Cognitive Radio (CR) capitalizes advances in signal processing and radio technology and is capable of reconfiguring RF and switching to desired frequency bands. It is a frequency-agile data communication device that is vastly more powerful than existing multi-channel multi-radio (MC-MR) technology. In this thesis, we investigate the important problem of multi-hop networking with CR nodes. In a CR network, each node has a set of frequency bands (not necessarily of equal size) that may not be the same as those at other nodes. The uneven size of frequency bands prompts the need of further division into sub-bands for optimal spectrum sharing. We characterize behaviors and constraints for such multi-hop CR network from multiple layers, including modeling of spectrum sharing and sub-band division, scheduling and interference constraints, and flow routing. We give a formal mathematical formulation with the objective of maximizing the network throughput for a set of user communication sessions. Since such problem formulation falls into mixed integer non-linear programming (MINLP), which is NP-hard in general, we develop a lower bound for the objective by relaxing the integer variables and linearization. Subsequently, we develop a nearoptimal algorithm to this MINLP problem. This algorithm is based on a novel sequential fixing (SF) procedure, where the integer variables are determined iteratively via a sequence of linear program (LP). In order to implement and evaluate these algorithms in a controlled laboratory setting, we design and implement an emulation testbed. The highlights of our experimental research include: • Emulation of a multi-hop CR network with arbitrary topology; • An implementation of the proposed SF algorithm at the application layer; • A source routing implementation that can easily support comparative study between SF algorithm and other schemes; • Experiments comparing the SF algorithm with another algorithm called Layered Greedy Algorithm (LGA); • Experimental results show that the proposed SF significantly outperforms LGA. In summary, the experimental research in this thesis has demonstrated that SF algorithm is a viable algorithm for optimal spectrum sharing in multi-hop CR networks. / Master of Science

As wireless communication mediums develop and Dynamic Spectrum Access (DSA) is implemented as a means to increase capacity on a limited spectrum, the threat of reactive interference becomes real. The motivation for this thesis is to address this problem by suggesting a mechanism which could be used in these spectrally harsh DSA environments. Overcoming certain types of interference in DSA environments requires unique approaches to transmitting and receiving data. This thesis discusses a decoy-based approach to mitigate conditions in which interference reacts to the spectral movement of the transmitting DSA radio as it hops around the frequency spectrum. Specifically using a polyphase channelizer, multiple replicas of the information signal are simultaneously transmitted at separate frequencies to lure reactive interference away from the main source of transmission. Using either serial or parallel transmission (splitting the signal in time or splitting the signal's energy) with the decoy signals and the original signal can either maximize data throughput in a minimal-interference environment or can add necessary robustness in the presence of multiple sources of reactive interference. This decoy-based approach is verified with network simulation. An event-based simulator written in C++ was used to define the capacity or maximum throughput. Configuration files loaded with the necessary presets are used to run three network simulation scenarios: First Responder, Military Patrol, and Airborne Network. / Master of Science

Cognitive radios have applied various forms of artificial intelligence (AI) to wireless systems in order to solve the complex problems presented by proper link management, network traffic balance, and system efficiency. Casebased reasoning (CBR) has seen attention as a prospective avenue for storing and organizing past information in order to allow the cognitive engine to learn from previous experience. CBR uses past information and observed outcomes to form empirical relationships that may be difficult to model apriori. As wireless systems become more complex and more tightly time constrained, scalability becomes an apparent concern to store large amounts of information over multiple dimensions. This thesis presents a renewed look at an abstract application of CBR to CR. By appropriately designing a case structure with useful information both to the cognitive entity as well as the underlying similarity relationships between cases, an accurate problem description can be developed and indexed. By separating the components of a case from the parameters that are meaningful to similarity, the situation can be quickly identified and queried given proper design. A data structure with this in mind is presented that orders cases in terms of general placement in Euclidean space, but does not require the discrete calculation of distance between the query case and all cases stored. By grouping possible similarity dimension values into distinct partitions called "similarity buckets", a data structure is developed with constant (O(1)) access time, which is an improvement of several orders of magnitude over traditional linear approaches (O(n)). / Master of Science

Development of Cognitive Radio (CR) applications, which rely on a radio's ability to adapt intelligently to it's spectral surroundings will soon make the all important technological jump from research interest to systems integration, as demand for highly adaptive wireless applications expand. VT-CORNET (Virginia Tech – Cognitive Radio Network Testbed) is a unique testbed concept, designed to facilitate this technology leap by offering researchers — both local and remote — the opportunity to conduct CR experiments on an installed infrastructure of highly flexible radio nodes. These nodes — 48 in total — are distributed throughout four floors of a building on the Virginia Tech campus, and provide researchers with diverse options in terms of channel conditions and deployment scenarios. The radios themselves consist of the widely used USRP2 Software Defined Radio (SDR) platform, coupled to a centrally located cluster of rack servers — which provide a high performance GPP environment for real-time software based signal processing. VT-CORNET is specially licensed to operate our low-power nodes over a broad range of frequencies, which provides researcher the opportunity to conduct experiments on live spectrum — in the presence of real primary users. Testbeds are a widely used tool in the wireless and networking fields, and VT-CORNET expands the concept through a focus on CR research and education. This thesis describes the construction and deployment of the CORNET testbed in detail. Specific contributions made to the testbed include the design and implementation of the management network, as well as the initial deployment of the SDR nodes in the ceiling. In addition, this thesis describes the administration and management of the CORNET GPP cluster, and provides a instructions for the basic usage of CORNET from an administrative and user perspective. Finally, this thesis describes a number of custom SDR waveforms implemented on CORNET which demonstrate the utility of the testbed for cognitive radio applications. / Master of Science

