abstract: The ability to identify unoccupied resources in the radio spectrum is a key capability for opportunistic users in a cognitive radio environment. This paper draws upon and extends geometrically based ideas in statistical signal processing to develop estimators for the rank and the occupied subspace in a multi-user environment from multiple temporal samples of the signal received at a single antenna. These estimators enable identification of resources, such as the orthogonal complement of the occupied subspace, that may be exploitable by an opportunistic user. This concept is supported by simulations showing the estimation of the number of users in a simple CDMA system using a maximum a posteriori (MAP) estimate for the rank. It was found that with suitable parameters, such as high SNR, sufficient number of time epochs and codes of appropriate length, the number of users could be correctly estimated using the MAP estimator even when the noise variance is unknown. Additionally, the process of identifying the maximum likelihood estimate of the orthogonal projector onto the unoccupied subspace is discussed. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2014

Cognitive radio (CR) is a novel wireless communication approach that may alleviate the looming spectrum-shortage crisis. Orthogonal frequency division multiplexing (OFDM) is an attractive modulation candidate for CR systems. In this thesis, we study resource allocation (RA) for OFDM-based CR systems using both aggressive and protective sharing. In aggressive sharing, cognitive radio users (CRUs) can share both non-active and active primary user (PU) bands. We develop a model that describes aggressive sharing, and formulate a corresponding multidimensional knapsack problem (MDKP). Low-complexity suboptimal RA algorithms are proposed for both single and multiple CRU systems. A simplified model is proposed which provides a faster suboptimal solution. Simulation results show that the proposed suboptimal solutions are close to optimal, and that aggressive sharing of the whole band can provide a substantial performance improvement over protective sharing, which makes use of only the non-active PU bands. Although aggressive sharing generally yields a higher spectrum-utilization efficiency than protective sharing, aggressive sharing may not be feasible in some situations. In such cases, sharing only non-active PU bands is more appropriate. When there are no fairness or quality of service (QoS) considerations among CRUs, both theoretical analysis and simulation results show that plain equal power allocation (PEPA) yields similar performance as optimal power allocation in a multiuser OFDM-based CR system. We propose a low-complexity discrete bit PEPA algorithm. To improve spectrum-utilization efficiency, while considering the time-varying nature of the available spectrum as well as the fading characteristics of wireless communication channels and providing QoS provisioning and fairness among users, this thesis introduces the following novel algorithms: (1) a distributed RA algorithm that provides both fairness and efficient spectrum usage for ad hoc systems; (2) a RA algorithm for non-real-time (NRT) services that maintains average user rates proportionally on the downlink of multiuser OFDM-based CR systems; and (3) cross-layer RA algorithms for the downlink of multiuser OFDM-based CR systems for both real-time (RT) services and mixed (RT and NRT) services. Simulation results show that the proposed algorithms provide satisfactory QoS to all supported services and perform better than existing algorithms designed for multiuser OFDM systems. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

The increased demand on wireless applications, coupled with the current inefficiency in spectrum usage, mandate a new communication paradigm shift from fixed spectrum assignment to dynamic spectrum sharing which can be achieved using the cognitive radio technology. Cognitive radio allows unlicensed secondary nodes to form communication links over licensed spectrum bands on an opportunistic basis which increases the spectrum management efficiency. Cognitive radio networks (CRN), however, impose unique challenges due to the fluctuation in the available spectrum as well as the diverse quality of service requirements. One of the main challenges is the establishment and maintenance of routes in multi-hop CRNs. In this thesis, we critically investigate the problem of routing in multi-hop CRNs. The main objective of this research is to maximize network connectivity while limiting routing delay. We developed a general connectivity metric for single-band and multi-band CRNs based on the properties of the Laplacian matrix eigenvalues spectrum. We show through analytical and simulation results that the developed metric is more robust and has lower computational complexity than the previously proposed metrics. Furthermore, we propose a new position-based routing algorithm for large scale CRNs which significantly reduces the routing computational complexity with negligible performance degradation compared to the traditional full node search algorithm. In addition, the connectivity metric developed in this thesis is used to develop a connectivity-aware distributed routing protocol for CRNs. Finally, we use a commodity cognitive radio testbed to demonstrate the concept of CR Wi-Fi networks.

