Abstract Uplink resource allocation strategies in modern cellular networks are studied in this thesis. With the presence of multiple antenna transmission, multiple base station (BS) coordination and multicarrier techniques, the resource allocation problem is reformulated and jointly optimized over a large set of variables. The focus is on the sum power minimization with per user rate constraints. A centralized multicarrier coordinated cellular network with multiple antennas implemented at the BS side is considered, where BSs can be adaptively clustered to detect signals from one mobile station (MS). The power, subcarrier, beamforming vector and BS cluster (BSC) are the design variables to be jointly optimized to satisfy the rate constraint per user. The first considered scenario is a simple single carrier multicell system. The power control problem with per user rate constraint can be optimally solved by the proposed algorithm, where power vector, BSC and beamforming vectors are separately updated until the sum power converges. The scenario is extended to more complicated multicarrier systems. The resource allocation problem is non-deterministic polynomial-time hard (NP-hard). Suboptimal algorithms are proposed to tackle the problem. To get more insights to the performance gap between the proposed algorithms and the capacity achieving bound, the scenario is specified to a single cell system with nonlinear receiver so that the calculation of the lower bound is possible. Efficient geometric aided fast converging power minimization algorithms are proposed to calculate the power bound of the multiple access channel (MAC) with per user rate constraint. By comparing the capacity achieving lower bound with the proposed algorithm, the BSW that starts from full rate allocation looks promising to have a good tradeoff between the convergence speed and the sum power consumption. Besides the resource allocation algorithms in the cellular network, the physical modeling and corresponding design of the network itself are also considered. The radio propagation in the elevation domain is modeled and considered. The diversity gain from the elevation domain is achieved by extra degree of freedom of beamforming in elevation domain. The antenna array can be either a uniform linear array or a uniform planar array with elements placed horizontally. The proposed power control algorithms are simulated in the 3D network scenarios. The effects of antenna array design in different propagation scenarios are compared. / Tiivistelmä Työssä tutkitaan ylälinkin resurssien kohdentamisstrategioita matkapuhelinverkoissa. Olettaen koordinointi useiden monikantoaaltotekniikoita käyttävien moniantennitukiasemien (BS) välillä, resurssien kohdentamisongelma muotoillaan uudelleen ja optimoidaan yli suuren joukon optimointimuuttujia. Erityisesti keskitytään yhteenlasketun tehon minimointiongelmaan käyttäjäkohtaisien siirtonopeusrajoitteiden kanssa. Työssä oletetaan keskitetty koordinointi useiden monikantoaaltotekniikoita käyttävien moniantennitukiasemien välillä, joten tukiasemat voidaan adaptiivisesti ryhmitellä yhden matkaviestimen signaalin havannointia varten. Lähetysteho, kantoaaltoallokaatio, keilanmuodostus ja tukiasemaklusterointi ovat ongelman muuttujia, jotka optimoidaan yhdessä siten, että käyttäjäkohtaiset siirtonopeusrajoitteet täyttyvät. Ensimmäinen käsitelty tapaus on yksinkertainen yhden operaattorin monisolujärjestelmä. Tehonsäätöongelma käyttäjäkohtaisten siirtonopeusrajoitusten kanssa voidaan optimaalisesti ratkaista ehdotetulla algoritmilla, jossa lähetysteho, keilanmuodostusvektorit ja tukiasemaklusterointi päivitetään erikseen, kunnes yhteenlaskettu teho suppenee. Tarkastelu laajennetaan monimutkaisempaan monikantoaaltojärjestelmään. Kun käyttäjäkohtainen siirtonopeustavoite kiinnitetään, ongelma voidaan vastaavasti hajottaa osittaisiksi alikantoaaltokohtaisiksi osaongelmiksi, jossa kukin osaongelma voidaan optimaalisesti ratkaista. Jos alikantoaaltokohtaista siirtonopeustavoitetta ei ole kiinnitetty, tehonsäätöongelmasta tulee ei-polynomisesti monimutkainen. Optimaalisia algoritmeja ehdotetaan ongelman ratkaisemiseksi. Jotta voitaisiin saada tietoa todellisesta suorituskykyerosta ehdotettujen algoritmien ja kapasiteettioptimaalisen rajan välillä, vertailu tehdään yhden solun simulointimallissa epälineaarisen vastaanottimen kanssa siten, että kapasiteettioptimaalisen alarajan laskeminen on mahdollista. Tätä varten kehitetään tehokas geometria-avusteinen ja nopeasti konvergoituva algoritmi tehon minimointia varten käyttäjäkohtaisten siirtonopeusrajoitusten kanssa. Vertaamalla kapasiteettioptimaalista alarajaa ehdotettujen algoritmien suorituskykyyn huomataan, että ehdotettu BSW algoritmi on hyvä kompromissi konvergoitumisnopeuden ja tehonkulutuksen välillä. Matkapuhelinverkkojen resurssienkohdentamisalgoritmien lisäksi työssä huomioidaan myös verkon fyysinen mallintaminen ja vastaava suunnittelu. Työssä mallinnetaan radiokanavan ominaisuudet myös korkeustasossa, joka mahdollistaa diversiteetin hyödyntämisen korkeustason keilanmuodostuksessa. Antenniryhmä voi olla joko yhtenäinen lineaarinen ryhmä tai yhtenäinen tasoryhmä, jossa antennielementit on sijoitettu tasoon. Ehdotettuja tehonsäätöalgoritmeja simuloidaan kolmiulotteisessa verkkoskenaarioissa, jossa verrataan antenniryhmäsuunnittelun vaikutuksia eri radiokanavaskenaarioissa.

