Abstract Spectrum sharing has become a high priority research area over the past few years. The motivation behind this lies in the fact that the limited spectrum is currently inefficiently utilized. As recognized by the World radio communication conference (WRC)-07, the amount of identified spectrum is not large enough to support large bandwidths for a substantial number of operators. Therefore, it is paramount for future mobile cellular systems to share the frequency spectrum and coexist in a more efficient manner. The present dissertation deals with the problem of spectrum scarcity by examining spectrum sharing paradigms where a migration from fixed to flexible resource allocation is investigated. First, a radio resource management (RRM) architecture is proposed where advanced spectrum functionalities accounting for the short-term variations of the spectrum are examined. The achievable gains are shown in a multi-cell, multi-network environment with realistic traffic patterns from a European operator, enhancing thereby spectrum utilization. Second, inter-operator resource sharing in a broadband network is considered where a packet-based cellular network is developed. It is shown that the obtained gains in terms of quality-of-service (QoS), number of operators and different data rates requirements improve the overall efficiency of the network. Besides and in order to cope with the stringent data rate requirements, direct terminal-to-terminal (T2T) communication is examined in which a realistic algorithm is proposed advocating resource reuse in a cellular system with simultaneous communications between mobiles. Numerical results confirm the advantages of resource reuse in terms of throughput, average frame delays and power consumption. In this thesis, a proposal is made as how to enhance spectrum sharing. The concept of hierarchy is proposed in which wireless competitive operators share the same spectrum band. The decentralized hierarchical approach is shown to bridge the gap between the selfish and centralized approach. Interference avoidance is studied for point-to-point communication in a selforganized network where different optimal power allocation strategies are examined along with the impact of frequency reuse on the ergodic capacity of the network.

COOPERATIVE WIDEBAND SPECTRUM SENSING BASED ON JOINT SPARSITY By Ghazaleh Jowkar, Master of Science A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science at Virginia Commonwealth University Virginia Commonwealth University 2017 Major Director: Dr. Ruixin Niu, Associate Professor of Department of Electrical and Computer Engineering In this thesis, the problem of wideband spectrum sensing in cognitive radio (CR) networks using sub-Nyquist sampling and sparse signal processing techniques is investigated. To mitigate multi-path fading, it is assumed that a group of spatially dispersed SUs collaborate for wideband spectrum sensing, to determine whether or not a channel is occupied by a primary user (PU). Due to the underutilization of the spectrum by the PUs, the spectrum matrix has only a small number of non-zero rows. In existing state-of-the-art approaches, the spectrum sensing problem was solved using the low-rank matrix completion technique involving matrix nuclear-norm minimization. Motivated by the fact that the spectrum matrix is not only low-rank, but also sparse, a spectrum sensing approach is proposed based on minimizing a mixed-norm of the spectrum matrix instead of low-rank matrix completion to promote the joint sparsity among the column vectors of the spectrum matrix. Simulation results are obtained, which demonstrate that the proposed mixed-norm minimization approach outperforms the low-rank matrix completion based approach, in terms of the PU detection performance. Further we used mixed-norm minimization model in multi time frame detection. Simulation results shows that increasing the number of time frames will increase the detection performance, however, by increasing the number of time frames after a number of times the performance decrease dramatically.

Cognitive radio (CR) is one of the most prominent technique to deal with the radio spectrum scarcity problem. CR systems can improve radio spectrum utilization by opportunistically accessing the underutilized spectrum resource of the licensed users. In interweave implementation, the secondary user (SU) has to wait and locate spectrum holes before its transmission. Therefore, the extended delivery time (EDT) for the secondary user consist of both wait slots and transmission slots. We study the EDT analysis of fixed size secondary packet transmission over multiple primary channel. In particular, we introduce a birth-death based approach to model the cognitive transmission of the secondary user over multiple primary channels. We use this approach to derive the exact probability density function and probability mass function of EDT of the secondary transmission for both continuous and periodic sensing cases. We also present selected numerical and simulation results to verify our analytical approach and to illustrate the mathematical formulation. / Graduate

