Cognitive Radio Systems

Cognitive radio is a hot research area for future wireless communications in the recent years. In order to increase the spectrum utilization, cognitive radio makes it possible for unlicensed users to access the spectrum unoccupied by licensed users. Cognitive radio let the equipments more intelligent to communicate with each other in a spectrum-aware manner and provide a new approach for the co-existence of multiple wireless systems. The goal of this book is to provide highlights of the current research topics in the field of cognitive radio systems. The book consists of 17 chapters, addressing various problems in cognitive radio systems

Evaluation of Overlay/underlay Waveform via SD-SMSE Framework for Enhancing Spectrum Efficiency

Recent studies have suggested that spectrum congestion is mainly due to the inefficient use of spectrum rather than its unavailability. Dynamic Spectrum Access (DSA) and Cognitive Radio (CR) are two terminologies which are used in the context of improved spectrum efficiency and usage. The DSA concept has been around for quite some time while the advent of CR has created a paradigm shift in wireless communications and instigated a change in FCC policy towards spectrum regulations. DSA can be broadly categorized as using a 1) Dynamic Exclusive Use Model, 2) Spectrum Commons or Open sharing model or 3) Hierarchical Access model. The hierarchical access model envisions primary licensed bands, to be opened up for secondary users, while inducing a minimum acceptable interference to primary users. Spectrum overlay and spectrum underlay technologies fall within the hierarchical model, and allow primary and secondary users to coexist while improving spectrum efficiency. Spectrum overlay in conjunction with the present CR model considers only the unused (white) spectral regions while in spectrum underlay the underused (gray) spectral regions are utilized. The underlay approach is similar to ultra wide band (UWB) and spread spectrum (SS) techniques utilize much wider spectrum and operate below the noise floor of primary users. Software defined radio (SDR) is considered a key CR enabling technology. Spectrally modulated, Spectrally encoded (SMSE) multi-carrier signals such as Orthogonal Frequency Domain Multiplexing (OFDM) and Multi-carrier Code Division Multiple Access (MCCDMA) are hailed as candidate CR waveforms. The SMSE structure supports and is well-suited for SDR based CR applications. This work began by developing a general soft decision (SD) CR framework, based on a previously developed SMSE framework that combines benefits of both the overlay and underlay techniques to improve spectrum efficiency and maximizing the channel capacity. The resultant SD-SMSE framework provides a user with considerable flexibility to choose overlay, underlay or hybrid overlay/underlay waveform depending on the scenario, situation or need. Overlay/Underlay SD-SMSE framework flexibility is demonstrated by applying it to a family of SMSE modulated signals such as OFDM, MCCDMA, Carrier Interferometry (CI) MCCDMA and Transform Domain Communication System (TDCS). Based on simulation results, a performance analysis of Overlay, Underlay and hybrid Overlay/Underlay waveforms are presented. Finally, the benefits of combining overlay/underlay techniques to improve spectrum efficiency and maximize channel capacity are addressed

Interference mitigation in cognitive femtocell networks

“A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Doctor of Philosophy”.Femtocells have been introduced as a solution to poor indoor coverage in cellular communication which has hugely attracted network operators and stakeholders. However, femtocells are designed to co-exist alongside macrocells providing improved spatial frequency reuse and higher spectrum efficiency to name a few. Therefore, when deployed in the two-tier architecture with macrocells, it is necessary to mitigate the inherent co-tier and cross-tier interference. The integration of cognitive radio (CR) in femtocells introduces the ability of femtocells to dynamically adapt to varying network conditions through learning and reasoning. This research work focuses on the exploitation of cognitive radio in femtocells to mitigate the mutual interference caused in the two-tier architecture. The research work presents original contributions in mitigating interference in femtocells by introducing practical approaches which comprises a power control scheme where femtocells adaptively controls its transmit power levels to reduce the interference it causes in a network. This is especially useful since femtocells are user deployed as this seeks to mitigate interference based on their blind placement in an indoor environment. Hybrid interference mitigation schemes which combine power control and resource/scheduling are also implemented. In a joint threshold power based admittance and contention free resource allocation scheme, the mutual interference between a Femtocell Access Point (FAP) and close-by User Equipments (UE) is mitigated based on admittance. Also, a hybrid scheme where FAPs opportunistically use Resource Blocks (RB) of Macrocell User Equipments (MUE) based on its traffic load use is also employed. Simulation analysis present improvements when these schemes are applied with emphasis in Long Term Evolution (LTE) networks especially in terms of Signal to Interference plus Noise Ratio (SINR)