This dissertation focuses on daily volt/var control in distribution networks with feeder capacitors, substation capacitors and transformers equipped with on-load tap changers. A hybrid approach is proposed to solve the daily volt/var control problem. To reduce the computational requirements of the problem, this approach combines two methods, namely heuristic and optimal scheduling for the substation and feeder sub-problems respectively. The feeder capacitor dispatch schedule is determined based on a heuristic reactive power setpoint method. At this stage the objective is to minimize the reactive power flow through the substation bus in every time-interval. And as such, mathematical modeling of the distribution network components is adapted to suit time-varying conditions. Furthermore, an optimization model to determine a proper dispatch schedule of the substation devices is formulated. The objective of this model is to minimize the daily total energy loss and voltage deviations. Additionally, the reference voltage of the substation secondary bus and the transformer tap position limits are modified to adapt to given load profiles. The optimization model is solved with a discrete particle swarm optimization algorithm, which incorporates Newton’s method to determine the power-flow solution. The proposed method is applied to a time-varying distribution system and evaluated under different operational scenarios. It is also compared to on-line volt/var control with various settings. Simulation results show that the proposed approach minimizes both the voltage deviations and the total energy loss, while on-line control prioritizes one objective over the other depending on the specified settings. / Dissertation (MEng)--University of Pretoria, 2015. / Electrical, Electronic and Computer Engineering / Unrestricted

This master´s thesis deals with a solution of the driving circuits of semiconductor laser. In the beginning of the thesis there is an analysis of semiconductor lasers and its characteristics. Then the principle of laser diodes and its excitation is described. This thesis is focused on semiconductor laser excitation through the use of direct and modulating current. Several circuits are described, designed and simulated. The best resulting circuit is realized and measured in the laboratory.

Connecting more non-dispatchable renewable energy sources (RESs) will result in a higher power variability and a lower system inertia when the synchronous generators are replaced by inverter-connected RES. Inverter control can be divided in three categories: grid-following, grid-forming (GFM) and grid-supporting. A literature review of inverter control strategies identifies the GFM control as having an important role in maintaining system stability assuming near 100 % inverter-connected RES. Critical aspects of the inverter control are also identified; the control need to function autonomously, be able to remain connected during transient events and be insensitive to grid topology. Combining various RES is also shown to improve system stability. The combination of RES that has been investigated in most studies is wind, solar and wave power. Wave power is still a young technology compared to solar and wind power. It generates higher power fluctuations over short time periods with a significant difference between average and maximum power. Additionally, wave power parks (WPPs) are often connected via long cables which contribute reactive power to the grid. These challenges has to be considered to maintain system stability and power quality when connecting a WPP to the grid. In a Power Hardware-In-the-Loop study of how a WPP affects the power quality at the point of common coupling (PCC), it is found that the impact is highest for WPPs with fewer generators as the variability is reduced when several generators are excited at different times. Energy storage is also shown to have a significant impact on the power quality at the PCC with reduced flicker, total harmonic distortion and power and voltage variability. A simulation study also shows the positive impact of energy storage on power variability and the role of inverter control in reactive power compensation.