Abstract The aim of this thesis is to devise coordination and adaptation techniques that enable the wireless devices operating in a cognitive network to utilize their available resources efficiently. The first part of this thesis considers the case where multiple autonomous devices sense the frequency channels sequentially in some sensing order for spectrum opportunities. In particular, the first part is interested in the scenario where devices with false alarms autonomously select the sensing orders in which they visit channels, without coordination from a centralized entity. An adaptive persistent sensing order selection strategy that allows autonomous adaptations to collision-free sensing orders is proposed and evaluated. It is shown that the proposed strategy converges and maximizes cognitive network throughput compared to a random selection of sensing orders. The second part of this thesis considers the case where distributed devices interact with one another to cooperate to fulfill tasks or to improve the efficiency of network resource usage. Tools from coalition formation game theory are adopted to devise dynamic cooperative strategies for distributed devices. Dynamic coalition formation methods, are proposed for two different network scenarios: 1) Distributed devices operating in an interference channel; 2) Distributed devices performing spectrum sensing. It is observed that in distributed spectrum sensing if the devices pursue their goals selfishly then coalition formation may lead to a suboptimal equilibrium where devices, through their interactions, reach an undesirable coalition structure from a network point of view. The proposed selfish model of dynamic coalition formation is then extended to determine whether and how the coalitional behavior of devices will change if coalition formation is ''not entirely selfish''. It is observed that for the problem of distributed spectrum sensing, average throughput per device is increased when devices cooperate to maximize the overall gains of the group as compared to when they cooperate to increase their individual gains. Finally, in the last part of the thesis, to reduce spectrum sensing overhead and total energy consumption of a cognitive radio network, the problem of sensor selection is considered. Different techniques for selecting devices with the best detection performance are proposed, and it is shown that the proposed device selection methods are able to offer significant gains in terms of system performance as compared to a random selection of devices. / Tiivistelmä Tämän työn tavoitteena oli kehittää koordinointi- ja adaptointimenetelmiä, jotka mahdollistavat langattomien laitteiden toiminnan kognitiivisessa verkossa ja tarjolla olevien resurssien tehokkaan käytön. Työn ensimmäisessä osassa käsitellään tapausta, jossa useat itsenäiset laitteet havainnoivat taajuuskanavien spektriominaisuuksia sekventiaalisesti jossakin järjestyksessä. Ensimmäisessä osassa ollaan erityisesti kiinnostuneita skenaariosta, jossa virheellisen hälytyksen antava laite automaattisesti valitsee kanavien havainnointijärjestyksen, joka tapahtuu ilman keskusyksikön koordinointia. Tässä työssä ehdotetaan ja evaluoidaan adaptiivinen jatkuva havainnointijärjestyksen valintastrategia, joka sallii itsenäisen sopeutumisen törmäysvapaaseen havainnointijärjestykseen. Osoitetaan, että ehdotettu strategia suppenee ja maksimoi kognitiivisen verkon kapasiteetin verrattuna satunnaiseen havainnointijärjestysten valintaan. Työn toisessa osassa pohditaan tilannetta, jossa hajautetut laitteet vuorovaikuttavat keskenään yhteistyössä suorittaakseen tehtäviään tai parantaakseen verkon resurssien käytön tehokkuutta. Peliteoreettisia työkaluja koalitioiden muodostamiseen mukautetaan dynaamisten yhteistoiminnallisten strategioiden laatimiseen hajautetuille laitteille. Dynaamisia koalitioiden muodostamismenetelmiä ehdotetaan kahteen erilaiseen verkkoskenaarioon: 1) hajautetut laitteet toimivat häiriöllisessä kanavassa, 2) hajautetut laitteet suorittavat spektrin havainnointia. Havaitaan, että jos hajautetussa spektrin havainnoinnissa laitteet tavoittelevat päämääriään itsekkäästi, niin koalitioiden muodostaminen voi johtaa alioptimaaliseen tasapainotilaan, jossa laitteet keskinäisen vaikutuksensa kautta saavuttavat verkon näkökulmasta epätoivotun koalitiorakenteen. Ehdotettua itsekästä mallia dynaamiseen koalitioiden muodostamiseen laajennetaan ottamaan selville, miten laitteiden koalitiokäyttäytyminen muuttuu, jos koalitioiden muodostaminen ei ole täydellisen itsekästä. Havaitaan, että hajautetun spektrin havainnoinnin probleemassa, keskimääräinen laitekohtainen kapasiteetti kasvaa kun laitteet tekevät yhteistyötä maksimoidakseen ryhmän kokonaishyödyn verrattuna siihen, jos ne tekevät yhteistyötä lisätäkseen yksittäisiä etujaan. Työn viimeisessä osassa pohditaan sensorien valintaongelmaa. Siinä ehdotetaan erilaisia menetelmiä, jotka valitsevat parhaan suorituskyvyn omaavat laitteet ja näytetään, että ehdotetut laitteiden valintamenetelmät pystyvät tarjoamaan merkittäviä suorituskykyetuja verrattuna satunnaiseen laitteiden valintaan.

