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

State of the Art, Taxonomy, and Open Issues on Cognitive Radio Networks with NOMA

The explosive growth of mobile devices and the rapid increase of wideband wireless services call for advanced communication techniques that can achieve high spectral efficiency and meet the massive connectivity requirement. Cognitive radio (CR) and non-orthogonal multiple access (NOMA) are envisioned to be important solutions for the fifth generation wireless networks. Integrating NOMA techniques into CR networks (CRNs) has the tremendous potential to improve spectral efficiency and increase the system capacity. However, there are many technical challenges due to the severe interference caused by using NOMA. Many efforts have been made to facilitate the application of NOMA into CRNs and to investigate the performance of CRNs with NOMA. This article aims to survey the latest research results along this direction. A taxonomy is devised to categorize the literature based on operation paradigms, enabling techniques, design objectives and optimization characteristics. Moreover, the key challenges are outlined to provide guidelines for the domain researchers and designers to realize CRNs with NOMA. Finally, the open issues are discussed.Comment: This paper has been accepted by IEEE Wireless Communications Magazine. Pages 16, Figures

An optimized power allocation algorithm for cognitive radio NOMA communication

The primary objective of cognitive radio network is to effectively utilize the unused spectrum bands. In cognitive radio networks, spectrum sharing between primary and secondary users is accomplished using either underlay or interweave cognitive radio approach. Non orthogonal multiple access (NOMA) is the proven technology in the present wireless developments, which allows the coexistence of multiple users in the same orthogonal block. The new paradigm cognitive radio NOMA (CR-NOMA) is one of the potential solutions to fulfill the demands of future wireless communication. This paper emphasizes on practical implementation of NOMA in cognitive radio networks to enhance the spectral efficiency. The goal is to increase the throughput of the secondary users satisfying the quality of service (QOS) requirements of primary users. To achieve this, we have presented the optimized power allocation strategy for underlay downlink scenario to support the simultaneous transmission of primary and secondary users. Furthermore, we have proposed QOS based power allocation scheme for CR-NOMA interweave model to support the coexistence of multiple secondary networks. Also, the changes adopted in implementing superposition coding (SC) and successive interference cancellation (SIC) for CR-NOMA are highlighted. Finally, simulation results validate the mathematical expressions that are derived for power allocation coefficient and outage probability