Two topics in fading channels with a strict delay constraint and a resolution-constrained feedback link are treated in this thesis. First, a multi-layer variable-rate single-antenna communication system with quantized feedback, where the expected rate is chosen as the performance measure, is studied under both short-term and long-term power constraints. Iterative algorithms exploiting results in the literature of parallel broadcast channels are developed to design the system parameters. A necessary and sufficient condition for single-layer coding to be optimal is derived. In contrast to the ergodic case, it is shown that a few bits of feedback information can improve the expected rate dramatically. The role of multi-layer coding, however, reduces quickly as the resolution of the feedback link increases. The other part of the thesis deals with partial power control systems utilizing quantized feedback to minimize outage probability, with an emphasis on the diversity-multiplexing tradeoff. An index mapping with circular structure is shown to be optimal and the design is facilitated with a justified Gaussian approximation. The diversity gain as a function of the feedback resolution is analyzed. The results are then extended to characterize the entire diversity-multiplexing tradeoff curve of multiple-antenna channels with resolution-constrained feedback. Adaptive-rate communication is also studied, where the concept of minimum multiplexing gain is introduced. It is shown that the diversity gain of a system increases significantly even with coarsely quantized feedback, especially at low multiplexing gains. / QC 20101117

The heterogeneity and complexity of modern communication networks demands coupling network nodes with intelligence to perceive and adapt to different network conditions autonomously. Cognitive Networking is an emerging networking research area that aims to achieve this goal by applying distributed reasoning and learning across the protocol stack and throughout the network. Various cognitive node and cognitive network architectures with different levels of maturity have been proposed in the literature. All of them adopt the idea of coupling network devices with sensors to sense network conditions, artificial intelligence algorithms to solve problems, and a reconfigurable platform to apply solutions. However, little further research has investigated suitable reasoning and learning algorithms. In this dissertation, we take cognitive network research a step further by investigating the reasoning component of cognitive networks. In a deviation from previous suggestions, we suggest the use of a single flexible distributed reasoning algorithm for cognitive networks. We first propose an architecture for a cognitive node in a cognitive network that is general enough to apply to future networking challenges. We then introduce and justify our choice of the island genetic algorithm (iGA) as the distributed reasoning algorithm. Having introduced our cognitive node architecture, we then focus on the applicability of the island genetic algorithm as a single reasoning algorithm for cognitive networks. Our approach is to apply the island genetic algorithm to different single and cross layer communication and networking problems and to evaluate its performance through simulation. A proof of concept cognitive network is implemented to understand the implementation challenges and assess the island genetic algorithm performance in a real network environment. We apply the island genetic algorithm to three problems: channel allocation, joint power and channel allocation, and flow routing. The channel allocation problem is a major challenge for dynamic spectrum access which, in turn, has been the focal application for cognitive radios and cognitive networks. The other problems are examples of hard cross layer problems. We first apply the standard island genetic algorithm to a channel allocation problem formulated for the dynamic spectrum cognitive network environment. We also describe the details for implementing a cognitive network prototype using the universal software radio peripheral integrated with our extended implementation of the GNU radio software package and our island genetic algorithm implementation for the dynamic spectrum channel allocation problem. We then develop a localized variation of the island genetic algorithm, denoted LiGA, that allows the standard island genetic algorithm to scale and apply it to the joint power and channel allocation problem. In this context, we also investigate the importance of power control for cognitive networks and study the effect of non-cooperative behavior on the performance of the LiGA. The localized variation of the island genetic algorithm, LiGA, is powerful in solving node-centric problems and problems that requires only limited knowledge about network status. However, not every communication and networking problems can be solved efficiently in localized fashion. Thus, we propose a generalized version of the LiGA, namely the K-hop island genetic algorithm, as our final distributed reasoning algorithm proposal for cognitive networks. The K-hop island genetic algorithm is a promising algorithm to solve a large class of communication and networking problems with controllable cooperation and migration scope that allows for a tradeoff between performance and cost. We apply it to a flow routing problem that includes both power control and channel allocation. For all problems simulation results are provided to quantify the performance of the island genetic algorithm variation. In most cases, simulation and experimental results reveal promising performance for the island genetic algorithm. We conclude our work with a discussion of the shortcomings of island genetic algorithms without guidance from a learning mechanism and propose the incorporation of two learning processes into the cognitive node architecture to solve slow convergence and manual configuration problems. We suggest the cultural algorithm framework and reinforcement learning techniques as candidate leaning techniques for implementing the learning processes. However, further investigation and implementation is left as future work. / Ph. D.

