The popularity of ubiquitous Internet services has spurred the fast growth of wireless communications by launching data hungry multimedia applications to mobile devices. Powered by spectrum agile cognitive radios, the newly emerged cognitive radio networks (CRN) are proposed to provision the efficient spectrum reuse to improve spectrum utilization. Unlicensed users in CRN, or secondary users (SUs), access the temporarily idle channels in a secondary and opportunistic fashion while preventing harmful interference to licensed primary users (PUs). To effectively detect and exploit the spectrum access opportunities released from a wide spectrum, the heterogeneous wireless channel characteristics and the underlying prioritized spectrum reuse features need to be considered in the protocol design and resource management schemes in CRN, which plays a critical role in unlicensed spectrum sharing among multiple users. The purpose of this dissertation is to address the challenges of utilizing heterogeneous wireless channels in CRN by its intrinsic dynamic and diverse natures, and build the efficient, scalable and, more importantly, practical dynamic spectrum access mechanisms to enable the cost-effective transmissions for unlicensed users. Note that the spectrum access opportunities exhibit the diversity in the time/frequency/space domain, secondary transmission schemes typically follow three design principles including 1) utilizing local free channels within short transmission range, 2) cooperative and opportunistic transmissions, and 3) effectively coordinating transmissions in varying bandwidth. The entire research work in this dissertation casts a systematic view to address these principles in the design of the routing protocols, medium access control (MAC) protocols and radio resource management schemes in CRN. Specifically, as spectrum access opportunities usually have small spatial footprints, SUs only communicate with the nearby nodes in a small area. Thus, multi-hop transmissions in CRN are considered in this dissertation to enable the connections between any unlicensed users in the network. CRN typically consist of intermittent links of varying bandwidth so that the decision of routing is closely related with the spectrum sensing and sharing operations in the lower layers. An efficient opportunistic cognitive routing (OCR) scheme is proposed in which the forwarding decision at each hop is made by jointly considering physical characteristics of spectrum bands and diverse activities of PUs in each single band. Such discussion on spectrum aware routing continues coupled with the sensing selection and contention among multiple relay candidates in a multi-channel multi-hop scenario. An SU selects the next hop relay and the working channel based upon location information and channel usage statistics with instant link quality feedbacks. By evaluating the performance of the routing protocol and the joint channel and route selection algorithm with extensive simulations, we determine the optimal channel and relay combination with reduced searching complexity and improved spectrum utilization. Besides, we investigate the medium access control (MAC) protocol design in support of multimedia applications in CRN. To satisfy the quality of service (QoS) requirements of heterogeneous applications for SUs, such as voice, video, and data, channels are selected to probe for appropriate spectrum opportunities based on the characteristics and QoS demands of the traffic along with the statistics of channel usage patterns. We propose a QoS-aware MAC protocol for multi-channel single hop scenario where each single SU distributedly determines a set of channels for sensing and data transmission to satisfy QoS requirements. By analytical model and simulations, we determine the service differentiation parameters to provision multiple levels of QoS. We further extend our discussion of dynamic resource management to a more practical deployment case. We apply the experiences and skills learnt from cognitive radio study to cellular communications. In heterogeneous cellular networks, small cells are deployed in macrocells to enhance link quality, extend network coverage and offload traffic. As different cells focus on their own operation utilities, the optimization of the total system performance can be analogue to the game between PUs and SUs in CRN. However, there are unique challenges and operation features in such case. We first present challenging issues including interference management, network coordination, and interworking between cells in a tiered cellular infrastructure. We then propose an adaptive resource management framework to improve spectrum utilization and mitigate the co-channel interference between macrocells and small cells. A game-theory-based approach is introduced to handle power control issues under constrained control bandwidth and limited end user capability. The inter-cell interference is mitigated based upon orthogonal transmissions and strict protection for macrocell users. The research results in the dissertation can provide insightful lights on flexible network deployment and dynamic spectrum access for prioritized spectrum reuse in modern wireless systems. The protocols and algorithms developed in each topic, respectively, have shown practical and efficient solutions to build and optimize CRN.