No / Eigenvalue based spectrum sensing schemes such as Maximum Minimum Eigenvalue (MME), Maximum Energy Detection (MED) and Energy with Minimum Eigenvalue (EME) have higher spectrum sensing performance without requiring any prior knowledge of Primary User (PU) signal but the decision hypothesis used in these eigenvalue based sensing schemes depends on the calculation of maximum eigenvalue from covariance matrix of measured signal. Calculation of the covariance matrix followed by eigenspace analysis of the covariance matrix is a resource intensive operation and takes overhead time during critical process of spectrum sensing. In this paper we propose a new blind spectrum sensing scheme based on the approximation of the maximum eigenvalue using state of the art results from Random Matrix Theory (RMT). The proposed sensing scheme has been evaluated through extensive simulations on wireless microphone signals and the proposed scheme shows higher probability of detection (Pd) performance. The proposed spectrum sensing also shows higher detection performance as compared to energy detection scheme and RMT based sensing schemes such as MME and EME.

One of the major challenges of Cognitive Radio (CRNs) is the spectrum handoff issue. Spectrum handoff happens when a Primary Users (PUs) appears in a spectrum band that is occupied by a Secondary User (SU). In such a case, SU should empty this spectrum band and perform a handoff procedure and search for an available free one. This process will be continued until the SU completes its data transmission. To avoid multiple spectrum handoffs, the spectrum handoff procedure should be performed in the unlicensed channels rather than the licensed channels. Thus, the number of handoffs can be reduced as no more spectrum handoffs will occur since all users have priority in this type of spectrum channel. This technique will help secondary users' QoS from degradation. This paper proposes a prioritized spectrum handoff decision scheme in a mixture spectrum environment of unlicensed and licensed channels, in order to reduce the handoff delay. The licensed channels in the proposed scheme have been modelled using a pre-emptive resume priority (PRP) M/M/C queue. In contrast, the unlicensed channels have been modelled using an M/M/C retrial priority queue. In order to examine the performance of the implemented model, the handoff and new SUs are considered with equal and different priorities. Experimental results show that the prioritized handoff scheme outperforms the other scheme in terms of average handoff delay under various traffic arrival rates as well as the number of licensed and unlicensed channels used.

Wireless devices and applications have been an unavoidable part of human lives in the past decade. In the past few years, the global mobile data traffic has grown considerably and is expected to grow even faster in future. Given the fact that the number of wireless nodes has significantly increased, the contention and interference on the license-free industrial, scientific, and medical band has become severer than ever. Cognitive radio nodes were introduced in the past decade to mitigate the issues related to spectrum scarcity. In this dissertation, we focus on the interference and performance analysis of networks coexisting with cognitive radio networks and address the design and analysis of spectrum allocation and routing for cognitive radio networks. Spectrum allocation enables nodes to construct a link on a common channel at the same time so they can start communicating with each other. We introduce a new approach for the modeling and analysis of interference and spectrum allocation schemes for cognitive radio networks with arbitrarily-shaped network regions. First, for the first time in the literature, we propose a simple and efficient approach that can derive the distribution of the distance between an arbitrary interior/exterior reference point and a random point within an arbitrary convex/concave irregular polygon. This tool is essential in analyzing important distance-related performance metrics in wireless communication networks. Second, considering the importance of interference analysis in cognitive radio networks and its important role in designing spectrum allocation schemes, we model and analyze a heterogeneous cellular network consisting of several cognitive femto cells and a coexisting multi-cell network. Besides the cumulative interference, important distance-related performance metrics have been investigated, such as the signal-to-interference ratio and outage probability. Finally, the spectrum allocation and routing problems in cognitive radio networks have been discussed. Considering a wireless cognitive radio network coexisting with a cellular network with irregular polygon-shaped cells, we have used the tools developed in this dissertation and proposed a joint spectrum allocation and routing scheme. / Graduate

Today, the radio spectrum is rarely fully utilized. This problem is valid in more domains, e.g., time, frequency and geographical location. To provide an efficient utilization of the radio spectrum, the Cognitive Radio Networks (CRNs) have been advanced. The key idea is to open up the licensed spectrum to unlicensed users, thus allowing them to use the so-called spectrum opportunities as long as they do not harmfully interfere with licensed users. An important focus is laid on the limitation of previously reported research efforts, which is due to the limited consideration of the problem of competition among unlicensed users for spectrum access in heterogeneous CRNs. A software framework is introduced, which is called PRioritized Opportunistic spectrum Access System (PROAS). In PROAS, the heterogeneity aspects of CRNs are specifically expressed in terms of cross-layer design and various wireless technologies. By considering factors like ease of implementation and efficiency of control, PROAS provides priority scheduling based solutions to alleviate the competition problem of unlicensed users in heterogenous CRNs. The advanced solutions include theoretical models, numerical analysis and experimental simulations for performance evaluation. By using PROAS, three particular CRN models are studied, which are based on ad-hoc, mesh-network and cellular-network technologies. The reported results show that PROAS has the ability to bridge the gap between research results and the practical implementation of CRNs.