The study started with the requirement that a photovoltaic (PV) power source should be integrated with other supplementary power sources whether it operates in a stand-alone or grid-connected mode. First, fuel cells for a backup of varying PV power were compared in detail with batteries and were found to have more operational benefits. Next, maximizing performance of a grid-connected PV-fuel cell hybrid system by use of a two-loop controller was discussed. One loop is a neural network controller for maximum power point tracking, which extracts maximum available solar power from PV arrays under varying conditions of insolation, temperature, and system load. A real/reactive power controller (RRPC) is the other loop. The RRPC meets the system's requirement for real and reactive powers by controlling incoming fuel to fuel cell stacks as well as switching control signals to a power conditioning subsystem. The RRPC is able to achieve more versatile control of real/reactive powers than the conventional power sources since the hybrid power plant does not contain any rotating mass. Results of time-domain simulations prove not only effectiveness of the proposed computer models of the two-loop controller, but also their applicability for use in transient stability analysis of the hybrid power plant. Finally, environmental evaluation of the proposed hybrid plant was made in terms of plant's land requirement and lifetime CO2 emissions, and then compared with that of the conventional fossil-fuel power generating forms. / Ph. D.

An important aspect of wireless networks is their dynamic behavior. The conventional protocol stack is inflexible as various protocol layers communicate in a strict manner. In such a case the layers are designed to operate under the worst conditions as opposed to adapting to changing conditions. This leads to inefficient use of spectrum and energy. Adaptation represents the ability of network protocols and applications to observe and respond to channel conditions. Traditional simulation methodologies independently model the physical and higher layers. When multiple layer simulations are required, an abstraction of one layer is inserted into the other to provide the multiple layer simulation. However, recent advances in wireless communication technologies, such as adaptive modulation and adaptive antenna algorithms, demand a cross layer perspective to this problem in order to provide a sufficient level of fidelity. However, a full simulation of both layers often results in excessively burdensome simulation run-times. The benefits and possible parametric characterization issues arising due to the cross-layer integration of lower physical and higher network layers are investigated in this thesis. The primary objective of investigating cross-layer simulation techniques is to increase the fidelity of cross-layer network simulations while minimizing the simulation runtime penalties. As a study of cross-layer system design a medium access control (MAC) scheme is studied for a MANET wherein the nodes are equipped with smart antennas. Traditional MAC protocols assume the use of omnidirectional antennas. Nodes with directional antennas are capable of transmitting in certain directions only and significantly reduce the chances of collision and increase the effective network capacity. MANETs using omni-directional antennas severely limit system performance as the entire space around a node up to its radio range is seen as a single logical channel. In this research a MAC protocol is studied that exploits space division multiple access at the physical layer. This is a strong example where physical and MAC design must be carried out simultaneously for adequate system performance. Power control is a very important in the design of cellular CDMA systems which suffer from the near-far problem. Finally, the interaction between successive interference cancellation (SIC) receivers at the physical layer and power control, which is a layer 2 radio resource management issue, is studied. Traffic for future wireless networks is expected to be a mix of real-time traffic such as voice, multimedia teleconferencing, and games and data traffic such as web browsing, messaging, etc. All these applications will require very diverse quality of service guarantees. A power control algorithm is studied, which drives the average received powers to those required, based on the QoS requirements of the individual users for a cellular CDMA system using SIC receivers. / Master of Science

