One of the problems facing wireless network planners is a perceived scarcity of spectrum. A technology that addresses this problem is cognitive radio (CR). A critical function of a CR network is spectrum sensing (SS). A secondary user (SU) in a CR network will perform SS to gather information about the radio environment within which it wishes to operate and then make decisions based on that information. While SS by individual SUs is very useful it has been found in the literature that a cooperative approach, where SUs share their individual results, may provide more accurate information about the radio environment. It has also been shown that it is beneficial for SUs to be able to make proactive decisions about spectrum resource allocation. To be able to make these proactive decisions, a SU will need to be able to make predictions about the future behaviour of other users of the same spectrum. This research project was divided into two parts. Firstly, a measurement campaign was performed to characterise spectrum scarcity in the South African context. Detailed information, about the occupancy of various commercially utilised South African frequency bands, was collected from spectrum measurement campaigns carried at the Hatfield campus of the University of Pretoria and at Pinmill Farm in Johannesburg. These bands included the television broadcast and mobile cellular bands. On average, the television broadcast bands were found to be underutilised highlighting the existence of a number of opportunities for television white space devices. However, the mobile cellular bands were found to be much more heavily occupied, particularly for the bands around 900 MHz, suggesting that mobile operators are currently in need of additional spectrum resources. The second part of this thesis followed a more theoretical approach and was based on the need for proactive decision making in CR networks. A single SU prediction method, of relatively cheap computational complexity, was proposed and tested under various traffic conditions. The premise that collaboration between SUs may improve the accuracy of single SU traffic predictions was then explored. Pre-fusion and post-fusion approaches to cooperative prediction were compared with the single SU prediction scenario. The prediction error for the cooperative approaches was found to be lower than for the single SU case, especially for the pre-fusion scenario. For example, for a signal-to-noise ratio of 8 dB and individual forecast probability of 0.9, the pre-fusion prediction error was found to be approximately 2% compared with 26% for single SU prediction error. The cost of this improvement, however, was added algorithm complexity. It was then demonstrated that primary user traffic prediction could be used to improve the energy consumption associated with cooperative SS in a CR network. Combined with an optimal scheduling algorithm, this approach was shown to prolong the lifetime of a group of twenty cooperating SUs by 21.2 time samples for a uniformly distributed group of SUs when predictions were made ten time samples into the future. / Thesis (PhD)--University of Pretoria, 2016. / The Sentech Chair in Broadband Wireless Multimedia Communication / The National Research Foundation / The Independent Communications Authority of South Africa / Electrical, Electronic and Computer Engineering / PhD / Unrestricted

For traditional wireless communication systems, static spectrum allocation is the major spectrum allocation methodology. However, according to the recent investigations by the FCC, this has led to more than 70 percent of the allocated spectrum in the United States being under-utilized. Cognitive radio (CR) technology, which supports opportunistic spectrum sharing, is one idea that is proposed to improve the overall utilization efficiency of the radio spectrum. In this thesis we consider a CR communication system based on spectrum sharing schemes, where we have a secondary user (SU) link with multiple transmitting antennas and a single receiving antenna, coexisting with a primary user (PU) link with a single receiving antenna. At the SU transmitter (SU-Tx), the channel state information (CSI) of the SU link is assumed to be perfectly known; while the interference channel from the SU-Tx to the PU receiver (PU-Rx) is not perfectly known due to less cooperation between the SU and the PU. As such, the SU-Tx is only assumed to know that the interference channel gain can take values from a finite set with certain probabilities. Considering a SU transmit power constraint, our design objective is to determine the transmit covariance matrix that maximizes the SU rate, while we protect the PU by enforcing both a PU average interference constraint and a PU outage probability constraint. This problem is first formulated as a non-convex optimization problem with a non-explicit probabilistic constraint, which is then approximated as a mixed binary integer programming (MBIP) problem and solved with the Branch and Bound (BB) algorithm. The complexity of the BB algorithm is analyzed and numerical results are presented to validate the eff ectiveness of the proposed algorithm. A key result proved in this thesis is that the rank of the optimal transmit covariance matrix is one, i.e., CR beamforming is optimal under PU outage constraints. Finally, a heuristic algorithm is proposed to provide a suboptimal solution to our MBIP problem by efficiently (in polynomial time) solving a particularly-constructed convex problem.

