ITC/USA 2012 Conference Proceedings / The Forty-Eighth Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2012 / Town and Country Resort & Convention Center, San Diego, California / The Test Resource Management Center's (TRMC) Spectrum Efficient Technologies (SET) S&T program is sponsoring development of the Enhanced Query Data Recorder (EQDR), a network flight recorder that is intended to meet the future needs of the networked telemetry environment. EQDR is designed to support the "fetch" of recorded test data during a test without interrupting the ongoing recording of data from the test article vehicle network. The key benefits of the network data recorder as implemented in EQDR are increased flexibility and efficiency of test in an environment with increasing demands on spectrum available for telemetered data. EQDR enables retrieval of individual recorded parameters on an as-needed basis. Having the flexibility to send data only when it is required rather than throughout the duration of the test significantly increases the efficiency with which limited spectrum resources are used. EQDR enables parametric-level data retrieval, based not only on time interval and data source, but also on the content of the recorded data messages. EQDR enables selective, efficient retrieval of individual parameters using indexes derived from the actual values of recorded data. This paper describes the design of EQDR and the benefits of selective data storage and retrieval in the application of networked telemetry. In addition it describes the performance of the EQDR in terms of data recording and data retrieval rates when implemented on single board computers designed for use in the aeronautical test environment with size, weight, and power constraints.

Emerging 4G standards, such as WiMAX and LTE have adopted the proven technique of Adaptive Modulation and Coding (AMC) to dynamically react to channel fluctuations while maintaining bit-error rate targets of the transmission. This scheme makes use of the estimated channel state indication (CSI) to efficiently utilize channel capacity for next transmission, but it brings with it the stale CSI problem due to the frequently channel fluctuations. As its objective, this thesis focuses on mitigating the vicious effect of stale CSI by proposing a novel framework that incorporate AMC with layered transmission through Superposition Coding (SPC) is introduced. A layered multi-step finite-state Markov chain model (FSMC) is developed under this framework, to effectively assist the system in selecting the optimal modulation and coding scheme as well as the power allocated for each layer in every multi-resolution unicast transmission. Extensive simulations are conducted to verify the proposed framework and compare its performance with other counterparts. The effects of changing key parameters, such as the complexity factor and step size, are also investigated to get close to real world performance. Results demonstrate that the proposed framework can achieve better spectrum efficiency than similar counterparts, due to its improved robustness to the stale CSI problem for each multi-resolution modulated transmission, also these show that the performance of two-layer scheme is good enough for layer allocation, without need of more layers.

In this thesis, the spectrum and energy efficiency of cooperative spectrum prediction (CSP) in cognitive radio networks are investigated. In addition, the performance of CSP is evaluated using a hidden Markov model (HMM) and a multilayer perceptron (MLP) neural network. The cooperation between secondary users in predicting the next channel status employs AND, OR and majority rule fusion schemes. These schemes are compared for HMM and MLP predictors as a function of channel occupancy in terms of prediction error, spectrum efficiency and energy efficiency. The impact of busy and idle state prediction errors on the spectrum efficiency is determined. Further, the spectrum efficiency is compared for different numbers of primary users (PUs). Simulation results are presented which show a significant improvement in the spectrum efficiency using CSP with the majority rule at the cost of a small degradation in energy efficiency compared to single spectrum prediction (SSP) and traditional spectrum sensing (TSS). The HMM predictor provides better performance than the MLP predictor. Moreover, the total probability of prediction error with the majority rule provides the best performance compared to SSP and the other fusion rules. On the other hand, the AND and OR rules have the worst performance in the high and low traffic cases, respectively. The majority rule provides a good tradeoff between busy and idle state prediction errors compared with the AND and OR rules and SSP. Further, a reduction in the busy state prediction error increases the SE more compared to a reduction in the idle state prediction error. / Graduate

