impact, the framework is employed on a collection of IPS component combinations ranging from (1) pulsed modulations to multicarrier modulations, (2) time, frequency, and code division multiple access, (3) received signal strength (RSS), time of flight (ToF), and AoA, as well as (4) trilateration and triangulation positioning algorithms. Results illustrate full room positioning coverage ranging with median accuracies ranging from 3.09 cm to 12.07 cm at 50% duty cycle illumination levels. The framework further allows for duty cycle variation to include dimming modulations and results range from 3.62 cm to 13.15 cm at 20% duty cycle while 2.06 cm to 8.44 cm at a 78% duty cycle. Testbed results reinforce this frameworks applicability. Lastly, a novel latency constrained optimization algorithm can be overlaid on the two phase framework to decide when to simply use the coarse estimate or when to expend more computational resources on a potentially more accurate fine estimate. The creation of the two phase framework enables robust, illumination, latency sensitive positioning with the ability to be applied within a vast array of system deployment constraints