Resource Allocation in Underlay and Overlay Spectrum Sharing

As the wireless communication technologies evolve and the demand of wireless services increases, spectrum scarcity becomes a bottleneck that limits the introduction of new technologies and services. Spectrum sharing between primary and secondary users has been brought up to improve spectrum efficiency. In underlay spectrum sharing, the secondary user transmits simultaneously with the primary user, under the constraint that the interference induced at the primary receiver is below a certain threshold, or a certain primary rate requirement has to be satisfied. Specifically, in this thesis, the coexistence of a multiple-input single-output (MISO) primary link and a MISO/multiple-input multiple-output (MIMO) secondary link is studied. The primary transmitter employs maximum ratio transmission (MRT), and single-user decoding is deployed at the primary receiver. Three scenarios are investigated, in terms of the interference from the primary transmitter to the secondary receiver, namely, weak interference, strong interference and very strong interference, or equivalently three ranges of primary rate requirement. Rate splitting and successive decoding are deployed at the secondary transmitter and receiver, respectively, when it is feasible, and otherwise single-user decoding is deployed at the secondary receiver. For each scenario, optimal beamforming/precoding and power allocation at the secondary transmitter is derived, to maximize the achievable secondary rate while satisfying the primary rate requirement and the secondary power constraint. Numerical results show that rate splitting at the secondary transmitter and successive decoding at the secondary receiver does significantly increase the achievable secondary rate if feasible, compared with single-user decoding at the secondary receiver. In overlay spectrum sharing, different from underlay spectrum sharing, the secondary transmitter can utilize the knowledge of the primary message, which is acquired non-causally (i.e., known in advance before transmission) or causally (i.e., acquired in the first phase of a two-phase transmission), to help transmit the primary message besides its own message. Specifically, the coexistence of a MISO primary link and a MISO/MIMO secondary link is studied. When the secondary transmitter has non-causal knowledge of the primary message, dirty-paper coding (DPC) can be deployed at the secondary transmitter to precancel the interference (when decoding the secondary message at the secondary receiver), due to the transmission of the primary message from both transmitters. Alternatively, due to the high implementation complexity of DPC, linear precoding can be deployed at the secondary transmitter. In both cases, the primary transmitter employs MRT, and single-user decoding is deployed at the primary receiver; optimal beamforming/precoding and power allocation at the secondary transmitter is obtained, to maximize the achievable secondary rate while satisfying the primary rate requirement and the secondary power constraint. Numerical results show that with non-causal knowledge of the primary message and the deployment of DPC at the secondary transmitter, overlay spectrum sharing can achieve a significantly higher secondary rate than underlay spectrum sharing, while rate loss occurs with the deployment of linear precoding instead of DPC at the secondary transmitter. When the secondary transmitter does not have non-causal knowledge of the primary message, and still wants to help with the primary transmission in return for the access to the spectrum, it can relay the primary message in an amplify-and-forward (AF) or a decode-and-forward (DF) way in a two-phase transmission, while transmitting its own message. The primary link adapts its transmission strategy and cooperates with the secondary link to fulfill its rate requirement. To maximize the achievable secondary rate while satisfying the primary rate requirement and the primary and secondary power constraints, in the case of AF cooperative spectrum sharing, optimal relaying matrix and beamforming vector at the secondary transmitter is obtained; in the case of DF cooperative spectrum sharing, a set of parameters are optimized, including time duration of the two phases, primary transmission strategies in the two phases and secondary transmission strategy in the second phase. Numerical results show that with the cooperation from the secondary link, the primary link can avoid outage effectively, especially when the number of antennas at the secondary transceiver is large, while the secondary link can achieve a significant rate. Power is another precious resource besides spectrum. Instead of spectrum efficiency, energy-efficient spectrum sharing focuses on the energy efficiency (EE) optimization of the secondary transmission. The EE of the secondary transmission is defined as the ratio of the achievable secondary rate and the secondary power consumption, which includes both the transmit power and the circuit power at the secondary transmitter. For simplicity, the circuit power is modeled as a constant. Specifically, the EE of a MIMO secondary link in underlay spectrum sharing is studied. Three transmission strategies are introduced based on the primary rate requirement and the channel conditions. Rate splitting and successive decoding are deployed at the secondary transmitter and receiver, respectively, when it is feasible, and otherwise single-user decoding is deployed at the secondary receiver. For each case, optimal