The sky-rocketing growth of multimedia infotainment applications and broadband-hungry mobile devices exacerbate the stringent demand for ultra high data rate and more spectrum resources. Along with it, the unbalanced temporal and geographical variations of spectrum usage further inspires those spectral-efficient networks, namely, cognitive radio and heterogeneous cellular networks (HCNs). This thesis focuses on the system design and performance enhancement of cognitive radio (CR) and HCNs. Three different aspects of performance improvement are considered, including link reliability of cognitive radio networks (CNs), security enhancement of CNs, and energy efficiency improvement of CNs and HCNs. First, generalized selection combining (GSC) is proposed as an effective receiver design for interference reduction and reliability improvement of CNs with outdated CSI. A uni- ed way for deriving the distribution of received signal-to-noise ratio (SNR) is developed in underlay spectrum sharing networks subject to interference from the primary trans- mitter (PU-Tx) to the secondary receiver (SU-Rx), maximum transmit power constraint at the secondary transmitter (SU-Tx), and peak interference power constraint at the PU receiver (PU-Rx), is developed. Second, transmit antenna selection with receive generalized selection combining (TAS/GSC) in multi-antenna relay-aided communica- tion is introduced in CNs under Rayleigh fading and Nakagami-m fading. Based on newly derived complex statistical properties of channel power gain of TAS/GSC, exact ergodic capacity and high SNR ergodic capacity are derived over Nakagami-m fading. Third, beamforming and arti cial noise generation (BF&AN) is introduced as a robust scheme to enhance the secure transmission of large-scale spectrum sharing networks with multiple randomly located eavesdroppers (Eves) modeled as homogeneous Poisson Point Process (PPP). Stochastic geometry is applied to model and analyze the impact of i BF&AN on this complex network. Optimal power allocation factor for BF&AN which maximizes the average secrecy rate is further studied under the outage probability con- straint of primary network. Fourth, a new wireless energy harvesting protocol is proposed for underlay cognitive relay networks with the energy-constrained SU-Txs. Exact and asymptotic outage probability, delay-sensitive throughput, and delay-tolerant through- put are derived to explore the tradeoff between the energy harvested from the PU-Txs and the interference caused by the PU-Txs. Fifth, a harvest-then-transmit protocol is proposed in K-tier HCNs with randomly located multiple-antenna base stations (BSs) and single antenna mobile terminals (MTs) modeled as homogeneous PPP. The average received power at MT, the uplink (UL) outage probability, and the UL average ergodic rate are derived to demonstrate the intrinsic relationship between the energy harvested from BSs in the downlink (DL) and the MT performance in the UL. Throughout the thesis, it is shown that link reliability, secrecy performance, and energy efficiency of CNs and HCNs can be signi cantly leveraged by taking advantage of multiple antennas, relays, and wireless energy harvesting.