Wireless communication systems are growing at an unprecedented pace, making the wireless spectrum at a premium, especially as billions of new Internet-of-Things (IoT) devices worldwide are demanding wireless connections. To accommodate the ever-growing spectrum demand, a promising solution is Non-Orthogonal Multiple Access (NOMA) that enables two users to communicate with the same spectrum resource at the same time, while decoding the two-user superimposed signal at the receiver. By doing this, the previously detrimental wireless interference caused by two concurrent transmitters becomes decodable at the receiver, potential for higher utilization of the wireless spectrum. Existing NOMA technologies, however, rely on strict power control to sequentially decode the two-user superimposed signal, which is infeasible for many IoT devices that are heterogeneous and often low-cost. In contrast, in this dissertation, we propose new NOMA schemes that are designed for wireless communication systems and can decode the two-user superimposed signals without power control. This dissertation makes four major contributions. First, it presents the first design to implement dynamic signal offsets tracking and reacting schemes to detect and decode two-user superimposed signals, robust against hardware imperfections and feasible for heterogeneous IoT devices. Second, by investigating the relationship between the channel condition and the bit-error-rate (BER) in decoding superimposed signals, we design a reliable NOMA scheme to combat dynamic channel conditions that are inevitable in many practical scenarios and may cause severe decoding errors. Third, considering the wireless communication systems in mobile scenarios, mobility is a vital feature of many applications but can cause severe signal variations and make the hardware offsets harder to predict, resulting in an unreliable decoding performance. To address this, we develop a diversity transmission and smart combining scheme to achieve high reliable decoding performance. Finally, we combine rotation coding to transmit and decode the superimposed signal to achieve both high spectrum efficiency and high reliability performance. To demonstrate our contributions, we derive the theoretical relationship of the BER under different practical settings, validate the performance with simulations, and conduct experiments using software-defined radio based platforms with static indoor, outdoor scenarios and mobile scenarios. The experimental results demonstrate that, compared with the state-of-the-art methods, our schemes can achieve higher reliability and spectrum efficiency in decoding the superimposed signal for wireless communication systems without power control. / Graduate

We are in the midst of a major paradigm shift in how we manage the radio spectrum. This paradigm shift in spectrum management from exclusive access to shared access is necessitated by the growth of wireless services and the demand pressure imposed on limited spectrum resources under legacy management regimes. The primary constraint in any spectrum sharing regime is that the incumbent users (IUs) of the spectrum need to be protected from harmful interference caused due to transmissions from secondary users (SUs). Unfortunately, legacy techniques rely on inadequately flexible and overly conservative methods for prescribing interference protection that result in inefficient utilization of the shared spectrum. In this dissertation, we first propose an analytical approach for characterizing the aggregate interference experienced by the IU when it shares the spectrum with multiple SUs. Proper characterization of aggregate interference helps in defining incumbent protection boundaries, a.k.a. Exclusion Zones (EZs), that are neither overly aggressive to endanger the IU protection requirement, nor overly conservative to limit spectrum utilization efficiency. In particular, our proposed approach addresses the two main limitations of existing methods that use terrain based propagation models for estimating the aggregate interference. First, terrain-based propagation models are computationally intensive and data-hungry making them unsuitable for large real-time spectrum sharing applications such as the spectrum access system (SAS). Second, terrain based propagation models require accurate geo-locations of SUs which might not always be available, such as when SUs are mobile, or when their locations are obfuscated for location privacy concerns. Our second contribution in this dissertation is the novel concept of Multi-tiered Incumbent Protection Zones (MIPZ) that can be used to prescribe interference protection to the IUs. Based on the aforementioned analytical tool for characterizing the aggregate interference, we facilitate a framework that can be used to replace the legacy notion of static and overly conservative EZs with multi-tiered dynamic EZs. MIPZ is fundamentally different from legacy EZs in that it dynamically adjusts the IU's protection boundary based on the radio environment, network dynamics, and the IU interference protection requirement. Our extensive simulation results show that MIPZ can be used to improve the overall spectrum utilization while ensuring sufficient protection to the IUs. As our third contribution, we investigate the operational security (OPSEC) issue raised by the emergence of new spectrum access technologies and spectrum utilization paradigms. For instance, although the use of geolocation databases (GDB) is a practical approach for enabling efficient spectrum sharing, it raises a potentially serious OPSEC problem, especially when some of the IUs are federal government entities, including military users. We show that malicious queriers can readily infer the locations of the IUs even if the database's responses to the queries do not directly reveal such information. To address this issue, we propose a perturbation-based optimal obfuscation strategy that can be implemented by the GDB to preserve the location privacy of IUs. The proposed obfuscation strategy is optimal in the sense that it maximizes IUs' location privacy while ensuring that the expected degradation in the SUs' performance due to obfuscated responses does not exceed a threshold. In summary, this dissertation focuses on investigating techniques that improve the utilization efficiency of the shared spectrum while ensuring adequate protection to the IUs from SU induced interference as well as from potential OPSEC threats. We believe that this study facilitates the regulators and other stakeholders a better understanding of mechanisms that enable improved spectrum utilization efficiency and minimize the associated OPSEC threats, and hence, helps in wider adoption of dynamic spectrum sharing. / Ph. D.