Wireless communication is facing an increasingly severe spectrum scarcity problem. Hybrid free space optical (FSO)/ millimetre wavelength (MMW) radio frequency (RF) systems and cognitive radios are two candidate solutions. Hybrid FSO/RF can achieve high data rate transmission for wireless back haul. Cognitive radio transceivers can opportunistically access the underutilized spectrum resource of existing systems for new wireless services. In this work we carry out accurate performance analysis on these two transmission techniques. In particular, we present and analyze a switching based transmission scheme for a hybrid FSO/RF system. Specifically, either the FSO or RF link will be active at a certain time instance, with the FSO link enjoying a higher priority. We consider both a single threshold case and a dual threshold case for FSO link operation. Analytical expressions are obtained for the outage probability, average bit error rate and ergodic capacity for the resulting system. We also investigate the delay performance of secondary cognitive transmission with interweave implementation. We first derive the exact statistics of the extended delivery time, that includes both transmission time and waiting time, for a fixed-size secondary packet. Both work-preserving strategy (i.e. interrupted packets will resume transmission from where interrupted) and non-work-preserving strategy (i.e. interrupted packets will be retransmitted) are considered with various sensing schemes. Finally, we consider a M/G/1 queue set-up at the secondary user and derive the closed-form expressions for the expected delay with Poisson traffic. The analytical results will greatly facilitate the design of the secondary system for particular target application. / Graduate

The rapid increasing interest in wireless communication has led to the continuous development of wireless devices and technologies. The modern convergence and interoperability of wireless technologies has further increased the amount of services that can be provided, leading to the substantial demand for access to the radio frequency spectrum in an efficient manner. Cognitive radio (CR) an innovative concept of reusing licensed spectrum in an opportunistic manner promises to overcome the evident spectrum underutilization caused by the inflexible spectrum allocation. Spectrum sensing in an unswerving and proficient manner is essential to CR. Cooperation amongst spectrum sensing devices are vital when CR systems are experiencing deep shadowing and in a fading environment. In this thesis, cooperative spectrum sensing (CSS) schemes have been designed to optimize detection performance in an efficient and implementable manner taking into consideration: diversity performance, detection accuracy, low complexity, and reporting channel bandwidth reduction. The thesis first investigates state of the art spectrums sensing algorithms in CR. Comparative analysis and simulation results highlights the different pros, cons and performance criteria of a practical CSS scheme leading to the problem formulation of the thesis. Motivated by the problem of diversity performance in a CR network, the thesis then focuses on designing a novel relay based CSS architecture for CR. A major cooperative transmission protocol with low complexity and overhead - Amplify and Forward (AF) cooperative protocol and an improved double energy detection scheme in a single relay and multiple cognitive relay networks are designed. Simulation results demonstrated that the developed algorithm is capable of reducing the error of missed detection and improving detection probability of a primary user (PU). To improve spectrum sensing reliability while increasing agility, a CSS scheme based on evidence theory is next considered in this thesis. This focuses on a data fusion combination rule. The combination of conflicting evidences from secondary users (SUs) with the classical Dempster Shafter (DS) theory rule may produce counter-intuitive results when combining SUs sensing data leading to poor CSS performance. In order to overcome and minimise the effect of the counter-intuitive results, and to enhance performance of the CSS system, a novel state of the art evidence based decision fusion scheme is developed. The proposed approach is based on the credibility of evidence and a dissociability degree measure of the SUs sensing data evidence. Simulation results illustrate the proposed scheme improves detection performance and reduces error probability when compared to other related evidence based schemes under robust practcial scenarios. Finally, motivated by the need for a low complexity and minmum bandwidth reporting channels which can be significant in high data rate applications, novel CSS quantization schemes are proposed. Quantization methods are considered for a maximum likelihood estimation (MLE) and an evidence based CSS scheme. For the MLE based CSS, a novel uniform and optimal output entropy quantization scheme is proposed to provide fewer overhead complexities and improved throughput. While for the Evidence based CSS scheme, a scheme that quantizes the basic probability Assignment (BPA) data at each SU before being sent to the FC is designed. The proposed scheme takes into consideration the characteristics of the hypothesis distribution under diverse signal-to-noise ratio (SNR) of the PU signal based on the optimal output entropy. Simulation results demonstrate that the proposed quantization CSS scheme improves sensing performance with minimum number of quantized bits when compared to other related approaches.