Le relayage cognitif multiple-input multiple-output (MIMO) hérite l’efficacité spectrale de la radiocognitive et les systèmes de relayage MIMO, apportant ainsi des gains prometteurs en termes de débit dedonnées et de fiabilité pour les futures communications sans fil et mobiles. Dans cette thèse, nous concevons et évaluons des schémas pratiques d’émetteurs et de récepteurs pour des systèmes de relayage MIMO cognitifs qui peuvent être mis en oeuvre à moindre coût. Tout d'abord, nous réduisons l'affaiblissement du débit du mode half-duplex du relayage MIMO amplify-and-forward non-orthogonale(NAF) large bande avec demande de répétition automatique (ARQ). Différemment des travaux de recherche existants, le protocole de relayage proposé ne nécessite que la durée de transmission d’un seul paquet sur des canaux sélectifs en fréquence. De plus, nous proposons une conception de réception itérative à complexité réduite pour cette classe de protocoles, entraînant ainsi une amélioration significative des performances de transmission de bout-en-bout. Deuxièmement, nous nous concentrons sur les systèmes de relayage cognitive de partage du spectre single-input multiple-output (SIMO) et évaluons l’impact des contraintes d’interférence instantanée et statistique sur la qualité de leur probabilité de coupure. Nos résultats révèlent que l’imposition d’une contrainte statistique sur la puissance d’émission du système secondaire est plus favorable que son adversaire consommatrice de spectre. Troisièmement, nous capitalisons sur notre deuxième contribution pour étudier les systèmes de relayage MIMO decode-and-forward (DF) cognitifs utilisant la sélection d'antenne à l’émission (TAS) ainsi que le maximum-ratio combining (MRC) à la réception. Basés sur la maximisation du rapport signal-sur-bruit (SNR) ou du rapport signal-sur-interférence-plus-bruit (SINR), nos résultats de probabilité de coupure nouvellement dérivés pour les deux stratégies proposées de TAS démontre l’optimalité du système de sélection d’antenne basé sur le SINR par rapport aux effets néfastes d’interférence mutuelle dans les systèmes de relayage MIMO DF cognitifs. / Cognitive multiple-input multiple-output (MIMO) relaying inherits the spectrum usage efficiency from both cognitive radio and MIMO relay systems, thereby bearing promising gains in terms of data rate and reliability for future wireless and mobile communications. In this dissertation, we design and evaluate practical transmitter and receiver schemes for cognitive MIMO relay systems that can readily be implemented at a lower cost. First, we reduce the multiplexing loss due the half-duplex operation in non orthogonal amplify-and-forward (NAF) MIMO relay broadband transmissions with automatic repeat request(ARQ). Different from existing research works, the proposed relaying protocol requires only one packet duration to operate over frequency-selective block-fading relay channels. Further, we propose a low complexityiterative receiver design for this class of protocols which results in significant enhancement of the end-to-end transmission performance. Second, we focus on cognitive underlay single-input multiple-output (SIMO) relay systems and evaluate the impact of instantaneous and statistical interference constraints on their outage performance. Our results reveal that imposing a statistical interference constraint on the secondary system transmit power is most favored than its spectrum-consuming counter part. Third, we capitalize on our second contribution to investigate cost-effective transmission schemes for cognitive MIMO decode-and-forward (DF) relaying systems employing transmit-antenna selection (TAS) along with maximum-ratio combining (MRC) at the transmitter and receiver sides, respectively. Driven by maximizing either the received signal-to-noise ratio (SNR) or signal-to-interference-plus-noise ratio (SINR), our newly derived outage performance results pertaining to both proposed TAS strategies are shown to entail an involved derivation roadmap yet demonstrate the optimality of the SINR-driven TAS against the detrimental effect of mutual interference incognitive MIMO DF relay systems.

Reliable wireless networks for high speed trains require a significant amount of data communications for enabling safety features such as train collision avoidance and railway management. Cognitive radio integrates heterogeneous wireless networks that will be deployed in order to achieve intelligent communications in future railway systems. One of the primary technical challenges in achieving reliable communications for railways is the handling of high mobility environments involving trains, which includes significant Doppler shifts in the transmission as well as severe fading scenarios that makes it difficult to estimate wireless spectrum utilization. This thesis has two primary contributions: (1) The creation of a Heterogeneous Cooperative Spectrum Sensing (CSS) prototype system, and (2) the derivation of a Long Term Evolution for Railways (LTE-R) system performance analysis. The Heterogeneous CSS prototype system was implemented using Software-Defined Radios (SDRs) possessing different radio configurations. Both soft and hard-data fusion schemes were used in order to compare the signal source detection performance in real-time fading scenarios. For future smart railways, one proposed solution for enabling greater connectivity is to access underutilized spectrum as a secondary user via the dynamic spectrum access (DSA) paradigm. Since it will be challenging to obtain an accurate estimate of incumbent users via a single-sensor system within a real-world fading environment, the proposed cooperative spectrum sensing approach is employed instead since it can mitigate the effects of multipath and shadowing by utilizing the spatial and temporal diversity of a multiple radio network. Regarding the LTE-R contribution of this thesis, the performance analysis of high speed trains (HSTs) in tunnel environments would provide valuable insights with respect to the smart railway systems operating in high mobility scenarios in drastically impaired channels.

