The exploding increase of wireless communications combined with the existing inefficient usage of the licensed spectrum gives a strong impetus to the development and standardization of cognitive radio networking and communications. In this dissertation, a framework for Dynamic Spectrum Access (DSA) is first presented, which is the enabling technology for increasing the spectral efficiency of wireless communications. Based on that, Cognitive Radio (CR) can be developed as an enabling technology for supporting the DSA, which means that the wireless users are provided with enhanced capability for sensing the operating radio environment and for exploiting the network side information obtained from this sensing. The DSA concept means that the users of a wireless system are divided into a multi-tiered hierarchy with the primary users (PUs) entitled to protection and with cognitive radio capable secondary users (SUs). The improved spectrum efficiency is obtained by means of a medium access control protocol with knowledge about the statistical properties or available local information of the channels already occupied by PUs as well as knowledge about the interference tolerance within which the interference to PUs is kept to a given level. Related to this, emphasis is laid on the protocol capability to determine the efficiency of the secondary sharing of spectrum. Based on the type of available local information, the capacity of opportunistic communication is investigated for three models. These are: with dynamic, distributed channels information; with dynamic, parallel channels information; and under a dynamic sub-channels allocation scheme. The results indicate that this capacity is robust with reference to the uncertainty associated with localized sensing of distributed dynamic channels and with timely sensing of parallel dynamic channels. The extension to dynamic parallel sub-channels enables resource allocation to be carried out in sub-channels. The analytical results on the performance of sub-channel allocation indicate a robust traffic capacity in terms of blocking probability, drop-out probability and delay performance as function of PUs traffic loads.

"Vehicular Dynamic Spectrum Access (VDSA) combines the advantages of dynamic spectrum access to achieve higher spectrum efficiency and the special mobility pattern of vehicle fleets. This dissertation presents several noval contributions with respect to vehicular communications, especially vehicle-to-vehicle communications. Starting from a system engineering aspect, this dissertation will present several promising future directions for vehicle communications, taking into consideration both the theoretical and practical aspects of wireless communication deployment. This dissertation starts with presenting a feasibility analysis using queueing theory to model and estimate the performance of VDSA within a TV whitespace environment. The analytical tool uses spectrum measurement data and vehicle density to find upper bounds of several performance metrics for a VDSA scenario in TVWS. Then, a framework for optimizing VDSA via artificial intelligence and learning, as well as simulation testbeds that reflect realistic spectrum sharing scenarios between vehicle networks and heterogeneous wireless networks including wireless local area networks and wireless regional area networks. Detailed experimental results justify the testbed for emulating a mobile dynamic spectrum access environment composed of heterogeneous networks with four dimensional mutual interference. Vehicular cooperative communication is the other proposed technique that combines the cooperative communication technology and vehicle platooning, an emerging concept that is expected to both increase highway utilization and enhance both driver experience and safety. This dissertation will focus on the coexistence of multiple vehicle groups in shared spectrum, where intra-group cooperation and inter-group competition are investigated in the aspect of channel access. Finally, a testbed implementation VDSA is presented and a few applications are developed within a VDSA environment, demonstrating the feasibility and benefits of some features in a future transportation system."

"As the demand for bandwidth increases, the inefficient use of the spectrum becomes more apparent and limiting. Currently, secondary (unlicensed) users can not use sparsely occupied portions of radio spectrum that are not allocated to them. In prior research, a variant of Orthogonal Frequency Division Multiplex (OFDM) called Non-Contiguous OFDM (NC-OFDM) was found to be a suitable transmission technique for enabling Dynamic Spectrum Access, which allows for multiple secondary users to share the spectrum. This thesis presents an algorithm for the synchronization of NC-OFDM. Moreover, a hardware architecture is proposed for the synchronization, and a pruned FFT/IFFT core is designed. At present, there has been minimal research into synchronization for NC-OFDM systems. As with any modulation scheme, synchronization is an important part for receiving the transmission successfully. The current synchronization scheme is simulated in variety of wireless channels to show that it can successfully communicate in the tested channels. Additionally a hardware architecture is laid out for the practical implementation of the synchronization algorithm. Since NC-OFDM does not use all of the carriers for transmission, the FFT and IFFT can have their computations reduced. Since the FFT and IFFT are important parts to the receiver and the transmitter, a pruned FFT/IFFT in hardware makes the most sense to be able to reduced the computation. The number of butterfly computations is reduced at the expense of a large increase in resource usage. "