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.

The main topic of this thesis is based on multiple-input multiple-output (MIMO) wireless communications, which is a novel technology that has attracted great interest in the last twenty years. Conventional MIMO systems using up to eight antennas play a vital role in the urban cellular network, where the deployment of multiple antennas have significantly enhanced the throughput without taking extra spectrum or power resources. The massive MIMO systems “scales” up the benefits that offered by the conventional MIMO systems. Using sixty four or more antennas at the BS not only improves the spectrum efficiency significantly, but also provides additional link robustness. It is considered as a key technology in the fifth generation of mobile communication technology standards network, and the design of new algorithms for these two systems is the basis of the research in this thesis. Firstly, at the receiver side of the conventional MIMO systems, a general framework of bit error rate (BER) approximation for the detection algorithms is proposed, which aims to support an adaptive modulation scheme. The main idea is to utilize a simplified BER approximation scheme, which is based on the union bound of the maximum-likelihood detector (MLD), whereby the bit error rate (BER) performance of the detector for the varying channel qualities can be efficiently predicted. The K-best detector is utilized in the thesis because its quasi- MLD performance and the parallel computational structure. The simulation results have clearly shown the adaptive K-best algorithm, by applying the simplified approximation method, has much reduced computational complexity while still maintaining a promising BER performance. Secondly, in terms of the uplink channel estimation for the massive MIMO systems with the time-division-duplex operation, the performance of the Grassmannian line packing (GLP) based uplink pilot codebook design is investigated. It aims to eliminate the pilot contamination effect in order to increase the downlink achievable rate. In the case of a limited channel coherence interval, the uplink codebook design can be treated as a line packing problem in a Grassmannian manifold. The closed-form analytical expressions of downlink achievable rate for both the single-cell and multi-cell systems are proposed, which are intended for performance analysis and optimization. The numerical results validate the proposed analytical expressions and the rate gains by using the GLP-based uplink codebook design. Finally, the study is extended to the energy efficiency (EE) of the massive MIMO system, as the reduction carbon emissions from the information and communication technology is a long-term target for the researchers. An effective framework of maximizing the EE for the massive MIMO systems is proposed in this thesis. The optimization starts from the maximization of the minimum user rate, which is aiming to increase the quality-of-service and provide a feasible constraint for the EE maximization problem. Secondly, the EE problem is a non-concave problem and can not be solved directly, so the combination of fractional programming and the successive concave approximation based algorithm are proposed to find a good suboptimal solution. It has been shown that the proposed optimization algorithm provides a significant EE improvement compared to a baseline case.