To solve the spectrum scarcity problem caused by the high number of wireless applications and users, the concept of cognitive radio (CR) was proposed in the past few years. Cognitive radio networks (CRNs) provide dynamic spectrum access (DSA), where the unlicensed users can access the spectrum without causing unacceptable level of interference to the primary user (PU). DSA was based on conventional spectrum sensing information or geolocation databases. Later, radio environment map (REM) as an improved geolocation database was introduced to enhance the DSA process. It is a comprehensive map consists of different integrated databases, and the interference field information is one of its databases. In this thesis, a description of the REM concept and its construction methods will be presented. The focus will be for the indirect methods for constructing interference map, which represents a layer of the REM. Indirect method refers to the methods that utilize known model information, to first estimate the primary transmitter parameters and then generate REM. Two indirect methods under lognormal shadowing were presented and compared. The better of these two methods is further investigated in different scenarios. These scenarios include different number of sensors, varied size of measurements, several shadowing spread values, different percentages of error in path-loss exponent, and the effect of the number of moving sensors and their speeds to the REM quality. The performance is evaluated using these metrics: “localization error, signal power error and correct detection zone ratio (CDZR). The results show that performance is enhanced as the number of sensors and the size of measurements increase, whereas clear degradation in REM quality is shown when shadowing spread increases or the model parameters are not well calibrated. Also, as the number of moving sensors or their speeds increase, the REM performance becomes less effective

The continuing increase in the adoption and use of wireless technology aggravates the problem of spectrum scarcity due to the way we utilize the spectrum. The radio spectrum is a limited resource regulated by governmental agencies according to a fixed spectrum assignment policy. However, many studies show that this fixed radio frequency allocation leads to significant underutilization of the radio spectrum creating artificial scarcity, as most of the allocated spectrum is not used all of the time in every location. To meet services growing demands, efficient use of the spectrum is essential. Therefore, there is a need to estimate the radio spectrum utilization in several locations and during different periods of time in order to opportunistically exploit the existing wireless spectrum. Cognitive radio technology aims to search for those portions of the radio spectrum that are assigned to a specific service, but are unused during a specific time and at specific location in order to share these white spaces and thus to reduce the radio spectrum inefficiency. In this thesis, we study spectrum utilization in the frequency range from 790MHz to 925MHz. The spectrum sensing has been realized using a number of specialized microcontroller based white space sensors which utilize energy detection, situated in different locations of a building in Kista, Sweden. The occupancy of the frequency bands in this chunk of the spectrum is quantified as the fraction of samples with a power level greater than a threshold. The results from these spectrum measurements show that a significant amount of spectrum in this scanned range around the building is inefficiently used all the time. / Den senaste tidens ökning av trådlös teknik förvärrar problemet med spektrumbrist på grund av hur vi använder den. Det radiospektrum är en begränsad resurs som regleras av statliga myndigheter enligt en fast spektrumtilldelningen politik. Men många studier visar att den fasta frekvensplan leder till betydande underutnyttjande av radiospektrum och skapar en konstgjord brist eftersom de flesta av de tilldelade spektrumet inte används hela tiden i varje platsen. För att uppfylla tjänster ökade krav, är viktigt en effektiv användning av spektrumet. Därför finns det ett behov av att uppskatta användningen av radiospektrum i flera platser och i olika tidsperioder för att kunna utnyttja den befintliga trådlösa spektrumet i opportunistiskt sätt. Kognitiv radio teknologi syftar till att söka efter dessa delar av radiospektrum som tilldelas till en konkret tjänst och är oanvända i en viss tid och på viss plats för att dela dessa vita ytor och därför lösa radio spektrum ineffektivitet problem. I denna uppsats studerar vi spektrumanvändning i frekvensområdet från 790 MHz till 925 MHz. Spektrat avkänning har utförts med hjälp av ett antal specialiserade mikrokontroller blanktecken sensorer vilka utnyttjar energin upptäckt, som ligger på olika platser i en byggnad i Kista, Sverige. Uthyrningsgraden av frekvensbanden i denna del av spektrumet kvantifieras som antalet prover med en effektnivå överstiger en tröskel. Resultaten från spektrat mätningarna visar att en betydande del av spektrumet i denna scannade intervall ineffektivt används hela tiden.