"We proposed a novel spectrum allocation approach for distributed cognitive radio networks. Cognitive radio systems are capable of sensing the prevailing environmental conditions and automatically adapting its operating parameters in order to enhance system and network performance. Using this technology, our proposed approach optimizes each individual wireless device and its single-hop communication links using the partial operating parameter and environmental information from adjacent devices within the wireless network. Assuming stationary wireless nodes, all wireless communication links employ non-contiguous orthogonal frequency division multiplexing (NC-OFDM) in order to enable dynamic spectrum access (DSA). The proposed approach will attempt to simultaneously minimize the bit error rate, minimize out-of-band (OOB) interference, and maximize overall throughput using a multi-objective fitness function. Without loss in generality, genetic algorithms are employed to perform the actual optimization. Two generic optimization approaches, subcarrier-wise approach and block-wise approach, were proposed to access spectrum. We also proposed and analyzed several approaches implemented via genetic algorithms (GA), such as quantizing variables, using adaptive variable ranges, and Multi-Objective Genetic Algorithms, for increasing the speed and improving the results of combined spectrum utilization/cross-layer optimization approaches proposed, together with several assisting processes and modifications devised to make the optimization to improve efficiency and execution time."

Due to the ever increasing dependency on existing wireless technologies and the growing usage of sophisticated wireless devices, the demand for bandwidth is rising exponentially. Also, the Federal Communications Commission (FCC) has reserved a considerable amount of spectrum for licensed users. As a result, the unlicensed spectrum usage is constrained to the overcrowded unlicensed spectrum. Various spectral management surveys have indicated inefficient spectrum utilization in the licensed spectral bands. The congested unlicensed spectrum and inefficiently used licensed frequency bands calls for an approach to use the available spectrum opportunistically. Therefore, the concept of "Spectrum Pooling", which is based on Dynamic Spectrum Access (DSA), was proposed to make the unused sections of licensed spectrum available to the unlicensed users. In Spectrum Pooling, an empty section of licensed spectrum is borrowed by a secondary user for certain period of time without interfering with the licensed user. Orthogonal Frequency Division Multiplexing (OFDM) is a transmission scheme that is a candidate for Spectrum Pooling since it is capable of forming an adaptive spectral shape that allows coexistence of licensed and unlicensed users while attemting to minimize any interference. Subcarriers in the OFDM signal can be deactivated to generate Non-Contiguous OFDM (NC-OFDM). Even though NC-OFDM allows efficient use of available spectrum, it causes out of band (OOB) radiation, which adversely affects the performance of adjacent user. This thesis presents two novel techniques for combat the effects of OOB radiation generated by NC-OFDM. The proposed techniques employ a filtering-based approach combined with the technique of windowing in order to suppress the unwanted sidelobes by around 35dB-40dB. The attenuation is achieved without affecting other transmission parameters of the secondary user significantly.

Spectrum scarcity is an important challenge faced by high-speed wireless communications. Meanwhile, caused by current spectrum assignment policy, a large portion of spectrum is underutilized. Motivated by this, cognitive radio (CR) has emerged as one of the most promising candidate solutions to improve spectrum utilization, by allowing secondary users (SUs) to opportunistically access the temporarily unused spectrum, without introducing harmful interference to primary users. Moreover, opening of TV white space (TVWS) gives us the con dence to enable CR for TVWS spectrum. A crucial requirement in CR networks (CRNs) is wideband spectrum sensing, in which SUs should detect spectral opportunities across a wide frequency range. However, wideband spectrum sensing could lead to una ordably high sampling rates at energy-constrained SUs. Compressive sensing (CS) was developed to overcome this issue, which enables sub-Nyquist sampling by exploiting sparse property. As the spectrum utilization is low, spectral signals exhibit a natural sparsity in frequency domain, which motivates the promising application of CS in wideband CRNs. This thesis proposes several e ective algorithms for invoking CS in wideband CRNs. Speci cally, a robust compressive spectrum sensing algorithm is proposed for reducing computational complexity of signal recovery. Additionally, a low-complexity algorithm is designed, in which original signals are recovered with fewer measurements, as geolocation database is invoked to provide prior information. Moreover, security enhancement issue of CRNs is addressed by proposing a malicious user detection algorithm, in which data corrupted by malicious users are removed during the process of matrix completion (MC). One key spotlight feature of this thesis is that both real-world signals and simulated signals over TVWS are invoked for evaluating network performance. Besides invoking CS and MC to reduce energy consumption, each SU is supposed to harvest energy from radio frequency. The proposed algorithm is capable of o ering higher throughput by performing signal recovery at a remote fusion center.

