Robust Reduced-Rank Adaptive Processing Based on Parallel Subgradient Projection and Krylov Subspace Techniques

In this paper, we propose a novel reduced-rank adaptive filtering algorithm by blending the idea of the Krylov subspace methods with the set-theoretic adaptive filtering framework. Unlike the existing Krylov-subspace-based reduced-rank methods, the proposed algorithm tracks the optimal point in the sense of minimizing the \sinq{true} mean square error (MSE) in the Krylov subspace, even when the estimated statistics become erroneous (e.g., due to sudden changes of environments). Therefore, compared with those existing methods, the proposed algorithm is more suited to adaptive filtering applications. The algorithm is analyzed based on a modified version of the adaptive projected subgradient method (APSM). Numerical examples demonstrate that the proposed algorithm enjoys better tracking performance than the existing methods for the interference suppression problem in code-division multiple-access (CDMA) systems as well as for simple system identification problems.Comment: 10 figures. In IEEE Transactions on Signal Processing, 201

Adaptive Techniques for Packet-Oriented Transmissions in Future Multicarrier Wireless Systems

I sistemi wireless dei prossimi anni sono tenuti a fornire trasmissioni caratterizzate da data rate e affidabilità sempre maggiori per sostenere la sempre più crescente richiesta di applicazioni e servizi eterogenei. Inoltre, tali requisiti devono essere soddisfatti nel difficile ambiente di propagazione rappresentato dal canale wireless, e devono far fronte alla scarsità dello spettro radio disponibile. Per tali sistemi, la tecnica di modulazione multiportante nota come orthogonal frequency division multiplexing (OFDM) è emersa come tecnologia chiave a livello fisico grazie alla sua elevata efficienza spettrale, struttura di ricetrasmissione piuttosto semplice e robustezza al fenomeno di multipath fading. In tale contesto, questa tesi indaga nuove tecniche adattative in cui le risorse e parametri di trasmissione sono adattati in base alle informazioni sullo stato di canale al fine di fornire una consegna affidabile ed efficiente di pacchetti dati su canali selettivi in frequenza. Queste tecniche, note in letteratura come link resource adaptation (LRA) e resource allocation (RA), sono proposte in combinazione con un numero di funzionalità avanzate come l'efficiente tecnica di codifica di canale chiamata bit interleaved coded modulation (BICM) e meccanismi di hybrid automatic repeat request (HARQ). Diversamente dalla maggior parte dei problemi di LRA e RA considerati nella letteratura, questa tesi si basa sul goodput come figura di merito, definito come il numero di bit di informazione consegnati in pacchetti senza errori per unità di tempo. Quest'ultimo rappresenta, infatti, una metrica adeguata per dare un quadro attendibile delle effettive prestazioni del collegamento caratterizzato da modulazione e codifici pratici, trasmissioni a pacchetto e meccanismi di HARQ. In dettaglio, i contributi principali della tesi sono: la derivazione di una strategia di LRA che assegna modulazione, tasso di codifica e potenza ad un sistema BIC-OFDM cognitivo; un nuovo metodo di predizione delle prestazioni, che sfrutta la metodologia di effective signal-to-noise ratio (SNR), per sistemi BIC-OFDM impieganti protocolli di HARQ con packet combining; un algoritmo di LRA che seleziona la migliore distribuzione dei bit e tasso di codifica per sistemi BIC-OFDM; uno schema equo di RA che assegna potenza, ordine di modulazione, tasso di codifica e sottoportanti agli utenti sul downlink di un sistema BIC orthogonal frequency division multiple access (OFDMA) col fine di ottimizzare le prestazioni dell'utente avente il valore più basso di goodput

Resource allocation for wireless networks: learning, competition and coordination.