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Dynamic spectrum access enabled by cognitive radio networks are envisioned to drive the next generation wireless networks that can increase spectrum utility by opportunistically accessing unused spectrum. Due to the policy constraint that there could be no interference to the primary (licensed) users, secondary cognitive radios have to continuously sense for primary transmissions. Typically, sensing reports from multiple cognitive radios are fused as stand-alone observations are prone to errors due to wireless channel characteristics. Such dependence on cooperative spectrum sensing is vulnerable to attacks such as Secondary Spectrum Data Falsification (SSDF) attacks when multiple malicious or selfish radios falsify the spectrum reports. Hence, there is a need to quantify the trustworthiness of radios that share spectrum sensing reports and devise malicious node identification and robust fusion schemes that would lead to correct inference about spectrum usage. In this work, we propose an anomaly monitoring technique that can effectively capture anomalies in the spectrum sensing reports shared by individual cognitive radios during cooperative spectrum sensing in a multi-channel distributed network. Such anomalies are used as evidence to compute the trustworthiness of a radio by its neighbours. The proposed anomaly monitoring technique works for any density of malicious nodes and for any physical environment. We propose an optimistic trust heuristic for a system with a normal risk attitude and show that it can be approximated as a beta distribution. For a more conservative system, we propose a multinomial Dirichlet distribution based conservative trust framework, where Josang*s Belief model is used to resolve any uncertainty in information that might arise during anomaly monitoring. Using a machine learning approach, we identify malicious nodes with a high degree of certainty regardless of their aggressiveness and variations introduced by the pathloss environment. We also propose extensions to the anomaly monitoring technique that facilitate learning about strategies employed by malicious nodes and also utilize the misleading information they provide. We also devise strategies to defend against a collaborative SSDF attack that is launched by a coalition of selfish nodes. Since, defense against such collaborative attacks is difficult with popularly used voting based inference models or node centric isolation techniques, we propose a channel centric Bayesian inference approach that indicates how much the collective decision on a channels occupancy inference can be trusted. Based on the measured observations over time, we estimate the parameters of the hypothesis of anomalous and non-anomalous events using a multinomial Bayesian based inference. We quantitatively define the trustworthiness of a channel inference as the difference between the posterior beliefs associated with anomalous and non-anomalous events. The posterior beliefs are updated based on a weighted average of the prior information on the belief itself and the recently observed data. Subsequently, we propose robust fusion models which utilize the trusts of the nodes to improve the accuracy of the cooperative spectrum sensing decisions. In particular, we propose three fusion models: (i) optimistic trust based fusion, (ii) conservative trust based fusion, and (iii) inversion based fusion. The former two approaches exclude untrustworthy sensing reports for fusion, while the last approach utilizes misleading information. All schemes are analyzed under various attack strategies. We propose an asymmetric weighted moving average based trust management scheme that quickly identifies on-off SSDF attacks and prevents quick trust redemption when such nodes revert back to temporal honest behavior. We also provide insights on what attack strategies are more effective from the adversaries* perspective. Through extensive simulation experiments we show that the trust models are effective in identifying malicious nodes with a high degree of certainty under variety of network and radio conditions. We show high true negative detection rates even when multiple malicious nodes launch collaborative attacks which is an improvement over existing voting based exclusion and entropy divergence techniques. We also show that we are able to improve the accuracy of fusion decisions compared to other popular fusion techniques. Trust based fusion schemes show worst case decision error rates of 5% while inversion based fusion show 4% as opposed majority voting schemes that have 18% error rate. We also show that the proposed channel centric Bayesian inference based trust model is able to distinguish between attacked and non-attacked channels for both static and dynamic collaborative attacks. We are also able to show that attacked channels have significantly lower trust values than channels that are not– a metric that can be used by nodes to rank the quality of inference on channels.