Network lifetime is an important performance metric in Wireless Sensor Networks (WSNs). Transmission Power Control (TPC) is a well-established method to minimise energy consumption in transmission in order to extend node lifetime and, consequently, lead to solutions that help extend network lifetime. The accurate lifetime estimation of sensor nodes is useful for routing to make more energy-efficient decisions and prolong lifetime. This research proposes an Energy-Efficient TPC (EETPC) mechanism using the measured Received Signal Strength (RSS) to calculate the ideal transmission power. This includes the investigation of the impact factors on RSS, such as distance, height above ground, multipath environment, the capability of node, noise and interference, and temperature. Furthermore, a Dynamic Node Lifetime Estimation (DNLE) technique for WSNs is also presented, including the impact factors on node lifetime, such as battery type, model, brand, self-discharge, discharge rate, age, charge cycles, and temperature. In addition, an Energy-Efficient and Lifetime Aware Routing (EELAR) algorithm is designed and developed for prolonging network lifetime in multihop WSNs. The proposed routing algorithm includes transmission power and lifetime metrics for path selection in addition to the Expected Transmission Count (ETX) metric. Both simulation and real hardware testbed experiments are used to verify the effectiveness of the proposed schemes. The simulation experiments run on the AVRORA simulator for two hardware platforms: Mica2 and MicaZ. The testbed experiments run on two real hardware platforms: the N740 NanoSensor and Mica2. The corresponding implementations are on two operating systems: Contiki and TinyOS. The proposed TPC mechanism covers those investigated factors and gives an overall performance better than the existing techniques, i.e. it gives lower packet loss and power consumption rates, while delays do not significantly increase. It can be applied for single-hop with multihoming and multihop networks. Using the DNLE technique, node lifetime can be predicted more accurately, which can be applied for both static and dynamic loads. EELAR gives the best performance on packet loss rate, average node lifetime and network lifetime compared to the other algorithms and no significant difference is found between each algorithm with the packet delay.

Dans le cadre de cette thèse, nous nous intéressons plus particulièrement àdeux techniques permettant d’améliorer l’efficacité énergétique ou spectrale desréseaux sans fil. Dans la première partie de cette thèse, nous proposons de combinerles capacités de prédictions du contexte futur de transmission au classiqueet connu tradeoff latence - efficacité énergétique, amenant à ce que l’on nommeraun réseau proactif tolérant à la latence. L’objectif dans ce genre de problèmesconsiste à définir des politiques de transmissions optimales pour un ensembled’utilisateur, qui garantissent à chacun de pouvoir accomplir une transmissionavant un certain délai, tout en minimisant la puissance totale consommée auniveau de chaque utilisateur. Nous considérons dans un premier temps le problèmemono-utilisateur, qui permet alors d’introduire les concepts de tolérance àla latence, d’optimisation et de contrôle de puissance qui sont utilisés dans lapremière partie de cette thèse. L’extension à un système multi-utilisateurs estensuite considérée. L’analyse révèle alors que l’optimisation multi-utilisateurpose problème du fait de sa complexité mathématique. Mais cette complexitépeut néanmoins être contournée grâce aux récentes avancées dans le domainede la théorie des jeux à champs moyens, théorie qui permet de transiter d’unjeu multi-utilisateur, vers un jeu à champ moyen, à plus faible complexité. Lessimulations numériques démontrent que les stratégies de puissance retournéespar l’approche jeu à champ moyen approchent notablement les stratégies optimaleslorsqu’elles peuvent être calculées, et dépassent les performances desheuristiques communes, lorsque l’optimum n’est plus calculable, comme c’est lecas lorsque le canal varie au cours du temps.Dans la seconde partie de cettethèse, nous investiguons un possible problème dual au problème précédent. Plusspécifiquement, nous considérons une approche d’optimisation d’efficacité spectrale,à configuration de puissance constante. Pour ce faire, nous proposonsalors d’étudier l’impact sur le réseau des récentes avancées en classification d’interférence.L’analyse conduite révèle que le système peut bénéficier d’uneadaptation des traitements d’interférence faits à chaque récepteur. Ces gainsobservés peuvent également être améliorés par deux altérations de la démarched’optimisation. La première propose de redéfinir les groupes