Lin, Xingqin.Thesis (M.Phil.)--Chinese University of Hong Kong, 2011.Includes bibliographical references (p. 103-109).Abstracts in English and Chinese.Abstract --- p.iAcknowledgement --- p.iiiChapter 1 --- Introduction --- p.1Chapter 1.1 --- Motivation --- p.1Chapter 1.2 --- Background --- p.3Chapter 1.2.1 --- Wireless Communication Schemes --- p.3Chapter 1.2.2 --- Mathematical Preliminaries --- p.8Chapter 1.3 --- Outline of the Thesis --- p.12Chapter 2 --- Learning for Parallel Gaussian Interference Channels --- p.14Chapter 2.1 --- System Model and Problem Formulation --- p.16Chapter 2.2 --- Stochastic Algorithm for Learning --- p.18Chapter 2.2.1 --- Algorithm Design --- p.18Chapter 2.2.2 --- Convergence Analysis --- p.21Chapter 2.3 --- Continuous Time Approximation --- p.26Chapter 2.4 --- Learning with Averaging --- p.28Chapter 2.5 --- Numerical Results --- p.29Chapter 3 --- Power Control for One-to-Many Transmissions --- p.34Chapter 3.1 --- System Model --- p.35Chapter 3.2 --- A GNEP Approach --- p.38Chapter 3.2.1 --- Problem Formulation --- p.38Chapter 3.2.2 --- Preliminary Results --- p.39Chapter 3.3 --- Algorithm Design --- p.42Chapter 3.4 --- Numerical Results --- p.46Chapter 4 --- Flow Allocation in Multiple Access Networks --- p.50Chapter 4.1 --- System Model and Problem Formulation --- p.52Chapter 4.1.1 --- System Model --- p.52Chapter 4.1.2 --- Problem Formulation --- p.53Chapter 4.2 --- Characterization of NE --- p.57Chapter 4.2.1 --- Feasibility Assumption --- p.57Chapter 4.2.2 --- Existence and Uniqueness of NE --- p.58Chapter 4.3 --- Distributed Algorithms Design --- p.60Chapter 4.3.1 --- D-SBRA --- p.60Chapter 4.3.2 --- P-SBRA --- p.61Chapter 4.3.3 --- Best Response and Layered Structure --- p.65Chapter 4.4 --- Performance Evaluation --- p.67Chapter 4.4.1 --- Protocol Evaluation --- p.67Chapter 4.4.2 --- Convergence and Performance --- p.69Chapter 4.4.3 --- Flow Distribution --- p.71Chapter 4.4.4 --- A Grid Network Simulation --- p.73Chapter 5 --- Relay Assignment in Cooperative Networks --- p.76Chapter 5.1 --- System Model and Problem Formulation --- p.77Chapter 5.1.1 --- Three-Node Relay Model --- p.77Chapter 5.1.2 --- Network Model --- p.78Chapter 5.1.3 --- Problem Formulation --- p.78Chapter 5.2 --- Centralized Scheme --- p.80Chapter 5.2.1 --- Generalized Relay Assignment --- p.80Chapter 5.2.2 --- Admission Control --- p.83Chapter 5.2.3 --- Iteration Algorithm and Some Remarks --- p.84Chapter 5.3 --- A Simple Distributed Algorithm --- p.84Chapter 5.4 --- Numerical Results --- p.86Chapter 6 --- Conclusions and Future Work --- p.88Chapter 6.1 --- Conclusions --- p.88Chapter 6.2 --- Future Work --- p.89Chapter A --- Proof of Theorem 21 --- p.93Chapter B --- Proof of Theorem 22 --- p.96Chapter C --- Proof of Proposition 31 --- p.98Chapter D --- Proof of Proposition 44 --- p.101Bibliography --- p.10

Resource management techniques for sustainable networks with energy harvesting nodes