With the reality that diverse air interfaces and dissimilar access networks coexist, accompanied by the trend that dynamic spectrum access (DSA) is allowed and will be gradually employed, cognition and cooperation form a promising framework to achieve the ideality of seamless ubiquitous connectivity in future communication networks. In this dissertation, the cognitive gateway (CG), conceived as a special cognitive radio (CR) node, is proposed and designed to facilitate universal interoperability among incompatible waveforms. A proof-of-concept prototype is built and tested. Located in places where various communication nodes and diverse access networks coexist, the CG can be easily set up and works like a network server with differentiated service (Diffserv) architecture to provide automatic traffic relaying and link establishment. The author extracts a scalable '“source-CG-destination“ snapshot from the entire network and investigates the key enabling technologies for such a snapshot. The CG features provide universal interoperability, which is enabled by a generic waveform representation format and the reconfigurable software defined radio platform. According to the trend of an all IP-based solution for future communication systems, the term “waveform“ in this dissertation has been defined as a protocol stack specification suite. The author gives a generic waveform representation format based on the five-layer TCP/IP protocol stack architecture. This format can represent the waveforms used by Ethernet, WiFi, cellular system, P25, cognitive radios etc. A significant advantage of CG over other interoperability solutions lies in its autonomy, which is supported by appropriate signaling processes and automatic waveform identification. The service process in a CG is usually initiated by the users who send requests via their own waveforms. These requests are transmitted during the signaling procedures. The complete operating procedure of a CG is depicted as a waveform-oriented cognition loop, which is primarily executed by the waveform identifier, scenario analyzer, central controller, and waveform converter together. The author details the service process initialized by a primary user (e.g. legacy public safety radio) and that initialized by a secondary user (e.g. CR), and describes the signaling procedures between CG and clients for the accomplishment of CG discovery, user registration and un-registration, link establishment, communication resumption, service termination, route discovery, etc. From the waveforms conveyed during the signaling procedures, the waveform identifier extracts the parameters that can be used for a CG to identify the source waveform and the destination waveform. These parameters are called “waveform indicators.“ The author analyzes the four types of waveforms of interest and outlines the waveform indicators for different types of communication initiators. In particular, a multi-layer waveform identifier is designed for a CG to extract the waveform indicators from the signaling messages. For the physical layer signal recognition, a Universal Classification Synchronization (UCS) system has been invented. UCS is conceived as a self-contained system which can detect, classify, synchronize with a received signal and provide all parameters needed for physical layer demodulation without prior information from the transmitter. Currently, it can accommodate the modulations including AM, FM, FSK, MPSK, QAM and OFDM. The design and implementation details of a UCS have been presented. The designed system has been verified by over-the-air (OTA) experiments and its performance has been evaluated by theoretical analysis and software simulation. UCS can be ported to different platforms and can be applied for various scenarios. An underlying assumption for UCS is that the target signal is transmitted continually. However, it is not the case for a CG since the detection objects of a CG are signaling messages. In order to ensure higher recognition accuracy, signaling efficiency, and lower signaling overhead, the author addresses the key issues for signaling scheme design and their dependence on waveform identification strategy. In a CG, waveform transformation (WT) is the last step of the link establishment process. The resources required for transformation of waveform pairs, together with the application priority, constitute the major factors that determine the link control and scheduling scheme in a CG. The author sorts different WT into five categories and describes the details of implementing the four typical types of WT (including physical layer analog – analog gateway, up to link layer digital – digital gateway, up-to-network-layer digital gateway, and Voice over IP (VoIP) – an up to transport layer gateway) in a practical CG prototype. The issues that include resource management and link scheduling have also been addressed. This dissertation presents a CG prototype implemented on the basis of GNU Radio plus multiple USRPs. In particular, the service process of a CG is modeled as a two-stage tandem queue, where the waveform identifier queues at the first stage can be described as M/D/1/1 models and the waveform converter queue at the second stage can be described as G/M/K/K model. Based on these models, the author derives the theoretical block probability and throughput of a CG. Although the “source-CG-destination” snapshot considers only neighboring nodes which are one-hop away from the CG, it is scalable to form larger networks. CG can work in either ad-hoc or infrastructure mode. Utilizing its capabilities, CG nodes can be placed in different network architectures/topologies to provide auxiliary connectivity. Multi-hop cooperative relaying via CGs will be an interesting research topic deserving further investigation. / Ph. D.

