Spectrum access protocols have been proposed recently to provide flexible and efficient use of the available bandwidth. Game theory has been applied to the analysis of the problem to determine the most effective allocation of the users’ power over the bandwidth. However, prior analysis has focussed on Shannon capacity as the utility function, even though it is known that real signals do not, in general, meet the Gaussian distribution assumptions of that metric. In a non-cooperative spectrum sharing environment, the Shannon capacity utility function results in a water-filling solution. In this thesis, the suitability of the water-filling solution is evaluated when using non-Gaussian signalling first in a frequency non-selective environment to focus on the resource allocation problem and its outcomes. It is then extended to a frequency selective environment to examine the proposed algorithm in a more realistic wireless environment. It is shown in both scenarios that more effective resource allocation can be achieved when the utility function takes into account the actual signal characteristics. Further, it is demonstrated that higher rates can be achieved with lower transmitted power, resulting in a smaller spectral footprint, which allows more efficient use of the spectrum overall. Finally, future spectrum management is discussed where the waveform adaptation is examined as an additional option to the well-known spectrum agility, rate and transmit power adaptation when performing spectrum sharing.

Spectrum access protocols have been proposed recently to provide flexible and efficient use of the available bandwidth. Game theory has been applied to the analysis of the problem to determine the most effective allocation of the users’ power over the bandwidth. However, prior analysis has focussed on Shannon capacity as the utility function, even though it is known that real signals do not, in general, meet the Gaussian distribution assumptions of that metric. In a non-cooperative spectrum sharing environment, the Shannon capacity utility function results in a water-filling solution. In this thesis, the suitability of the water-filling solution is evaluated when using non-Gaussian signalling first in a frequency non-selective environment to focus on the resource allocation problem and its outcomes. It is then extended to a frequency selective environment to examine the proposed algorithm in a more realistic wireless environment. It is shown in both scenarios that more effective resource allocation can be achieved when the utility function takes into account the actual signal characteristics. Further, it is demonstrated that higher rates can be achieved with lower transmitted power, resulting in a smaller spectral footprint, which allows more efficient use of the spectrum overall. Finally, future spectrum management is discussed where the waveform adaptation is examined as an additional option to the well-known spectrum agility, rate and transmit power adaptation when performing spectrum sharing.

For traditional wireless communication systems, static spectrum allocation is the major spectrum allocation methodology. However, according to the recent investigations by the FCC, this has led to more than 70 percent of the allocated spectrum in the United States being under-utilized. Cognitive radio (CR) technology, which supports opportunistic spectrum sharing, is one idea that is proposed to improve the overall utilization efficiency of the radio spectrum. In this thesis we consider a CR communication system based on spectrum sharing schemes, where we have a secondary user (SU) link with multiple transmitting antennas and a single receiving antenna, coexisting with a primary user (PU) link with a single receiving antenna. At the SU transmitter (SU-Tx), the channel state information (CSI) of the SU link is assumed to be perfectly known; while the interference channel from the SU-Tx to the PU receiver (PU-Rx) is not perfectly known due to less cooperation between the SU and the PU. As such, the SU-Tx is only assumed to know that the interference channel gain can take values from a finite set with certain probabilities. Considering a SU transmit power constraint, our design objective is to determine the transmit covariance matrix that maximizes the SU rate, while we protect the PU by enforcing both a PU average interference constraint and a PU outage probability constraint. This problem is first formulated as a non-convex optimization problem with a non-explicit probabilistic constraint, which is then approximated as a mixed binary integer programming (MBIP) problem and solved with the Branch and Bound (BB) algorithm. The complexity of the BB algorithm is analyzed and numerical results are presented to validate the eff ectiveness of the proposed algorithm. A key result proved in this thesis is that the rank of the optimal transmit covariance matrix is one, i.e., CR beamforming is optimal under PU outage constraints. Finally, a heuristic algorithm is proposed to provide a suboptimal solution to our MBIP problem by efficiently (in polynomial time) solving a particularly-constructed convex problem.