Premi extraordinari doctorat UPC curs 2015-2016, àmbit Enginyeria de les TICThis dissertation proposes novel techniques for assigning resources of wireless networks by considering that the coverage radii are small, implying that some power consumption sinks not considered so far shouldnow be introduced, and by considering that the devices are battery-powered terminals provided with energy harvesting capabilities. In this framework, two different configurations in terms of harvesting capabilities are considered. First, we assume that the energy source is external and not controllable, e.g. solar energy. In this context, the proposed design should adapt to the energy that is currently being harvested. We also study the effect of having a finite backhaul connection that links the wireless access network with the core network. On the other hand, we propose a design in which the transmitter feeds actively the receivers with energy by transmitting signals that receivers use for recharging their batteries. In this case, the power transfer design should be carried out jointly with the power control strategy for users that receive information as both procedures, transfer of information and transfer of power, are implemented at the transmitter and make use of a common resource, i.e., power. Apart from techniques for assigning the radio resources, this dissertation develops a procedure for switching on and off base stations. Concerning this, it is important to notice that the traffic profile is not constant throughout the day. This is precisely the feature that can be exploited to define a strategy based on a dynamic selection of the base stations to be switched off when the traffic load is low, without affecting the quality experienced by the users. Thanks to this procedure, we are able to deploy smaller energy harvesting sources and smaller batteries and, thus, to reduce the cost of the network deployment. Finally, we derive some procedures to optimize high level decisions of the network operation in which variables from several layers of the protocol stack are involved. In this context, admission control procedures for deciding which user should be connected to which base station are studied, taking into account information of the average channel information, the current battery levels, etc. A multi-tier multi-cell scenario is assumed in which base stations belonging to different tiers have different capabilities, e.g., transmission power, battery size, end energy harvesting source size. A set of strategies that require different computational complexity are derived for scenarios with different user mobility requirements.Aquesta tesis doctoral proposa tècniques per assignar els recursos disponibles a les xarxes wireless considerant que els radis de cobertura són petits, el que implica que altres fonts de consum d’energia no considerades fins al moment s’hagin d’introduir dins els dissenys, i considerant que els dispositius estan alimentats amb bateries finites i que tenen a la seva disposició fonts de energy harvesting. En aquest context, es consideren dues configuracions diferents en funció de les capacitats de l’energia harvesting. En primer lloc, s’assumirà que la font d’energia és externa i incontrolable com, per exemple, l’energia solar. Els dissenys proposats han d’adaptar-se a l’energia que s’està recol·lectant en un precís moment. En segon lloc, es proposa un disseny en el qual el transmissor és capaç d’enviar energia als receptors mitjançant senyals de radiofreqüència dissenyats per aquest fi, energia que és utilitzada per recarregar les bateries. A part de tècniques d’assignació de recursos radio, en aquesta tesis doctoral es desenvolupa un procediment dinàmic per apagar i encendre estacions base. És important notar que el perfil de tràfic no és constant al llarg del dia. Aquest és precisament el patró que es pot explotar per definir una estratègia dinàmica per poder decidir quines estaciones base han de ser apagades, tot això sense afectar la qualitat experimentada pels usuaris. Gràcies a aquest procediment, es possible desplegar fonts d'energy harvesting més petites i bateries més petites. Finalment, aquesta tesis doctoral presenta procediments per optimitzar decisions de nivell més alt que afecten directament al funcionament global de la xarxa d’accés. Per prendre aquestes decisions, es fa ús de diverses variables que pertanyen a diferents capes de la pila de protocols. En aquest context, aquesta tesis aborda el disseny de tècniques de control d’admissió d’usuaris a estacions base en entorns amb múltiples estacions base, basant-se amb la informació estadística dels canals, i el nivell actual de les bateries, entre altres. L'escenari considerat està format per múltiples estacions base, on cada estació base pertany a una família amb diferents capacitats, per exemple, potència de transmissió o mida de la bateria. Es deriven un conjunt de tècniques amb diferents costos computacionals que són d'utilitat per a poder aplicar a escenaris amb diferents mobilitats d’usuaris.Award-winningPostprint (published version