Cognitive Radio (CR) aims to access the wireless spectrum in an opportunistic manner while the licensed user is not using it. To accurately determine the licensed user's existence, spectrum sensing procedure is vital to CR system. Energy detection-based spectrum sensing techniques is favourable due to its simplicity and low complexity. In addition, to improve the detection performance, cooperative spectrum sensing technique exploits multi-user diversity and mitigates detection uncertainty. In this thesis, we investigate several energy detection based cooperative spectrum sensing techniques.First, the closed-form analysis for the Equal Gain Combining based Soft Decision Combining (EGC-SDC) scheme, in which all CR users forward its observation to the fusion center, is derived. In order to reduce the communication overhead between CR users and the fusion center, we proposed quantized cooperative spectrum sensing technique, in which CR users quantize its local observation before forwarding to the fusion center. Next, the Double Threshold scheme, where some users only forward its local decision while other users forward its observation, is considered and analyzed. To further reduce the communication overhead, we also proposed that quantization is applied to the users who forward its observation. Later on, three sequential cooperative spectrum sensing schemes in time-varying channel are considered. By aggregating past local observations from previous sensing slots, CR users can improve the detection performance. The Weighted Sequential Energy Detector (SED) scheme simply takes fixed number of past local observations, while the other two schemes, Two-Stage SED and Differential SED, adaptively determine the number of observations, based on its decision towards primary user's existence.Simulation results show that the analysis on EGC-SDC scheme is accurate and the quantized cooperative spectrum sensing technique can improve the performance and approach the detection performance of EGC-SDC scheme with much less bandwidth requirement. Also, the Double Threshold scheme can help improve the detection performance over the conventional technique. Furthermore, the analysis on Double Threshold provides a closed-form for the probability of false alarm and detection. Additionally, the sequential spectrum sensing schemes are shown to improve the detection performance and enable CR system to work in scenarios that the conventional technique can not accommodate.

Due to the scarcity of frequency spectrum in view of the evolution of wireless communication technologies, the cognitive radio (CR) concept has been introduced to efficiently exploit the available spectrum. This concept consists in introducing unlicensed/secondary users (SU’s) in existing networks to share the spectrum of licensed/primary users (PU’s) without harming primary communications hence the name of “spectrum sharing” technique. We study in this dissertation, the capacity and the achievable rate of the secondary user within various communication settings. We, firstly, investigate the capacity of the (SU’s) at low power regime for Nakagami fading channels and present closed form of the capacity under various types of interference and/or power constraints. We explicitly characterize two regimes where either the interference constraint or the power constraint dictates the optimal power profile. Our framework also highlights the effects of different fading parameters on the secondary link ergodic capacity. Interestingly, we show that the low power regime analysis provides a specific insight on the capacity behavior of CR that has not been reported by previous studies. Next, we determine the spectral efficiency gain of an uplink CR Multi-Input Multi- Output (MIMO) system in which the SU is allowed to share the spectrum with the PU using a specific precoding scheme to communicate with a common receiver. Applied to Rayleigh fading channels, we show, through numerical results, that our proposed scheme enhances considerably the cognitive achievable rate. For instance, in case of a perfect detection of the PU signal, after applying Successive Interference Cancellation (SIC), the CR rate remains non-zero for high Signal to Noise Ratio (SNR) which is usually impossible when we only use space alignment technique. In addition, we show that the rate gain is proportional to the allowed interference threshold by providing a fixed rate even in the high SNR range. Finally, we study the impact of the broadcast approach and multi-layer coding on the throughput of CR systems for general fading channels. And we found that at the absence of the channel state information(CSI), we show that this improvement could be almost reached by 2-Layers coding. Then, we introduce a quantized CSI policy and highlight its improvement in terms of throughput before we study the rate when BA with quantized CSI is adopted. Numerical results show that the improvement of the additional layers is decreasing as the number of quantized regions increases.

In underlay cognitive radio networks, secondary users can share the spectrum with primary users as long as the interference caused by the secondary users to primary users is below a certain predetermined threshold. It is reasonable to assume that there is always a large pool of secondary users trying to access the channel, which can be occupied by only one secondary user at a given time. As a result, a multi-user scheduling problem arises among the secondary users. In this thesis, by manipulating basic schemes based on selective multi-user diversity, normalized thresholding, transmission power control, and opportunistic round robin, we propose and analyze eight scheduling schemes of secondary users in an underlay cognitive radio set-up. The system performance of these schemes is quantified by using various performance metrics such as the average system capacity, normalized average feedback load, scheduling outage probability, and system fairness of access. In our proposed schemes, the best user out of all the secondary users in the system is picked to transmit at each given time slot in order to maximize the average system capacity. Two thresholds are used in the two rounds of the selection process to determine the best user. The first threshold is raised by the power constraint from the primary user. The second threshold, which can be adjusted by us, is introduced to reduce the feedback load. The overall system performance is therefore dependent on the choice of these two thresholds and the number of users in the system given the channel conditions for all the users. In this thesis, by deriving analytical formulas and presenting numerical examples, we try to provide insights of the relationship between the performance metrics and the involved parameters including two selection thresholds and the number of active users in the system, in an effort to maximize the average system capacity as well as satisfy the requirements of scheduling outage probability and feedback load.

This thesis presents the realization of an intelligent cognitive radio network that uses long short term memory (LSTM) neural network for sensing and predicting the spectrum activity at each instant of time. The simulation is done using Python and GNU Radio. The implementation is done using GNU Radio and Universal Software Radio Peripherals (USRP). Simulation results show that the confidence factor of opportunistic users not causing interference to licensed users of the spectrum is 98.75%. The implementation results demonstrate high reliability of the LSTM based cognitive radio network.