Developments such as machine-to-machine communications and multimedia services are placing growing demands on high-speed reliable transmissions and limited wireless spectrum resources. Although multiple-input multiple-output (MIMO) systems have shown the ability to provide reliable transmissions in fading channels, it is not practical for single-antenna devices to support MIMO system due to cost and hardware limitations. Cooperative communication allows single-antenna devices to share their spectrum resources and form a virtual MIMO system where their quality of service (QoS) may be improved via cooperation. Most cooperative communication solutions are based on fixed spectrum access schemes and thus cannot further improve spectrum efficiency. In order to support more users in the existing spectrum, we consider dynamic spectrum access schemes and cognitive radio techniques in this dissertation. Our work includes the modelling, characterization and optimization of QoS-constrained cooperative networks and cognitive radio networks. QoS constraints such as delay and data rate are modelled. To solve power control and channel resource allocation problems, dynamic power control, matching theory and multi-armed bandit algorithms are employed in our investigations. In this dissertation, we first consider a cluster-based cooperative wireless network utilizing a centralized cooperation model. The dynamic power control and optimization problem is analyzed in this scenario. We then consider a cooperative cognitive radio network utilizing an opportunistic spectrum access model. Distributed spectrum access algorithms are proposed to help secondary users utilize vacant channels of primary users in order to optimize the total utility of the network. Finally, a noncooperative cognitive radio network utilizing the opportunistic spectrum access model is analyzed. In this model, primary users do not communicate with secondary users. Therefore, secondary users are required to find vacant channels on which to transmit. Multi-armed bandit algorithms are proposed to help secondary users predict the availability of licensed channels. In summary, in this dissertation we consider both cooperative communication networks and cognitive radio networks with QoS constraints. Efficient power control and channel resource allocation schemes have been proposed for optimization problems in different scenarios.

Submitted in fulfilment of the academic requirements for the degree of Doctor of Philosophy (Ph.D.) in Engineering, in the School of Electrical and Information Engineering, Faculty of Engineering and the Built Environment, at the University of the Witwatersrand, Johannesburg, South Africa, 2017 / The continuous evolution of wireless communications technologies has increasingly imposed a burden on the use of radio spectrum. Due to the proliferation of new wireless networks applications and services, the radio spectrum is getting saturated and becoming a limited resource. To a large extent, spectrum scarcity may be a result of deficient spectrum allocation and management policies, rather than of the physical shortage of radio frequencies. The conventional static spectrum allocation has been found to be ineffective, leading to overcrowding and inefficient use. Cognitive radio (CR) has therefore emerged as an enabling technology that facilitates dynamic spectrum access (DSA), with a great potential to address the issue of spectrum scarcity and inefficient use. However, provisioning of reliable and robust communication with seamless operation in cognitive radio networks (CRNs) is a challenging task. The underlying challenges include development of non-intrusive dynamic resource allocation (DRA) and optimization techniques. The main focus of this thesis is development of adaptive channel assembling (ChA) and DRA schemes, with the aim to maximize performance of secondary user (SU) nodes in CRNs, without degrading performance of primary user (PU) nodes in a primary network (PN). The key objectives are therefore four-fold. Firstly, to optimize ChA and DRA schemes in overlay CRNs. Secondly, to develop analytical models for quantifying performance of ChA schemes over fading channels in overlay CRNs. Thirdly, to extend the overlay ChA schemes into hybrid overlay and underlay architectures, subject to power control and interference mitigation; and finally, to extend the adaptive ChA and DRA schemes for multiuser multichannel access CRNs. Performance analysis and evaluation of the developed ChA and DRA is presented, mainly through extensive simulations and analytical models. Further, the cross validation has been performed between simulations and analytical results to confirm the accuracy and preciseness of the novel analytical models developed in this thesis. In general, the presented results demonstrate improved performance of SU nodes in terms of capacity, collision probability, outage probability and forced termination probability when employing the adaptive ChA and DRA in CRNs. / CK2018

The cognitive radio (CR) concept is expected to be adopted along with many technologies to meet the requirements of the next generation of wireless and mobile systems, the 5G. Consequently, it is important to determine the performance of the CR systems with respect to these requirements. In this thesis, after briefly describing the 5G requirements, we present three main directions in which we aim to enhance the CR performance. The first direction is the reliability. We study the achievable rate of a multiple-input multiple-output (MIMO) relay-assisted CR under two scenarios; an unmanned aerial vehicle (UAV) one-way relaying (OWR) and a fixed two-way relaying (TWR). We propose special linear precoding schemes that enable the secondary user (SU) to take advantage of the primary-free channel eigenmodes. We study the SU rate sensitivity to the relay power, the relay gain, the UAV altitude, the number of antennas and the line of sight availability. The second direction is the scalability. We first study a multiple access channel (MAC) with multiple SUs scenario. We propose a particular linear precoding and SUs selection scheme maximizing their sum-rate. We show that the proposed scheme provides a significant sum-rate improvement as the number of SUs increases. Secondly, we expand our scalability study to cognitive cellular networks. We propose a low-complexity algorithm for base station activation/deactivation and dynamic spectrum management maximizing the profits of primary and secondary networks subject to green constraints. We show that our proposed algorithms achieve performance close to those obtained with the exhaustive search method. The third direction is the energy efficiency (EE). We present a novel power allocation scheme based on maximizing the EE of both single-input and single-output (SISO) and MIMO systems. We solve a non-convex problem and derive explicit expressions of the corresponding optimal power. When the instantaneous channel is not available, we present a simple sub-optimal power that achieves a near-optimal EE. The simulations show that the sub-optimal solution is very close to the optimal one. In the MIMO case, we show that adopting more antennas is more energy efficient.