Resource Management in Multicarrier Based Cognitive Radio Systems

The ever-increasing growth of the wireless application and services affirms the importance of the effective usage of the limited radio spectrum. Existing spectrum management policies have led to significant spectrum under-utilization. Recent measurements showed that large range of the spectrum is sparsely used in both temporal and spatial manner. This conflict between the inefficient usage of the spectrum and the continuous evolution in the wireless communication calls upon the development of more flexible management policies. Cognitive radio (CR) with the dynamic spectrum access (DSA) is considered to be a key technology in making the best solution of this conflict by allowing a group of secondary users (SUs) to share the radio spectrum originally allocated to the primary user (PUs). The operation of CR should not negatively alter the performance of the PUs. Therefore, the interference control along with the highly dynamic nature of PUs activities open up new resource allocation problems in CR systems. The resource allocation algorithms should ensure an effective share of the temporarily available frequency bands and deliver the solutions in timely fashion to cope with quick changes in the network. In this dissertation, the resource management problem in multicarrier based CR systems is considered. The dissertation focuses on three main issues: 1) design of efficient resource allocation algorithms to allocate subcarriers and powers between SUs such that no harmful interference is introduced to PUs, 2) compare the spectral efficiency of using different multicarrier schemes in the CR physical layer, specifically, orthogonal frequency division multiplexing (OFDM) and filter bank multicarrier (FBMC) schemes, 3) investigate the impact of the different constraints values on the overall performance of the CR system. Three different scenarios are considered in this dissertation, namely downlink transmission, uplink transmission, and relayed transmission. For every scenario, the optimal solution is examined and efficient sub-optimal algorithms are proposed to reduce the computational burden of obtaining the optimal solution. The suboptimal algorithms are developed by separate the subcarrier and power allocation into two steps in downlink and uplink scenarios. In the relayed scenario, dual decomposition technique is used to obtain an asymptotically optimal solution, and a joint heuristic algorithm is proposed to find the suboptimal solution. Numerical simulations show that the proposed suboptimal algorithms achieve a near optimal performance and perform better than the existing algorithms designed for cognitive and non-cognitive systems. Eventually, the ability of FBMC to overcome the OFDM drawbacks and achieve more spectral efficiency is verified which recommends the consideration of FBMC in the future CR systems.El crecimiento continuo de las aplicaciones y servicios en sistemas inal´ambricos, indica la importancia y necesidad de una utilizaci´on eficaz del espectro radio. Las pol´ıticas actuales de gesti´on del espectro han conducido a una infrautilizaci´on del propio espectro radioel´ectrico. Recientes mediciones en diferentes entornos han mostrado que gran parte del espectro queda poco utilizado en sus ambas vertientes, la temporal, y la espacial. El permanente conflicto entre el uso ineficiente del espectro y la evoluci´on continua de los sistemas de comunicaci´on inal´ambrica, hace que sea urgente y necesario el desarrollo de esquemas de gesti´on del espectro m´as flexibles. Se considera el acceso din´amico (DSA) al espectro en los sistemas cognitivos como una tecnolog´ıa clave para resolver este conflicto al permitir que un grupo de usuarios secundarios (SUs) puedan compartir y acceder al espectro asignado inicialmente a uno o varios usuarios primarios (PUs). Las operaciones de comunicaci´on llevadas a cabo por los sistemas radio cognitivos no deben en ning´un caso alterar (interferir) los sistemas primarios. Por tanto, el control de la interferencia junto al gran dinamismo de los sistemas primarios implica nuevos retos en el control y asignaci´on de los recursos radio en los sistemas de comunicaci´on CR. Los algoritmos de gesti´on y asignaci´on de recursos (Radio Resource Management-RRM) deben garantizar una participaci´on efectiva de las bandas con frecuencias disponibles temporalmente, y ofrecer en cada momento oportunas soluciones para hacer frente a los distintos cambios r´apidos que influyen en la misma red. En esta tesis doctoral, se analiza el problema de la gesti´on de los recursos radio en sistemas multiportadoras CR, proponiendo varias soluciones para su uso eficaz y coexistencia con los PUs. La tesis en s´ı, se centra en tres l´ıneas principales: 1) el dise˜no de algoritmos eficientes de gesti´on de recursos para la asignaci´on de sub-portadoras y distribuci´on de la potencia en sistemas segundarios, evitando asi cualquier interferencia que pueda ser perjudicial para el funcionamiento normal de los usuarios de la red primaria, 2) analizar y comparar la eficiencia espectral alcanzada a la hora de utilizar diferentes esquema de transmisi´on multiportadora en la capa f´ısica del sistema CR, espec´ıficamente en sistemas basados en OFDM y los basados en banco de filtros multiportadoras (Filter bank Multicarrier-FBMC), 3) investigar el impacto de las diferentes limitaciones en el rendimiento total del sistema de CR. Los escenarios considerados en esta tesis son tres, es decir; modo de transmisi´on descendente (downlink), modo de transmisi´on ascendente (uplink), y el modo de transmisi´on ”Relay”. En cada escenario, la soluci´on ´optima es examinada y comparada con algoritmos sub- ´optimos que tienen como objetivo principal reducir la carga computacional. Los algoritmos sub-´optimos son llevados a cabo en dos fases mediante la separaci´on del propio proceso de distribuci´on de subportadoras y la asignaci´on de la potencia en los modos de comunicaci´on descendente (downlink), y ascendente (uplink). Para los entornos de tipo ”Relay”, se ha utilizado la t´ecnica de doble descomposici´on (dual decomposition) para obtener una soluci´on asint´oticamente ´optima. Adem´as, se ha desarrollado un algoritmo heur´ıstico para poder obtener la soluci´on ´optima con un reducido coste computacional. Los resultados obtenidos mediante simulaciones num´ericas muestran que los algoritmos sub-´optimos desarrollados logran acercarse a la soluci´on ´optima en cada uno de los entornos analizados, logrando as´ı un mayor rendimiento que los ya existentes y utilizados tanto en entornos cognitivos como no-cognitivos. Se puede comprobar en varios resultados obtenidos en la tesis la superioridad del esquema multiportadora FBMC sobre los sistemas basados en OFDM para los entornos cognitivos, causando una menor interferencia que el OFDM en los sistemas primarios, y logrando una mayor eficiencia espectral. Finalmente, en base a lo analizado en esta tesis, podemos recomendar al esquema multiportadora FBMC como una id´onea y potente forma de comunicaci´on para las futuras redes cognitivas