The wireless spectrum is currently regulated by government agencies and is assigned to license holders or services on a long-term basis over vast geographical regions. Recent research has shown that a large portion of the assigned spectrum is used sporadically, leading to underutilization and waste of valuable frequency resources. Consequently, dynamic spectrum access techniques are proposed to solve these current spectrum inefficiency problems. This new area of research foresees the development of cognitive radio (CR) networks to further improve spectrum efficiency. The basic idea of CR networks is that the unlicensed devices (also called CR users) share wireless channels with the licensed devices (also known as primary users) that are already using an assigned spectrum. CR networks, however, impose unique challenges resulting from high fluctuation in the available spectrum, as well as diverse quality-of-service (QoS) requirements. These challenges necessitate novel cross-layer techniques that simultaneously address a wide range of communication problems from radio frequency (RF) design to communication protocols, which can be realized through spectrum management functions as follows: (1) determine the portions of the spectrum currently available (spectrum sensing), (2) select the best available channel (spectrum decision), (3) coordinate access to this channel with other users (spectrum sharing), and (4) effectively vacate the channel when a primary user is detected (spectrum mobility). In this thesis, a spectrum management framework for CR networks is investigated that enables seamless integration of CR technology with existing networks. First, an optimal spectrum sensing framework is developed to achieve maximum spectrum opportunities while satisfying interference constraints, which can be extended to multi-spectrum/multi-user CR networks through the proposed sensing scheduling and adaptive cooperation methods. Second, a QoS-aware spectrum decision framework is proposed where spectrum bands are determined by considering the application requirements as well as the dynamic nature of the spectrum bands. Moreover, a dynamic admission control scheme is developed to decide on the spectrum bands adaptively dependent on the time-varying CR network capacity. Next, for spectrum sharing in infrastructure-based CR networks, a joint spectrum and power allocation scheme is proposed to achieve fair resource allocation as well as maximum capacity by opportunistically negotiating additional spectrum based on the licensed user activity (exclusive allocation) and having a share of reserved spectrum for each cell (common use sharing). Finally, we propose a novel CR cellular network architecture based on the spectrum-pooling concept, which mitigates the heterogeneous spectrum availability. Based on this architecture, a unified mobility management framework is devised to support both user and spectrum mobilities in CR networks.

As resources are limited, radio spectrum becomes congested due to the growth of wireless applications. However, measurements address the fact that most of the licensed spectrums experience low utilization even in intensively teeming areas. In the exertion to improve the utilization of the limited spectrum resources, cognitive radio networks have emerged as a powerful technique to resolve this problem. There are two types of user in cognitive radio networks (CRNs) named as primary user (PU) and secondary user (SU). Therein, the CRN enables the SU to utilize the unused licensed frequency of the PU if it possibly finds the vacant spectrum or white space (known as opportunistic spectrum access). Alternatively, SU can transmit simultaneously with the PU provided that transmission power of SU does not cause any harmful interference to the PU (known as spectrum sharing systems). In this thesis work, we study fundamental knowledge of the CRNs and focus on the performance analysis of the single input multiple output (SIMO) system for spectrum sharing approach. We assume that a secondary transmitter (SU-Tx) has full channel state information (CSI). The SU-Tx can adjust its transmit power not to cause harmful interference to the PU and obtain an optimal transmit rate. In particular, we derive the closed-form expressions for the cumulative distribution function (CDF), outage probability and an analytical expression for symbol error probability (SEP). / As resources are limited, radio spectrum becomes congested due to the growth of wireless applications. However, measurements address the fact that most of the licensed spectrums experience low utilization even in intensively teeming areas. In the exertion to improve the utilization of the limited spectrum resources, cognitive radio networks have emerged as a powerful technique to resolve this problem. There are two types of user in cognitive radio networks (CRNs) named as primary user (PU) and secondary user (SU). Therein, the CRN enables the SU to utilize the unused licensed frequency of the PU if it possibly finds the vacant spectrum or white space (known as opportunistic spectrum access). Alternatively, SU can transmit simultaneously with the PU provided that transmission power of SU does not cause any harmful interference to the PU (known as spectrum sharing systems). In this thesis work, we study fundamental knowledge of the CRNs and focus on the performance analysis of the single input multiple output (SIMO) system for spectrum sharing approach. We assume that a secondary transmitter (SU-Tx) has full channel state information (CSI). The SU-Tx can adjust its transmit power not to cause harmful interference to the PU and obtain an optimal transmit rate. In particular, we derive the closed-form expressions for the cumulative distribution function (CDF), outage probability and an analytical expression for symbol error probability (SEP). / Iqbal Hasan Haider, cell: +46704571807 MD. Fazla Rabby, cell: +46734965477