本文取徑經濟學的公共財概念，試圖從此一角度出發探討頻譜管理從「稀有論」轉向「公有論」的論述正當性，並釐清管理模式與財貨特性之關連。根據研究結果，頻譜資源的原始狀態雖符合公共財定義，但並非任何人所有，其財貨特性會隨著科技發展和法律制度而變動，因此「頻譜公有」的論述並未獲得專家學者支持。 儘管如此，頻譜資源在運用上需避免使用者相互干擾，因此建立一套合理的使用秩序，方能促使資源發揮效用。針對提供商業服務之頻譜，本文建議主管機關在規劃與指配上應給予使用者更多彈性，以類似出租國有地的方式，視頻譜資源為獨立客體並制訂相關法律；其次為放寬技術與用途限制，並在釋出資源後開放頻譜二次交易，讓分配效率得以提升。 長期而言，無線通訊科技將不斷演化，當干擾問題可獲得妥善解決，為追求資源使用效率，本文建議管理模式應朝開放共享的方向邁進。簡言之，「頻譜管理」任務本身就是一種公共服務，政府責無旁貸，唯有充分掌握頻譜資源的供給與需求變化，施政方針才能充分反應使用者需求。 / This research argues that the scarcity rationale could be replaced by public spectrum rationale. The research results show that although the nature of spectrum resource is public good by economic definition, it doesn’t mean the resources are owned by the public. Therefore, the ownership of resources should be clearly defined under the law to prevent users from interfering with each other. For spectrum used in private sector, the allocative efficiency is important for some valuable blocks of spectrum such as 800MHz, 900MHz, 1800MHz, 2600MHz. To improve allocative efficiency, the research result suggest that the government could legislate specific laws on spectrum management, while allowing users to decide how they want to make use of the resources. In the long run, wireless communication technology will keep developing. As long as signal interference can be controlled under specific conditions, spectrum sharing including common regime and license-exempt use should be adopted. A government plays the key role which not only provides management service but should also have a systematic plan for improving spectrum efficiency.

Avec le besoin croissant en bande-passante, les technologies dites de radio-cognitive sont de plus en plus étudiées par la communauté scientifique. L’enjeu est d’utiliser au mieux le spectre disponible. L'une de ces technologies, Transform Domain Communication System (TDCS), dont les performances en termes d’efficacité énergétique et spectrale étaient jusqu'à présent méconnues, constitue le sujet d'étude de cette thèse. Après une présentation du contexte scientifique et industriel de la thèse, le système TDCS est introduit, ainsi que ses similarités et différences avec OFDM et MC-CDMA. Le système est ensuite décrit sous le formalisme algébrique des modulations linaires. Cela a permis d’établir une expression de l’efficacité spectrale du système. Plusieurs techniques sont alors proposées pour améliorer celle-ci tout en améliorant, dans certains cas, le taux d’erreur binaire. Étant composé d’un de plusieurs composantes sinusoïdales, le signal TDCS souffre d’un fort Peak-to-Average Power Ratio (PAPR). La théorie ensembliste est alors présentée puis mise à profit en troisième partie de cette thèse pour proposer les algorithmes Douglas-Rachford et ROCS de réduction du PAPR des signaux TDCS. Ces algorithmes convergent plus rapidement et vers des valeurs plus basses que l’algorithme POCS précédemment utilisé dans la littérature / For about ten years, spectrum scarcity and the growing need of bandwidth have pushed the studies on cognitive-radio technologies to counter this waste. Among them: the Transform Domain Communication System (TDCS), on which this thesis focuses. Until now, TDCS’ performance in terms of spectral and power efficiency was largely unknown. After introducing the thesis’ industrial and scientific context, the TDCS is introduced and compared with popular technologies such as OFDM and MC-CDMA. The system is then studied by means of the linear modulations’ algebraic framework. This has led to the TDCS’ spectral efficiency determination and to new design rules to jointly achieve a better spectral efficiency and a lower BER. Several methods are then proposed to further increase the spectral efficiency by means of a dense multidimensional modulation. Since a TDCS signal is made of several sines, it suffers from a strong Peak-to-Average Power Ratio (PAPR). Set theoretic estimation is then introduced in a third part and new PAPR-reduction algorithms such as Douglas-Rachford and Reflection Onto Convex Sets are brought to light and achieve better performance than the usual POCS algorithm regarding to the convergence rate, as well as the achieved PAPR

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.