No / The development of the IEEE 802.22 standard is aimed at providing broadband access in rural areas by effectively utilizing the unused TV band, provided no harmful interference is caused to the incumbent operation. The motivation behind TV band selection is of having lower frequencies compared to other licensed bands, which, therefore, results in lower propagation path loss. Due to this quality, the spectral power density of the radio signal reduces slowly, which results in a high coverage area. Further, it has been observed that many TV channels largely remain unoccupied, as most households and businesses rely on cable and satellite TV services. This is the first international standard for a wireless regional area network (WRAN) based on cognitive radio technologies. This standard provides both PHY and MAC layer functionalities in an infrastructure based network for communication between customer premise equipments (CPEs) through a base station (BS). The Spectrum Manager is the central part of the BS, which plays a significant role in maintaining spectrum availability information, channel selection, channel management, scheduling quiet periods for spectrum sensing, accessing to the database and implementing IEEE 802.22 policies. A WRAN can particularly accommodate up to 512 CPEs in a cell. Contention may occur during initial ranging, periodic ranging, bandwidth request and urgent coexistence situation notification. The medium access control (MAC) incorporates several schemes to control contention between CPEs within a cell and overlapping cells sharing the same channel. A CPE has to make decision to resolve collisions in the upstream direction. In the case of initial ranging and periodic ranging, code division multiple access (CDMA) is employed to resolve collisions. For bandwidth and UCS notification, either a CDMA or exponential time backoff approach can be applied for collision resolution. This paper presents the analytical framework to evaluate the number of active CPEs in a cognitive radio network, It is important to note that when the arrival rate becomes equal to the service rate, the active CPEs curve attains a constant value. Further, the active CPEs length is highly dependent on service rate. The different special cases have been addressed and the effectiveness of the proposed framework has been validated through various evaluation results.

The development of the IEEE 802.22 standard is aimed at providing broadband access in rural areas by effectively utilizing the unused TV band, provided no harmful interference is caused to the incumbent operation. This thesis presents the analytical framework to evaluate the number of active customer premise equipments (CPEs) in a wireless regional area network. Initial ranging is the primary process in IEEE 802.22 networks for CPEs to access the network and establish their connections with the base station (BS). A comprehensive analysis of initial ranging mechanism is provided in this work and initial ranging request success probability is derived based on the number of contended CPEs and the initial contention window size. Further, the average ranging success delay is derived for the maximum backoff stages. The collision probability is highly dependent on the size of the initial contention window and the number of contended CPEs. To keep it at a specific level, it is necessary for the BS to schedule the required size of the initial contention window to facilitate the maximum number of CPEs to establish their connections with reasonable delay. Therefore, the optimized initial window size is proposed that meets the collision probability constraint for a particular number of contended CPEs. An analytical model is also developed to estimate the ranging request collision probability depending upon the size of initial contention window and the number of contended CPEs. Moreover, this approximation provides the threshold size for contention window to start the initial ranging process in the IEEE 802.22 network.

Abstract Cognitive Radio (CR) improves the efficiency of spectrum utilization by allowing non- licensed users to utilize bands when not occupied by licensed users. In this thesis, we address several challenges currently limiting the wide use of cognitive radios. These challenges include identification of unoccupied bands, energy consumption and other technical challenges. Improved accuracy edge detection techniques are developed for CR to mitigate both noise and estimation error variance effects. Next, a reduced complexity Simplified DFT (SDFT) is proposed for use in CR. Then, a sub-Nyquist rate A to D converter is introduced to reduce energy consumption. Finally, a novel multi-resolution PSD estimation based on expectation-maximization algorithm is introduced that can obtain a more accurate PSD within a specified sensing time.