Radio spectrum has become increasingly scarce due to the proliferation of new wireless communication services. This problem has been exacerbated by fixed bandwidth licensing policies that often lead to spectral underutilization. Cognitive radio networks (CRN) can address this issue using flexible spectrum management that permits unlicensed (secondary) users to access the licensed spectrum. Supporting real-time quality-of-service (QoS) in CRNs however, is very challenging, due to the random spectrum availability induced by the licensed (primary) user activity. This thesis considers the problem of real-time voice transmission in CRNs with an emphasis on secondary network ``friendliness''. Friendliness is measured by the secondary real-time voice capacity, defined as the number of connections that can be supported, subject to typical QoS constraints. The constant bit rate (CBR) air interface case is first assumed. An offline scheduler that maximizes friendliness is derived using an integer linear program (ILP) that can be solved using a minimum cost flow graph construction. Two online primary scheduling algorithms are then introduced. The first algorithm is based on shaping the primary spectral hole patterns subject to primary QoS constraints. The second applies real-time scheduling to both primary traffic and virtual secondary calls. The online scheduling algorithms are found to perform well compared to the friendliness upper bound. Extensive simulations of the primary friendly schedulers show the achievable secondary voice capacity for a variety of parameters compared to non-friendly primary scheduling. The thesis then considers the variable bit rate (VBR) air interface option for primary transmissions. Offline and online approaches are taken to generate a primary VBR traffic schedule that is friendly to secondary voice calls. The online VBR schedulers are found to perform well compared to the friendliness upper bound. Simulation results are presented that show the effect of the primary traffic load and primary network delay tolerance on the primary network friendliness level towards potential secondary voice traffic. Finally, secondary user friendliness is considered from an infrastructure deployment point of view. A cooperative framework is proposed, which allows the primary traffic to be relayed by helper nodes using decode-and-forward (DF) relaying. This approach decreases the primary traffic channel utilization, which, in turn, increases the capacity available to potential secondary users. A relay selection optimization problem is first formulated that minimizes the primary channel utilization. A greedy algorithm that assigns relay nodes to primary data flows is introduced and found to perform well compared to the optimum bound. Results are presented that show the primary network friendliness for different levels of primary channel utilization. / Dissertation / Doctor of Philosophy (PhD)

Fueled by the rapid advancement in digital and wireless technologies, the ever-increasing capabilities of wireless devices have placed upon us a tremendous challenge - how to put all of this capability to effective use. Individually, wireless devices have outpaced the ability of users to optimally configure them. Collectively, the complexity is far more daunting. Research in cognitive networks seeks to provide a solution to the diffculty of effectively using the expanding capabilities of wireless networks by embedding greater degrees of intelligence within the network itself. In this dissertation, we address some fundamental questions related to cognitive networks, such as "What is a cognitive network?" and "What methods may be used to design a cognitive network?" We relate cognitive networks to a common artificial intelligence (AI) framework, the multi-agent system (MAS). We also discuss the key elements of learning and reasoning, with the ability to learn being the primary differentiator for a cognitive network. Having discussed some of the fundamentals, we proceed to further illustrate the cognitive networking principle by applying it to two problems: multichannel topology control for dynamic spectrum access (DSA) and routing in a mobile ad hoc network (MANET). The multichannel topology control problem involves confguring secondary network parameters to minimize the probability that the secondary network will cause an outage to a primary user in the future. This requires the secondary network to estimate an outage potential map, essentially a spatial map of predicted primary user density, which must be learned using prior observations of spectral occupancy made by secondary nodes. Due to the complexity of the objective function, we provide a suboptimal heuristic and compare its performance against heuristics targeting power-based and interference-based topology control objectives. We also develop a genetic algorithm to provide reference solutions since obtaining optimal solutions is impractical. We show how our approach to this problem qualifies as a cognitive network. In presenting our second application, we address the role of network state observations in cognitive networking. Essentially, we need a way to quantify how much information is needed regarding the state of the network to achieve a desired level of performance. This question is applicable to networking in general, but becomes increasingly important in the cognitive network context because of the potential volume of information that may be desired for decision-making. In this case, the application is routing in MANETs. Current MANET routing protocols are largely adapted from routing algorithms developed for wired networks. Although optimal routing in wired networks is grounded in dynamic programming, the critical assumption, static link costs and states, that enables the use of dynamic programming for wired networks need not apply to MANETs. We present a link-level model of a MANET, which models the network as a stochastically varying graph that possesses the Markov property. We present the Markov decision process as the appropriate framework for computing optimal routing policies for such networks. We then proceed to analyze the relationship between optimal policy and link state information as a function of minimum distance from the forwarding node. The applications that we focus on are quite different, both in their models as well as their objectives. This difference is intentional and signficant because it disassociates the technology, i.e. cognitive networks, from the application of the technology. As a consequence, the versatility of the cognitive networks concept is demonstrated. Simultaneously, we are able to address two open problems and provide useful results, as well as new perspective, on both multichannel topology control and MANET routing. This material is posted here with permission from the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Virginia Tech library's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this material, you agree to all provisions of the copyright laws protecting it. / Ph. D.