<p>   The need for RF spectrum for the rapidly growing broadband access services is evident. Cognitive radio is an emerging technology that aims to introduce secondary usage of the spectrum resources without interfering with the primary usage of the licensed users but with a lower priority.</p><p>   Signal detection for cognitive radios has drawn a lot of interest in the research community, where different algorithms are suggested. The most commonly used algorithms are energy detection, feature detection, eigenvalue based detection. Energy detection is the simplest and most common way to detect signals. It has fast sensing time but poor performance. The feature detection and eigenvalue based detection methods are more sophisticated and offer better performance but they are more complex and expensive. This thesis will present the pros and cons of each method and offer comparisons between them.</p><p>   To evaluate the performance of different algorithms used in cognitive radio, different research testbeds have been suggested in the literature. Some of the most frequently used testbeds are based on GNU-radio, WARP, or BEE2. GNU-radio is the simplest testbed and is free, but it has low bandwidth and poor performance. WARP and BEE2 are more advanced testbeds. They offer good performance and are easy to update, but they are more complex and expensive. These three testbeds will be described, compared, and their advantages and disadvantages will be observed in this thesis.</p>

The need for RF spectrum for the rapidly growing broadband access services is evident. Cognitive radio is an emerging technology that aims to introduce secondary usage of the spectrum resources without interfering with the primary usage of the licensed users but with a lower priority.    Signal detection for cognitive radios has drawn a lot of interest in the research community, where different algorithms are suggested. The most commonly used algorithms are energy detection, feature detection, eigenvalue based detection. Energy detection is the simplest and most common way to detect signals. It has fast sensing time but poor performance. The feature detection and eigenvalue based detection methods are more sophisticated and offer better performance but they are more complex and expensive. This thesis will present the pros and cons of each method and offer comparisons between them.    To evaluate the performance of different algorithms used in cognitive radio, different research testbeds have been suggested in the literature. Some of the most frequently used testbeds are based on GNU-radio, WARP, or BEE2. GNU-radio is the simplest testbed and is free, but it has low bandwidth and poor performance. WARP and BEE2 are more advanced testbeds. They offer good performance and are easy to update, but they are more complex and expensive. These three testbeds will be described, compared, and their advantages and disadvantages will be observed in this thesis.

Spectrum sensing is an essential pre-processing step of cognitive radio technology for dynamic radio spectrum management. One of the main functions of Cognitive radios is to detect the unused spectrum and share it without harmful interference with other users. The detection of signal components present within a determined frequency band is an important requirement of any sensing technique. Most methods are restricted to the detection of the spectral lines. However, these methods may not comply with the needs imposed by practical applications.  This master thesis work presents a novel method to detect significant spectral components in measured non-flat spectra by classifying them in two groups: signal and noise frequency lines. The algorithm based on Fisher’s discriminant analysis, aside from the detection of spectral lines, estimates the magnitude of the spectral lines and provides a measure of the quality of classification to determine if a spectral line was incorrectly classified. Furthermore, the frequency lines with higher probability of misclassification are regrouped and the validation process recomputed, which results in lower probabilities of misclassification. The proposed automatic detection algorithm requires no user interaction since any prior knowledge about the measured signal and the noise power is needed. The presence or absence of a signal regardless of the shape of the spectrum can be detected. Hence, this method becomes a strong basis for high-quality operation mode of cognitive radios. Simulation and measurement results prove the advantages of the presented technique. The performance of the technique is evaluated for different signal-to-noise ratios (SNR) ranging from 0 to -21dB as required by the IEEE standard for smart radios. The method is compared with previous signal detection methods.

This thesis investigates cooperative communication under the framework of cognitive radio network, which consists of primary and secondary users(PU & SU). The cooperative and cognitive radio network (CCR) adopts overlay dynamic spectrum access, That is, the SU simultaneously assists PU¡¦s transmission and transmits its own message using spectrum shared by primary user. The secondary user adopts decode-and-forward (DF) relaying to assist the primary user in transmitting message. With secondary user¡¦s assistance, the cooperative system can be treat as an equivalent multiple input single output (MISO) system to attain the spatial diversity of the primary user. The virtual MISO system can reduce the outage probability and enhance the transmission reliability. Under the requirement on primary user's transmission quality, secondary user transmits both user¡¦s signals simultaneously, so that the secondary acquires authority to access spectrum. Based on limited feedback regarding SNR of link between primary transmitter and receiver, secondary user allocates transmission power of primary signal and secondary signal to increase throughput and spectrum efficiency of SU subject to satisfying PU¡¦s outage constraint.