Cognitive radio (CR) networks and heterogeneous cellular networks are promising approaches to satisfy the demand for higher data rates and better connectivity. A CR network increases the utilization of the radio spectrum by opportunistically using it. Heterogeneous networks provide high data rates and improved connectivity by spatially reusing the spectrum and by bringing the network closer to the user. Interference presents a critical challenge for reliable communication in these networks. Accurately modeling it is essential in ensuring a successful design and deployment of these networks. We first propose modeling the aggregate interference power at a primary receiver (PU-Rx) caused from transmissions by randomly located cognitive users (CUs) in a CR network as a shifted lognormal random process. Its parameters are determined using a moment matching method. Extensive benchmarking shows that the proposed model is more accurate than the lognormal and Gaussian process models considered in the literature, even for a relatively dense deployment of CUs. It also compares favorably with the asymptotically exact stable and symmetric truncated stable distribution models, except at high CU densities. Our model accounts for the effect of imperfect spectrum sensing, interweave and underlay modes of CR operation, and path-loss, time-correlated shad-owing and fading of the various links in the network. It leads to new expressions for the probability distribution function, level crossing rate (LCR), and average exceedance duration (AED). The impact of cooperative spectrum sensing is also characterized. We also apply and validate the proposed model by using it to redesign the primary exclusive zone to account for the time-varying nature of interference. Next we model the uplink inter-cell aggregate interference power in homogeneous and heterogeneous cellular systems as a simpler lognormal random variable. We develop a new moment generating function (MGF) matching method to determine the lognormal’s parameters. Our model accounts for the transmit power control, peak transmit power constraint, small scale fading and large scale shadowing, and randomness in the number of interfering mobile stations and their locations. In heterogeneous net-works, the random nature of the number and locations of low power base stations is also accounted for. The accuracy of the proposed model is verified for both small and large values of interference. While not perfect, it is more accurate than the conventional Gaussian and moment-matching-based lognormal and Gamma distribution models. It is also performs better than the symmetric-truncated stable and stable distribution models, except at higher user density.

Abstract Cognitive Radio (CR) improves the efficiency of spectrum utilization by allowing non- licensed users to utilize bands when not occupied by licensed users. In this thesis, we address several challenges currently limiting the wide use of cognitive radios. These challenges include identification of unoccupied bands, energy consumption and other technical challenges. Improved accuracy edge detection techniques are developed for CR to mitigate both noise and estimation error variance effects. Next, a reduced complexity Simplified DFT (SDFT) is proposed for use in CR. Then, a sub-Nyquist rate A to D converter is introduced to reduce energy consumption. Finally, a novel multi-resolution PSD estimation based on expectation-maximization algorithm is introduced that can obtain a more accurate PSD within a specified sensing time.

The federal communications commission (FCC) has predicted that, under the current regulatory environment, a spectrum shortage may be faced in the near future. This impending spectrum shortage is in part due to a rapidly increasing demand for wireless services and in part due to inefficient usage of currently licensed bands. A new paradigm pertaining to wireless spectrum allocation, known as cognitive radio (CR), has been proposed as a potential solution to this problem. This dissertation seeks to contribute to research in the field of CR through an investigation into the effect that a primary user (PU) channel occupancy model will have on the performance of a secondary user (SU) in a CR network. The model assumes that PU channel occupancy can be described as a binary process and a two state Hidden Markov Model (HMM) was thus chosen for this investigation. Traditional algorithms for training the model were compared with certain evolutionary-based training algorithms in terms of their resulting prediction accuracy and computational complexity. The performance of this model is important since it provides SUs with a basis for channel switching and future channel allocations. A CR simulation platform was developed and the results gained illustrated the effect that the model had on channel switching and the subsequently achievable performance of a SU operating within a CR network. Performance with regard to achievable SU data throughput, PU disruption rate and SU power consumption, were examined for both theoretical test data as well as data obtained from real world spectrum measurements (taken in Pretoria, South Africa). The results show that a trade-off exists between the achievable SU throughput and the average PU disruption rate. Significant SU performance improvements were observed when prediction modelling was employed and it was found that the performance and complexity of the model were influenced by the algorithm employed to train it. SU performance was also affected by the length of the quick sensing interval employed. Results obtained from measured occupancy data were comparable with those obtained from theoretical occupancy data with an average percentage similarity score of 96% for prediction accuracy (using the Viterbi training algorithm), 90% for SU throughput, 83% for SU power consumption and 71% for PU disruption rate. / Dissertation (MEng)--University of Pretoria, 2012. / Electrical, Electronic and Computer Engineering / unrestricted