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This dissertation considers gray-space primary-secondary spectrum sharing, in which secondary devices are allowed to transmit when primary transmissions are strong enough that additional interference would be tolerable, rather than when the primary transmissions are weak or absent so the spectrum is considered unused, as occurs in white-space sharing. To avoid causing harmful interference (i.e., interference causing disruptions in services), transmit power of a secondary device is dynamically adjusted. Various novel sharing mechanisms are proposed for two different types of primary system: cellular systems, and rotating radars. Both cases when primary and secondary systems cooperate (cooperative sharing), and when they do not (coexistent sharing) are considered. Based on analyses and extensive Monte Carlo simulations, this dissertation shows that useful secondary transmissions are possible even when the shared spectrum is considered 100% utilized by the primary system under conventional approaches to spectrum management. For example, in spectrum sharing with cellular systems, even when the primary system is 100% utilized, a modest extent of transmissions of around 0.01–0.03 bps/Hz is achievable for secondary transmitter and receiver that are 400 m apart. In spectrum sharing with radars, even in the scenario where radars are the most densely packed, a secondary transmitter can get almost 1.2 bps/Hz on average, when 5% of the transmitters are competing for the shared spectrum. This dissertation also shows the potential of sharing models in which a secondary system has information about a primary system, but does not cooperate in real time; such arrangements are not typically considered today. For sharing with radars, the case in which an OFDMA-based cellular system operates as the secondary spectrum-user in non-contiguous cells is considered, as might occur with a broadband hotspot service, or a cellular system using shared spectrum to supplement its dedicated spectrum. It is found that even with fluctuations and interruptions in secondary transmissions while radars rotate, the shared spectrum could be used efficiently for applications that generate much of the traffic on mobile Internet, including non-interactive video on demand, peer-to-peer file sharing, large file transfers, and web browsing, but not for applications such as real-time transfers of small files, and VoIP. For sharing with cellular systems, the efficiency of cooperative and coexistent sharing is compared based on performance of the secondary system measured as achievable transmissions, and performance of the cellular system measured as power consumption of a mobile device, which may be increased to compensate for additional interference from secondary transmissions. When both achievable secondary transmissions and primary power consumption are of concern, coexistent sharing is found to be as effective as cooperative sharing.

Spectrum access protocols have been proposed recently to provide flexible and efficient use of the available bandwidth. Game theory has been applied to the analysis of the problem to determine the most effective allocation of the users’ power over the bandwidth. However, prior analysis has focussed on Shannon capacity as the utility function, even though it is known that real signals do not, in general, meet the Gaussian distribution assumptions of that metric. In a non-cooperative spectrum sharing environment, the Shannon capacity utility function results in a water-filling solution. In this thesis, the suitability of the water-filling solution is evaluated when using non-Gaussian signalling first in a frequency non-selective environment to focus on the resource allocation problem and its outcomes. It is then extended to a frequency selective environment to examine the proposed algorithm in a more realistic wireless environment. It is shown in both scenarios that more effective resource allocation can be achieved when the utility function takes into account the actual signal characteristics. Further, it is demonstrated that higher rates can be achieved with lower transmitted power, resulting in a smaller spectral footprint, which allows more efficient use of the spectrum overall. Finally, future spectrum management is discussed where the waveform adaptation is examined as an additional option to the well-known spectrum agility, rate and transmit power adaptation when performing spectrum sharing.