Cognitive radio (CR) is a cutting-edge wireless communication technology that adopts several existing communication concepts in order to efficiently utilize the spectrum and meet the users demands of high throughput and real-time systems. Conventionally, high throughput demands are met through adopting broadband and multi-antenna technologies such as, orthogonal frequency division multiplexing (OFDM) and Multi-Input Multi-Output (MIMO). Whereas, real-time application demands are met by analyzing metrics which characterize the delay limited channels, such as, outage probability over block-fading channels. Being an environmental friendly technology, energy efficiency metrics should be considered in the design of a CR application. This thesis tackles the energy efficiency of CR system from different aspects, utilizing different measuring metrics and constrains. Under the single-input single-output (SISO) OFDM we minimized the energy per goodbit (EPG) metric subject to several power and Quality of Service (QoS) constraints. In this approach, the minimum EPG metric is optimized via proposing two optimal and sub-optimal resource allocation schemes. We consider several parameters as optimization variables, such as, power policy, sensing threshold, and channel quality threshold. We also captured the impact of involving the media access control (MAC) layers parameters, such as, frame length, in the minimization of a modified EPG metric. Also, a MAC protocol, i.e., hybrid automatic repeat request (HARQ), and the associated power consumption of the retransmission mechanism is considered in the formulation of the problem. In this context, the optimal power and frame length are derived to minimize the modified EPG while considering several spectrum-sharing scenarios, which depend on sensing information. In MIMO based CR system, we maximized capacity to power ratio (CPR) (as an energy efficiency (EE) metric) subject to several power and QoS constraints. In this context, the impact of sensing information with imperfect channel state information (CSI) of the secondary channel has been considered. To realize a CR system with real-time applications we minimized the outage probability over M block-fading channel with several long-term and short-term energy constrains. We derive the minimum outage region and the associated optimal power. Tractable expressions to lower and upper bound the outage probability are derived. We then analyze the impact of utilizing the sensing process of primary user activity.

With the increase in wireless technology devices and mobile users, wireless radio spectrum is coming under strain. Networks are becoming more and more congested and free usable spectrum is running out. This creates a resource allocation problem. The resource, wireless spectrum, needs to be allocated to users in a manner such that it is utilised efficiently and fairly. The objective of this research is to find a solution to the resource allocation problem in radio networks, i.e to increase the efficiency of spectrum utilisation by making maximum use of the spectrum that is currently available through taking advantage of co-existence and exploiting interference limits. The solution proposed entails adding more secondary users (SU) on a cognitive radio network (CRN) and having them transmit simultaneously with the primary user. A typical network layout was defined for the scenario. The interference temperature limit (ITL) was exploited to allow multiple SUs to share capacity. Weighting was applied to the SUs and was based on allowable transmission power under the ITL. Thus a more highly weighted SU will be allowed to transmit at more power. The weighting can be determined by some network-defined rule. Specific models that define the behaviour of the network were then developed using queuing theory, specifically weighted processor sharing techniques. Optimisation was finally applied to the models to maximize system performance. Convex optimization was deployed to minimize the length of the queue through the power allocation ratio. The system was simulated and results for the system performance obtained. Firstly, the performance of the proposed models under the processor-sharing techniques was determined and discussed, with explanations given. Then optimisation was applied to the processor-sharing results and the performance was measured. In addition, the system performance was compared to other existing solutions that were deemed closest to the proposed models. / Dissertation (MEng)--University of Pretoria, 2017. / Electrical, Electronic and Computer Engineering / MEng / Unrestricted

There is a belief that radio frequencies  are running out. However, according to a report from the Federal Communications Commission (FCC) in 2002, a different story was told : At any given time and location, much of the prized spectrum lies idle. At the same time, FCC revealed the fact that, in many bands, spectrum access is a more significant problem than physical scarcity of spectrum, in large part due to legacy command-and-control regulation that limits the ability of potential spectrum users to obtain such access. Hence, as opposed to static spectrum access, dynamic spectrum access (DSA) was proposed to solve the predicament. One such DSA model propose the existence of Primary users (licensed users and Secondary users (unlicensed users). Multicarrier communication technology is adopted to enable the coexistence of PU and SU. Orthogonal Frequency Division Multiplexing (OFDM) technology has been popular for multicarrier communications. A disadvantage for OFDM in the Cognitive Radio environment is its large side lobes in the frequency domain, which is a result of single-symbol pulse duration. Filter Bank Multicarrier (FBMC) uses filters that have small side lobes to synthesize/analyze the sub-carriers so as to greatly alleviate the previous mentioned disadvantage. FMT is one FBMC technique.  Although many hardware implementations have been explored during last few decades on OFDM, few FMT hardware implementation results, especially Hardware/Software Co-design, have been presented. This paper presents a HW/SW Co-design implementation result of FMT transceiver on the Altera DE4 board. / Master of Science