The development of the IEEE 802.22 standard is aimed at providing broadband access in rural areas by effectively utilizing the unused TV band, provided no harmful interference is caused to the incumbent operation. This thesis presents the analytical framework to evaluate the number of active customer premise equipments (CPEs) in a wireless regional area network. Initial ranging is the primary process in IEEE 802.22 networks for CPEs to access the network and establish their connections with the base station (BS). A comprehensive analysis of initial ranging mechanism is provided in this work and initial ranging request success probability is derived based on the number of contended CPEs and the initial contention window size. Further, the average ranging success delay is derived for the maximum backoff stages. The collision probability is highly dependent on the size of the initial contention window and the number of contended CPEs. To keep it at a specific level, it is necessary for the BS to schedule the required size of the initial contention window to facilitate the maximum number of CPEs to establish their connections with reasonable delay. Therefore, the optimized initial window size is proposed that meets the collision probability constraint for a particular number of contended CPEs. An analytical model is also developed to estimate the ranging request collision probability depending upon the size of initial contention window and the number of contended CPEs. Moreover, this approximation provides the threshold size for contention window to start the initial ranging process in the IEEE 802.22 network. / Bahauddin Zakariya University Multan, Pakistan.

Given the ever increasing reliance of today’s society on ubiquitous wireless access, the paradigm of dynamic spectrum access (DSA) as been proposed and implemented for utilizing the limited wireless spectrum more efficiently. Orthogonal frequency division multiplexing (OFDM) is growing in popularity for adoption into wireless services employing DSA frame- work, due to its high bandwidth efficiency and resiliency to multipath fading. While these advantages have been proven for many wireless applications, including LTE-Advanced and numerous IEEE wireless standards, one potential drawback of OFDM or its non-contiguous variant, NC-OFDM, is that it exhibits high peak-to-average power ratios (PAPR), which can induce in-band and out-of-band (OOB) distortions when the peaks of the waveform enter the compression region of the transmitter power amplifier (PA). Such OOB emissions can interfere with existing neighboring transmissions, and thereby severely deteriorate the reliability of the DSA network. A performance-enhancing digital pre-distortion (DPD) technique compensating for PA and in-phase/quadrature (I/Q) modulator distortions is proposed in this dissertation. Al- though substantial research efforts into designing DPD schemes have already been presented in the open literature, there still exists numerous opportunities to further improve upon the performance of OOB suppression for NC-OFDM transmission in the presence of RF front-end impairments. A set of orthogonal polynomial basis functions is proposed in this dissertation together with a simplified joint DPD structure. A performance analysis is presented to show that the OOB emissions is reduced to approximately 50 dBc with proposed algorithms employed during NC-OFDM transmission. Furthermore, a novel and intuitive DPD solution that can minimize the power regrowth at any pre-specified frequency in the spurious domain is proposed in this dissertation. Conventional DPD methods have been proven to be able to effectively reduce the OOB emissions that fall on top of adjacent channels. However more spectral emissions in more distant frequency ranges are generated by employing such DPD solutions, which are potentially in violation of the spurious emission limit. At the same time, the emissions in adjacent channel must be kept under the OOB limit. To the best of the author’s knowledge, there has not been extensive research conducted on this topic. Mathematical derivation procedures of the proposed algorithm are provided for both memoryless nonlinear model and memory-based nonlinear model. Simulation results show that the proposed method is able to provide a good balance of OOB emissions and emissions in the far out spurious domain, by reducing the spurious emissions by 4-5 dB while maintaining the adjacent channel leakage ratio (ACLR) improvement by at least 10 dB, comparing to the PA output spectrum without any DPD.