transmit covariance matrices at the secondary transmitter are obtained, to maximize the EE of the secondary transmission while satisfying the primary rate requirement and the secondary power constraint. Based on this, an energy-efficient resource allocation algorithm is proposed. Numerical results show that MIMO underlay spectrum sharing with EE optimization can achieve a significantly higher EE compared with MIMO underlay spectrum sharing with rate optimization, at certain SNRs and with certain circuit power, at the cost of the achievable secondary rate, while saving the transmit power. With rate splitting at the secondary transmitter and successive decoding at the secondary receiver if feasible, a significantly higher EE can be achieved compared with the case when only single-user decoding is deployed at the secondary receiver. Moreover, the EE of a MIMO secondary link in overlay spectrum sharing is studied, where the secondary transmitter has non-causal knowledge of the primary message and employs DPC to obtain an interference-free secondary link. Energy-efficient precoding and power allocation is obtained to maximize the EE of the secondary transmission while satisfying the primary rate requirement and the secondary power constraint. Numerical results show that MIMO overlay spectrum sharing with EE optimization can achieve a significantly higher EE compared with MIMO overlay spectrum sharing with rate optimization, at certain SNRs and with certain circuit power, at the cost of the achievable secondary rate, while saving the transmit power. MIMO overlay spectrum sharing with EE optimization can achieve a higher EE compared with MIMO underlay spectrum sharing with EE optimization.Aufgrund der rasanten Entwicklung im Bereich der drahtlosen Kommunikation und der ständig steigenden Nachfrage nach mobilen Anwendungen ist die Knappheit von Frequenzbändern ein entscheidender Engpass, der die Einführung neuer Funktechnologien behindert. Die gemeinsame Benutzung von Frequenzen (Spektrum-Sharing) durch primäre und sekundäre Nutzer ist eine Möglichkeit, die Effizienz bei der Verwendung des Spektrums zu verbessern. Bei der Methode des Underlay-Spektrum-Sharing sendet der sekundäre Nutzer zeitgleich mit dem primären Nutzer unter der Einschränkung, dass für den primären Nutzer die erzeugte Interferenz unterhalb eines Schwellwertes liegt oder gewisse Anforderungen an die Datenrate erfüllt werden. In diesem Zusammenhang wird in der Arbeit insbesondere die Koexistenz von Mehrantennensystemen untersucht. Dabei wird für die primäre Funkverbindung der Fall mit mehreren Sendeantennen und einer Empfangsantenne (MISO) angenommen. Für die sekundäre Funkverbindung werden mehrere Sendeantennen und sowohl eine als auch mehrere Empfangsantennen (MISO/MIMO) betrachtet. Der primäre Sender verwendet Maximum-Ratio-Transmission (MRT) und der primäre Empfänger Einzelnutzerdecodierung. Für den sekundären Nutzer werden außerdem am Sender eine Datenratenaufteilung (rate splitting) und am Empfänger entweder eine sukzessive Decodierung – sofern sinnvoll – oder andernfalls eine Einzelnutzerdecodierung verwendet. Im Unterschied zur Methode des Underlay-Spektrum-Sharing kann der sekundäre Nutzer beim Verfahren des Overlay-Spektrum-Sharing die Kenntnis über die Nachrichten des primären Nutzers einsetzen, um die Übertragung sowohl der eigenen als auch der primären Nachrichten zu unterstützen. Das Wissen über die Nachrichten erhält er entweder nicht-kausal, d.h. vor der Übertragung, oder kausal, d.h. während der ersten Phase einer zweistufigen Übertragung. In der Arbeit wird speziell die Koexistenz von primären MISO-Funkverbindungen und sekundären MISO/MIMO-Funkverbindungen untersucht. Bei nicht-kausaler Kenntnis über die primären Nachrichten kann der sekundäre Sender beispielsweise das Verfahren der Dirty-Paper-Codierung (DPC) verwenden, welches es ermöglicht, die Interferenz durch die primären Nachrichten bei der Decodierung der sekundären Nachrichten am sekundären Empfänger aufzuheben. Da die Implementierung der DPC mit einer hohen Komplexität verbunden ist, kommt als Alternative auch eine lineare Vorcodierung zum Einsatz. In beiden Fällen verwendet der primäre Transmitter MRT und der primäre Empfänger Einzelnutzerdecodierung. Besitzt der sekundäre Nutzer keine nicht-kausale Kenntnis über die primären Nachrichten, so kann er als Gegenleistung für die Mitbenutzung des Spektrums dennoch die Übertragung der primären Nachrichten unterstützen. Hierfür leitet er die primären Nachrichten mit Hilfe der Amplify-And-Forward-Methode oder der Decode-And-Forward-Methode in einer zweitstufigen Übertragung weiter, währenddessen er seine eigenen Nachrichten sendet. Der primäre Nutzer passt seine Sendestrategie entsprechend an und kooperiert mit dem sekundären Nutzer, um die Anforderungen an die Datenrate zu erfüllen. Nicht nur das Spektrum sondern auch die Sendeleistung ist eine wichtige Ressource. Daher wird zusätzlich zur Effizienz bei der Verwendung des Spektrums auch die Energieeffizienz (EE) einer sekundären MIMO-Funkverbindung für das Underlay-Spektrum-Sharing-Verfahren analysiert. Wie zuvor wird für den sekundären Nutzer am Sender eine Datenratenaufteilung (rate splitting) und am Empfänger entweder eine sukzessive Decodierung oder eine Einzelnutzerdecodierung betrachtet. Weiterhin wird die EE einer sekundären MIMO-Funkverbindung für das Overlay-Spektrum-Sharing-Verfahren untersucht. Dabei nutzt der sekundäre Nutzer die nicht-kausale Kenntnis über die primären Nachrichten aus, um mittels DPC eine interferenzfreie sekundäre Funkverbindung zu erhalten