[pt] A tecnologia de rádio cognitivo está em pleno desenvolvimento na academia e indústria, sendo apresentada como uma solução para o reduzir o congestionamento do espectro radioelétrico. Dessa forma, diversos estudos têm sido desenvolvidos para obter novas técnicas de compartilhamento do espectro entre usuários ditos primários e secundários. Estas técnicas devem ser robustas o suficiente para minimizar as colisões de ocupação do espectro entre os usuários supracitados, quando o acesso dinâmico ao espectro for aplicado. O presente estudo investigou as soluções de ocupação compartilhada do espectro, em especial nos para serviços de voz na faixa de 450 MHz. A modelagem de ocupação dos canais, a partir de medidas de transmissões reais, permitiu o desenvolvimento de algoritmo robusto que realiza a predição de espaços espectrais (white spaces) dentro de canais destinados a usuários primários. Esse método proposto define, estatisticamente, uma janela de intervalos de tempo futuros que pode ser utilizada por usuários secundários, por apresentar maior probabilidade de possuir espaços espectrais livres, minimizando as possíveis colisões. O emprego do método proposto aumenta a vazão de informações de modo seguro e,com alto desempenho, otimizando,assim,a utilização do espectro radioelétrico. / [en] The cognitive radio technology is being developedin universities and industry as a solution to the radio spectrum scarcity. This technology willallow spectrum sharing between primary and secondary telecommunication users. The techniques employed must be robust enough to minimize spectrum occupancy collisions, when the dynamic spectrum access is applied. This study investigates the trends of spectrum usersoccupation, particularly in voice services in the 450 MHz frequency band.An users occupancy model was developed taking into accountmeasured data of real transmissions. It allowed the development of a robust algorithm that predicts spectral vacancy in channels allocated to primary users. The method selects, statistically, a group of future time intervals that can be used by secondary users, due to a higher probability of having a free spectral space. The use of this new technique minimizes possible collisions, increasing the flow of information in secure way and optimizing the radio spectrum use.

Nous proposons un nouveau schéma d’échantillonnage non uniforme périodique appelé Système d’Échantillonnage Non Uniforme en Radio Intelligente (SENURI). Notre schéma détecte la localisation spectrale des bandes actives dans la bande totale échantillonnée afin de réduire la fréquence moyenne d’échantillonnage, le nombre d’échantillons prélevé et par conséquent la consommation d’énergie au niveau du traitement numérique. La fréquence moyenne d’échantillonnage du SENURI dépend uniquement du nombre de bandes contenues dans le signal d’entrée x(t). Il est nettement plus performant, en termes d’erreur quadratique, qu’une architecture classique d’échantillonnage non uniforme périodique constituée de p branches, lorsque le spectre de x(t) change dynamiquement. / In this work we consider the problem of designing an effective sampling scheme for sparse multi-band signals. Based on previous results on periodic non-uniform sampling (Multi-Coset) and using the well known Non-Uniform Fourier Transform through Bartlett’s method for Power Spectral Density estimation, we propose a new sampling scheme named the Dynamic Single Branch Non-uniform Sampler (DSB-NUS). The idea of the proposed scheme is to reduce the average sampling frequency, the number of samples collected, and consequently the power consumption of the Analog to Digital Converter (ADC). In addition to that our proposed method detects the location of the bands in order to adapt the sampling rate. In this thesis, we show through simulation results that compared to existing multi-coset based samplers, our proposed sampler provides superior performance, both in terms of sampling rate and energy consumption. It is notconstrained by the inflexibility of hardware circuitry and is easily reconfigurable. We also show the effect of the false detection of active bands on the average sampling rate of our new adaptive non-uniform sub-Nyquist sampler scheme.