Wireless communication systems have evolved substantially over the last two decades. The explosive growth of the wireless communications market is expected to continue in the future, as the demand for all types of wireless services is increasing. Beside providing higher data rates, next generation wireless networks (NGWN) are expected to have advanced capabilities such as interoperability, efficient spectrum utilization along with a wide variety of applications over different domains (e.g., public safety and military, aeronautical networks, femtocells, and so on) to the mobile users while serving as many users as possible. However, these advanced capabilities and services must be achieved under the constraint of limited available resources such as electromagnetic spectrum and power. In addition, NGWNs (and nodes within) need to modify themselves under rapidly changing conditions such as wireless propagation channel characteristics, traffic load, and so on. Moreover, NGWNs are expected to optimize their parameters by evaluating their experiences in the past. All of these characteristics imply that NGWNs should be equipped with cognitive capabilities including sensing, awareness, adaptation and responding to changing conditions along with learning about the past experiences. In this dissertation, environment, channel, and interference awareness are investigated in detail for NGWN. Methods for being aware of environment, channel, and interference are provided along with some possible ways of adapting several design parameters of NGWNs. In addition, cross-layer optimization issues are addressed from the perspective of both recently emerging technology called cognitive radio (CR) and NGWN.

In the last decade, cellular networks have been characterized by an ever-growing user data demand. This caused increasing capacity shortfall and coverage issues, aggravated by inefficient fixed spectrum management policies and obsolete network structures. From a practical point of view, novel technical and architectural solutions have been proposed to frame next generation cellular networks, capable of meeting the identified target performance to satisfy the user data demands. Specifically, new spectrum management policies based on the so-called dynamic spectrum access (DSA), together with hierarchical approaches to network planning, where a tier of macro base stations is underlaid with a tier of massively deployed low-power small base stations, are seen as promising candidates to achieve this scope. The resulting two-tiered network layout may improve the capacity of current networks in several ways, thanks to a better average link quality between the devices, a more efficient usage of spectrum resources and a potentially higher spatial reuse. In this thesis, we focus on the challenging problem arising when the two tiers share the transmit band, to capitalize on the available spectrum and avoid possible inefficiencies. In this case, the coexistence of the two tiers is not feasible, if suitable interference management techniques are not designed to mitigate/cancel the mutual interference generated by the active transmitters in the network. This thesis is divided in three main parts, and proposes a rather exhaustive approach to the development of new DSA and interference management techniques, to go from the theoretical basis up to a proof-of-concept development.

The prime wireless spectrum is inherently a critical yet scarce resource. As the demand of wireless bandwidth grows exponentially, it becomes a crucial issue to improve the spectrum utilization for the development and deployment of any new wireless technologies. In this thesis, we seek to address this problem through cooperative diversity and dynamic spectrum trading, in the context of the envisioned primary-secondary dynamic spectrum sharing paradigm. For an OFDMA-based cellular primary network which owns an exclusive right to access a certain spectrum band, we propose XOR-assisted cooperative diversity to improve the spectral efficiency of the allocated band, as well as an optimization framework to address the resource allocation problem. For the secondary network that utilizes cognitive radios to opportunistically exploit the spectrum white spaces, we establish a spectrum secondary market, design the market institution based on double auctions, and solve the decision making problem using reinforcement learning, to improve spectrum utilization via trading among secondary users.

The prime wireless spectrum is inherently a critical yet scarce resource. As the demand of wireless bandwidth grows exponentially, it becomes a crucial issue to improve the spectrum utilization for the development and deployment of any new wireless technologies. In this thesis, we seek to address this problem through cooperative diversity and dynamic spectrum trading, in the context of the envisioned primary-secondary dynamic spectrum sharing paradigm. For an OFDMA-based cellular primary network which owns an exclusive right to access a certain spectrum band, we propose XOR-assisted cooperative diversity to improve the spectral efficiency of the allocated band, as well as an optimization framework to address the resource allocation problem. For the secondary network that utilizes cognitive radios to opportunistically exploit the spectrum white spaces, we establish a spectrum secondary market, design the market institution based on double auctions, and solve the decision making problem using reinforcement learning, to improve spectrum utilization via trading among secondary users.