Resource Optimization for multi-antenna Cognitive radio networks

Ph.DDOCTOR OF PHILOSOPH

Integrated Scheduling and Beam Steering for Spatial Reuse

This document describes an approach to integrating antenna selection and control into a time-division MAC scheduling process. I argue that through such integration it is possible to achieve greater spatial reuse and interference mitigation than by solving the two problems separately. Without coupling between the MAC scheduling and physical antenna configuration processes, a \u22chicken-and-egg\u22 problem exists: If antenna decisions are made before scheduling, they cannot be optimized for the communication that will actually occur. If, on the other hand, the scheduling decisions are made first, the scheduler cannot know what the actual interference and communications properties of the network will be. This dissertation presents algorithms for optimal spatial reuse TDMA scheduling with reconfigurable antennas. I present and solve the joint beam steering and scheduling problem for spatial reuse TDMA and describe an implemented system based on the algorithms developed. The algorithms described achieve up to a 600% speedup over TDMA in the experiments performed. This is based on using an optimization decomposition approach to arrive at a working distributed protocol which is equivalent to the original problem statement while also producing optimal solutions in an amount of time that is at worst linear in the size of the input. This is, to the best of my knowledge, the first actually implemented STDMA scheduling system based on dual decomposition. This dissertation identifies and briefly address some of the challenges that arise in taking such a system from theory to reality