Efficiently allocating the scarce and expensive radio resources is a key challenge for advanced radio communication systems. To this end, cognitive radio (CR) has emerged as a promising solution which can offer considerable improvements in spectrum utilization. Furthermore, cooperative communication is a concept proposed to obtain spatial diversity gains through relays without requiring multiple antennas. To benefit from both CR and cooperative communications, a combination of CR networks (CRNs) with cooperative relaying referred to as cognitive cooperative relay networks (CCRNs) has recently been proposed. CCRNs can better utilize the radio spectrum by allowing the secondary users (SUs) to opportunistically access spectrum, share spectrum with primary users (PUs), and provide performance gains offered by cooperative relaying. In this thesis, a performance analysis of underlay CRNs and CCRNs in different fading channels is provided based on analytical expressions, numerical results, and simulations. To allocate power in the CCRNs, power allocation policies are proposed which consider the peak transmit power limit of the SUs and the outage probability constraint of the primary network. Thus, the impact of multiuser diversity, peak transmit power, fading parameters, and modulation schemes on the performance of the CRNs and CCRNs can be analyzed. The thesis is divided into an introduction and five research parts based on peer-reviewed conference papers and journal articles. The introduction provides fundamental background on spectrum sharing systems, fading channels, and performance metrics. In the first part, a basic underlay CRN is analyzed where the outage probability and the ergodic capacity of the network over general fading channels is derived. In the second part, the outage probability and the ergodic capacity of an underlay CRN are assessed capturing the effect of multiuser diversity on the network subject to Nakagami-m fading. Considering the presence of a PU transmitter (PU-Tx), a power allocation policy is derived and utilized for CRN performance analysis under Rayleigh fading. In the third part, the impact of multiple PU-Txs and multiple PU receivers (PU-Rxs) on the outage probability of an underlay CCRN is studied. The outage constraint at the PU-Rx and the peak transmit power constraint of the SUs are taken into account to derive the power allocation policies for the SUs. In the fourth part, analytical expressions for the outage probability and symbol error probability for CCRNs are derived where signal combining schemes at the SU receiver (SU-Rx) are compared. Finally, the fifth part applies a sleep/wake-up strategy and the min(N; T) policy to an underlay CRN. The SUs of the network operate as wireless sensor nodes under Nakagami-m fading. A power consumption function of the CRN is derived. Further, the impact of M/G/1 queue and fading channel parameters on the power consumption is assessed.

Over time, wireless technology advancements in the field of communications have been attracting every individual to turn into a wireless user. To accommodate the increasing number of users and to avoid the problem of spectrum scarcity, the concept of Cognitive Radio Network (CRN) has been developed. Cognitive Radio (CR) is an intelligent radio which efficiently detects and allocates the spectrums of primary licensed users (PUs) to the secondary unlicensed users (SUs). The SUs can utilize these spectrums as long as they do not cause harmful interfere to the PUs. Interference may occur because of the following reasons: misdetection of spectrum availability, the high transmission power of SU when both SU and PU are present in the same channel at the same time. In order to avoid interference, the radio has to have a very accurate spectrum sensing method, transmit power at SU should be constrained by the peak interference power of PU and the CR should continuously sense the presence of PUs. To increase the wireless coverage area and reliability of CRN, a new technology called Cooperative Cognitive Radio Network (CCRN), which is a combination of CRN and cooperative communications was developed. A CCRN not only increases the reliability and wireless coverage area of CR but also improves the overall performance of the system. In this context, the main objective of this research work is to evaluate the outage performance of a CCRN in an environment where fading and shadowing also come into the picture and to study the importance of relay networks in CRN. To fulfill the objectives of this research work, a two-hop decode-and-forward CCRN is considered. The recently introduced κ − µ shadowed fading channel is employed over the CCRN to generate a realistic environment.  In order to implement such system as a whole, a deep literature study is performed beforehand. Analytical expressions for the Probability Density Function (PDF) and Cumulative Distribution Function (CDF) of the Signal-to-Noise Ratio (SNR) are obtained. The analytical expressions and simulation results for Outage Probability (OP) are obtained and compared under different fading parameters. The importance of a multiple-relay system in CRN is presented. From the results obtained in this research work, we can conclude that the OP decreases with increase in allowable peak interference power at the PU. The transmit power at SU should always be constrained by the peak interference power at the PU to avoid interference. The overall system performance increases with increasing number of relays.