ACCESS AND STABILITY ISSUES IN SPECTRUM COMMONS

Ph.DDOCTOR OF PHILOSOPH

Cognitive radio performance optimisation through spectrum availability prediction

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 Engineeringunrestricte

Opportunistic transmitter selection for selfless overlay cognitive radios

We propose an opportunistic strategy to grant channel access to the primary and secondary transmitters in causal selfless overlay cognitive radios over block-fading channels. The secondary transmitter helps the primary transmitter by relaying the primary messages opportunistically, aided by a buffer to store the primary messages temporarily. The optimal channel-aware transmitter- selection strategy is the solution of the maximization of the average secondary rate under the average primary rate requirement and the buffer stability constraints. Numerical results demonstrate the gains of the proposed opportunistic selection strategy. © 2013 IEEE

Unmanned Aerial Vehicle (UAV)-Enabled Wireless Communications and Networking

The emerging massive density of human-held and machine-type nodes implies larger traffic deviatiolns in the future than we are facing today. In the future, the network will be characterized by a high degree of flexibility, allowing it to adapt smoothly, autonomously, and efficiently to the quickly changing traffic demands both in time and space. This flexibility cannot be achieved when the network’s infrastructure remains static. To this end, the topic of UAVs (unmanned aerial vehicles) have enabled wireless communications, and networking has received increased attention. As mentioned above, the network must serve a massive density of nodes that can be either human-held (user devices) or machine-type nodes (sensors). If we wish to properly serve these nodes and optimize their data, a proper wireless connection is fundamental. This can be achieved by using UAV-enabled communication and networks. This Special Issue addresses the many existing issues that still exist to allow UAV-enabled wireless communications and networking to be properly rolled out