The usage of the wireless communication technologies have been increasing due to the benefits they provide in our daily life. These technologies are used in various fields such as military communication, public safety, cellular communication. The current systems might not be sufficient to meet the increasing demand. Therefore, the new solutions such as the usage of smart antennas have been proposed to satisfy this demand. Among different solutions, cognitive heterogeneous networks (HetNets) have been recently introduced as a promising one to meet the high user demand. In cognitive Hetnets, there are secondary base stations (SBSs) with secondary users (SUs) and primary base stations (PBSs) with primary users (PUs) in a given area without any coordination between SBS-SBS and SBS-PBS. Due to the physical coexistence of SBSs and the lack of available spectrum, interference caused by the SBSs becomes a significant issue. Therefore, there is a need for the techniques that allow users to share the same spectrum while maintaining the required performance level for each user by adopting interference mitigation techniques. In this dissertation, we focus on resource allocation, interference coordination/mitigation and channel control techniques in 4G and beyond systems. As resource allocation techniques, we propose two studies. In the first study, we present the random subcarrier selection algorithm which is that each SU selects a specific number of subcarriers determined by its needs. In comparison where, at each iteration of the game, the SU searches all the subcarriers to maximize its payof, our algorithm is based on selecting the subcarriers randomly and checks only those subcarriers that achieve higher payof. In the second study, we utilize the reconfigurable antennas (RAs) which allows wireless devices to alter their antenna states determined by different radiation patterns to maximize received signal strength, and present the joint subcarrier and antenna state selection algorithm. SU selects the subcarriers whose capacity values are the highest among the available ones. Since SUs employ RAs, i.e., multiple antenna states, they obtain the reports for all subcarriers from each antenna states, and select the state with the subcarriers which provide the highest capacity gain. As interference coordination/mitigation technique, we propose a game theoretical partially overlapping filtered multitone (POFMT) scheme. Partially overlapping is performed in both frequency and space domains. While intentional carrier frequency shift is introduced in frequency, RAs are utilized to achieve partially overlapping in space domain. Within a game theoretical framework, when SUs search for the frequency shift ratio, they also select the antenna state to increase the system utility. We also combine the resource allocation technique with POTs and present the game theoretical resource allocation with POFMT. To achieve the resource allocation, an SBS slides a group of consecutive subcarriers through all available ones and computes the utility for each selected subcarriers. It picks the consecutive ones which give the highest capacity result. Our results show that our algorithms reach Nash equilibrium and increase the system gain substantially in terms of the corresponding utility. As channel control technique, we propose a wireless channel control using spatially adaptive antenna arrays. This technique simultaneously utilizes beam-steering and spatial adaptation to enhance the wireless channel gain and system capacity. While the interference is reduced via beam-steering feature of proposed antenna, the wireless channel can be controlled by spatially moving the antenna in one axis. Simulated realized gain patterns at various array positions and phase shifter states are subsequently utilized in link and system level simulations to demonstrate the advantages of the proposed concept. It is shown that the system gain can be increased with the spatial adaptation capability of the antenna.

A compact, frequency-reconfigurable filtenna with sharp out-of-band rejection in both its wideband and continuously tunable narrowband states is presented. It is intended for use in cognitive radio applications. The wideband state is the sensing state and operationally covers 2.35-4.98 GHz. The narrowband states are intended to cover communications within the 3.05-4.39 GHz range, which completely covers the Worldwide Interoperability for Microwave Access (WiMAX) band and the satellite communications C-band. A p-i-n diode is employed to switch between these wide and narrowband operational states. Two varactor diodes are used to shift the operational frequencies continuously among the narrowband states. The filtenna consists of a funnel-shaped monopole augmented with a reconfigurable filter; it has a compact electrical size: 0.235 lambda(L) x 0.392 lambda(L), where the wavelength lambda(L) corresponds to the lower bound of its operational frequencies. The measured reflection coefficients, radiation patterns, and realized gains for both operational states are in good agreement with their simulated values.