Recently, massive multiple-input multiple-output (MIMO) systems have gained significant attention as a new network architecture to not only achieving unprecedented spectral and energy efficiencies, but also to alleviating propagation losses and inter-user/inter-cell interference. Therefore, massive MIMO has been identified as one of the key candidate technologies for the 5th generation wireless standard. This dissertation thus focuses on (1) developing a performance analysis framework for cognitive massive MIMO systems by investigating the uplink transmissions of multi-cell multi-user massive MIMO secondary systems, which are underlaid in multi-cell multi-user primary massive MIMO systems, with taking into consideration the detrimental effects of practical transmission impairments, (2) proposing a new wireless-powered underlay cognitive massive MIMO system model, as the secondary user nodes is empowered by the ability to efficiently harvest energy from the primary user transmissions, and then access and utilize the primary network spectrum for information transmission, and (3) developing a secure communication strategy for cognitive multi-user massive MIMO systems, where physical layer secure transmissions are provisioned for both primary and secondary systems by exploiting linear precoders and artificial noise (AN) generation in order to degrade the signal decodability at eavesdropper. The key design feature of the proposed cognitive systems is to leverage the spatial multiplexing strategies to serve a large number of spatially distributed user nodes by using very large numbers of antennas at the base-stations. Moreover, the fundamental performance metrics, the secondary transmit power constraints, which constitute the underlay secondary transmissions subject to a predefined primary interference temperature, and the achievable sum rates of the primary and secondary systems, are characterized under different antenna array configurations. Additionally, the detrimental impact of practical wireless transmission impairments on the performance of the aforementioned systems are quantified. The important insights obtained throughout these analyses can be used as benchmarks for designing practical cognitive spectrum sharing networks.

The broadcast nature of wireless medium has made information security as one of the most important and critical issues in wireless systems. Physical layer security, which is based on information-theoretic secrecy concepts, can be used to secure the wireless channels by exploiting the noisiness and imperfections of the channels. Massive multiple-input multiple-output (MIMO) systems, which are equipped with very large antenna arrays at the base stations, have a great potential to boost the physical layer security by generating the artificial noise (AN) with the exploitation of excess degrees-of-freedom available at the base stations. In this thesis, we investigate physical layer security provisions in the presence of passive/active eavesdroppers for single-hop massive MIMO, dual-hop relay-assisted massive MIMO and underlay spectrum-sharing massive MIMO systems. The performance of the proposed security provisions is investigated by deriving the achievable rates at the user nodes, the information rate leaked into the eavesdroppers, and the achievable secrecy rates. Moreover, the effects of active pilot contamination attacks, imperfect channel state information (CSI) acquisition at the base-stations, and the availability of statistical CSI at the user nodes are quantified. The secrecy rate/performance gap between two AN precoders, namely the random AN precoder and the null-space based AN precoder, is investigated. The performance of hybrid analog/digital precoding is compared with the full-dimensional digital precoding. Furthermore, the physical layer security breaches in underlay spectrum-sharing massive MIMO systems are investigated, and thereby, security provisions are designed/analyzed against active pilot contamination attacks during the channel estimation phase. A power-ratio based active pilot attack detection scheme is investigated, and thereby, the probability of detection is derived. Thereby, the vulnerability of uplink channel estimation based on the pilots transmitted by the user nodes in time division duplexing based massive MIMO systems is revealed, and the fundamental trade-offs among physical layer security provisions, implementation complexity and performance gains are discussed.