d’interféreurs decellules concurrentes, supposés transmettre sur les mêmes ressources spectrales.L’objectif étant alors de former des paires d’interféreurs “amis”, capables detraiter efficacement leurs interférences réciproques. La seconde altération portele nom de “Virtual Handover” : lorsque la classification d’interférence est considérée,l’access point offrant le meilleur SNR n’est plus nécessairement le meilleuraccess point auquel assigner un utilisateur. Pour cette raison, il est donc nécessairede laisser la possibilité au système de pouvoir choisir par lui-même la façondont il procède aux assignations des utilisateurs. Le processus d’optimisationse décompose donc en trois parties : i) Définir les coalitions d’utilisateurs assignésà chaque access point ; ii) Définir les groupes d’interféreurs transmettantsur chaque ressource spectrale ; et iii) Définir les stratégies de transmissionet les traitements d’interférences optimaux. L’objectif de l’optimisationest alors de maximiser l’efficacité spectrale totale du système après traitementde l’interférence. Les différents algorithmes utilisés pour résoudre, étape parétape, l’optimisation globale du système sont détaillés. Enfin, des simulationsnumériques permettent de mettre en évidence les gains de performance potentielsofferts par notre démarche d’optimisation. / In this thesis, we investigate two techniques used for enhancing the energy orspectral efficiency of the network. In the first part of the thesis, we propose tocombine the network future context prediction capabilities with the well-knownlatency vs. energy efficiency tradeoff. In that sense, we consider a proactivedelay-tolerant scheduling problem. In this problem, the objective consists ofdefining the optimal power strategies of a set of competing users, which minimizesthe individual power consumption, while ensuring a complete requestedtransmission before a given deadline. We first investigate the single user versionof the problem, which serves as a preliminary to the concepts of delay tolerance,proactive scheduling, power control and optimization, used through the first halfof this thesis. We then investigate the extension of the problem to a multiusercontext. The conducted analysis of the multiuser optimization problem leads toa non-cooperative dynamic game, which has an inherent mathematical complexity.In order to address this complexity issue, we propose to exploit the recenttheoretical results from the Mean Field Game theory, in order to transitionto a more tractable game with lower complexity. The numerical simulationsprovided demonstrate that the power strategies returned by the Mean FieldGame closely approach the optimal power strategies when it can be computed(e.g. in constant channels scenarios), and outperform the reference heuristicsin more complex scenarios where the optimal power strategies can not be easilycomputed.In the second half of the thesis, we investigate a dual problem to the previousoptimization problem, namely, we seek to optimize the total spectral efficiencyof the system, in a constant short-term power configuration. To do so, we proposeto exploit the recent advances in interference classification. the conductedanalysis reveals that the system benefits from adapting the interference processingtechniques and spectral efficiencies used by each pair of Access Point (AP) and User Equipment (UE). The performance gains offered by interferenceclassification can also be enhanced by considering two improvements. First, wepropose to define the optimal groups of interferers: the interferers in a samegroup transmit over the same spectral resources and thus interfere, but can processinterference according to interference classification. Second, we define theconcept of ’Virtual Handover’: when interference classification is considered,the optimal Access Point for a user is not necessarily the one providing themaximal SNR. For this reason, defining the AP-UE assignments makes sensewhen interference classification is considered. The optimization process is thenthreefold: we must define the optimal i) interference processing technique andspectral efficiencies used by each AP-UE pair in the system; ii) the matching ofinterferers transmitting over the same spectral resources; and iii) define the optimalAP-UE assignments. Matching and interference classification algorithmsare extensively detailed in this thesis and numerical simulations are also provided,demonstrating the performance gain offered by the threefold optimizationprocedure compared to reference scenarios where interference is either avoidedwith orthogonalization or treated as noise exclusively.