La thèse aborde le problème de la détection d’un signal dans une bande de fréquences donnée sans aucune connaissance à priori sur la source (détection aveugle) dans le contexte de la radio intelligente. Le détecteur proposé dans la thèse est basé sur l’estimation des valeurs propres de la matrice de corrélation du signal reçu. A partir de ces valeurs propres, plusieurs critères ont été développés théoriquement (Standard Condition Number, Scaled Largest Eigenvalue, Largest Eigenvalue) en prenant pour hypothèse majeure un nombre fini d’éléments, contrairement aux hypothèses courantes de la théorie des matrices aléatoires qui considère un comportement asymptotique de ces critères. Les paramètres clés des détecteurs ont été formulés mathématiquement (probabilité de fausse alarme, densité de probabilité) et une correspondance avec la densité GEV a été explicitée. Enfin, ce travail a été étendu au cas multi-antennes (MIMO) pour les détecteurs SLE et SCN. / In Cognitive Radio, Spectrum Sensing (SS) is the task of obtaining awareness about the spectrum usage. Mainly it concerns two scenarios of detection: (i) detecting the absence of the Primary User (PU) in a licensed spectrum in order to use it and (ii) detecting the presence of the PU to avoid interference. Several SS techniques were proposed in the literature. Among these, Eigenvalue Based Detector (EBD) has been proposed as a precious totally-blind detector that exploits the spacial diversity, overcome noise uncertainty challenges and performs adequately even in low SNR conditions. The first part of this study concerns the Standard Condition Number (SCN) detector and the Scaled Largest Eigenvalue (SLE) detector. We derived exact expressions for the Probability Density Function (PDF) and the Cumulative Distribution Function (CDF) of the SCN using results from finite Random Matrix Theory; In addition, we derived exact expressions for the moments of the SCN and we proposed a new approximation based on the Generalized Extreme Value (GEV) distribution. Moreover, using results from the asymptotic RMT we further provided a simple forms for the central moments of the SCN and we end up with a simple and accurate expression for the CDF, PDF, Probability of False-Alarm, Probability of Detection, of Miss-Detection and the decision threshold that could be computed and hence provide a dynamic SCN detector that could dynamically change the threshold value depending on target performance and environmental conditions. The second part of this study concerns the massive MIMO technology and how to exploit the large number of antennas for SS and CRs. Two antenna exploitation scenarios are studied: (i) Full antenna exploitation and (ii) Partial antenna exploitation in which we have two options: (i) Fixed use or (ii) Dynamic use of the antennas. We considered the Largest Eigenvalue (LE) detector if noise power is perfectly known and the SCN and SLE detectors when noise uncertainty exists.

The aggregate interference distribution in cognitive radio networks is studied in a rigorous and analytical way using the popular Poisson point process model. While a number of results are available for this model for non-cognitive radio networks, cognitive radio networks present extra levels of difficulties for the analysis, mainly due to the exclusion region around the primary receiver, which are typically addressed via various ad-hoc approximations (e.g., based on the interference cumulants) or via the large-deviation analysis. Unlike the previous studies, we do not use here ad-hoc approximations but rather obtain the asymptotic interference distribution in a systematic and rigorous way, which also has a guaranteed level of accuracy at the distribution tail. This is in contrast to the large deviation analysis, which provides only the (exponential) order of scaling but not the outage probability itself. Unlike the cumulant-based analysis, our approach provides a guaranteed level of accuracy at the distribution tail. Additionally, our analysis provides a number of novel insights. In particular, we demonstrate that there is a critical transition point below which the outage probability decays only polynomially but above which it decays super-exponentially. This provides a solid analytical foundation to the earlier empirical observations in the literature and also reveals what are the typical ways outage events occur in different regimes. The analysis is further extended to include interference cancelation and fading (from a broad class of distributions). The outage probability is shown to scale down exponentially in the number of canceled nearest interferers in the below-critical region and does not change significantly in the above-critical one. The proposed asymptotic expressions are shown to be accurate in the non-asymptotic regimes as well.