In recent years, the wireless data traffic grew exponentially, which was further accompanied by an increasing demand for higher data rates. Towards this aim, Terahertz band (0.1-10 THz) communication is envisioned as one of the key wireless technologies of the next decade. The THz band will help to overcome the spectrum scarcity problems and capacity limitations of current wireless networks, by providing an unprecedentedly large bandwidth. In addition, THz band communication will enable a plethora of long-awaited applications ranging from instantaneous massive data transfer among nearby devices in ultra-high-speed wireless personal and local area networks, to ultra-high-definition content streaming over mobile devices in 5G and beyond small cells. The objective of the thesis is to establish the physical layer foundations of the ultra- broadband communication in the THz band. First, a unified multi-path propagation channel is modeled in the THz band, based on ray-tracing techniques. The wideband characterization are analyzed, which include the distance-varying spectral windows, the delay spread, the wideband capacity and the temporal broadening effects. Second, a multi-wideband waveform design for the THz band is proposed to improve the distance and support ultra- high-speed transmissions. Third, two algorithms for timing acquisition in the pulse-based wireless systems are developed, namely the low-sampling-rate (LSR) algorithm, and the maximum likelihood (ML)-based approach. Fourth, the distance-aware bandwidth resource allocation schemes for the single-user and multi-user THz band networks are developed. Fifth, a three-dimensional (3-D) end-to-end model is developed and characterized, which includes the responses of the graphene-based reflectarray antenna and the 3-D multi-path propagation. The provided physical layer analysis in this thesis lays out the foundation for reliable and efficient ultra-high-speed wireless communications in the THz band.

Cooperative Spectrum Sensing (CSS) allows Cognitive Radio Networks (CRNs) to locate vacant spectrum channels and to protect active Primary Users (PUs). However, the achieved detection accuracy is proportional to the duration of the CSS process which, unfortunately, reduces the time of useful communication as well as increases the Co-Channel Interference (CCI) perceived by an active PU. To overcome this, this thesis proposes three CSS strategies, namely the Dual-Threshold CSS (DTCSS), the Maximum CSS (MCSS), and the Max-Min CSS (MMCSS). These strategies reduce the number of reporting terminals while maintaining reliable performance and minimal CCI e ect. The performance of these three methods is analyzed, and the numerical and simulations results illustrate the accuracy of the derived results as well as the achieved performance gains. The second part of this thesis studies the impact of CCI on the performance of a number of transmission techniques used by CRNs. These are Chase combining Hybrid Automatic Repeat Request (HAQR), Fixed Relaying (FR), Selective Relaying (SR), Incremental Relaying (IR), and Selective Incremental Relaying (SIR). The performance of these techniques is studied in terms of the average spectral e ciency, the outage probability, and the error probability. To obtain closed forms for the error probabilities, this thesis proposes a novel accurate approximation of the exponential integral function using a sum of exponentials. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2013-02-05 13:39:22.35

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Next Generation Wireless Networks (NGWNs) are envisaged to be heterogeneous. They will integrate multiple Radio Access Technologies (RATs) on the same platform where the RAT s are expected to work together in a coordinated fashion. Radio resources will therefore be jointly managed. Joint Call Admission Control (JCAC) approach has been adopted to jointly allocate or handle the radio resources amongst the different RATs in an NGWN. A number of JCAC algorithms have been proposed in the literature with the objective of enabling efficient utilisation of the radio resources and ensuring that required QoS requirements are met . However, studies in JCAC have not typically considered the revenue obtained by network operators in NGWNs . With the implementation of NGWNs, user demand for network services is expected to significantly increase. Consequently, one of the challenges envisaged in the NGWNs for network operators is a large decoupling between users' traffic and the revenue obtained . Therefore, it is important to analyse the network operators' revenue in NGWN s and devise means to ensure that sufficient revenue is obtained. This research analyses network operators' revenue in a heterogeneous network environment while maintaining QoS by incorporating pricing in JCAC. An analytical model based on a multi-dimensional Markov decision process is used to model JCAC algorithm in an NGWN. The JCAC algorithm used is load-based whereby calls arriving in the network are admitted to the least loaded RATs. The performance of the algorithm is evaluated using MATLAB. The analysed NGWN consists of two RATs and two service classes. QoS performance is measured with connection-level QoS metrics namely call blocking probability and call dropping probability. Other investigated performance metrics are average number of calls in the systems, user utility and revenue obtained. Performance of the NGWN is carried out with a dynamic pricing scheme incorporated in JCAC. A discount approach is applied to determine new price under the dynamic pricing scheme. User behaviour with price variation is impacted by change of call arrival rate and average call duration. Simulations are also carried out with flat pricing for comparison purposes. The results obtained show that better system performance and high revenue for network operators are obtained with the dynamic pricing scheme. Furthermore, a hybrid pricing model is proposed whereby flat and dynamic pricing schemes are integrated, giving users flexibility of choosing an appropriate pricing scheme. The analysis is conducted with different percentages of users opting for either dynamic or flat pricing schemes. Simulation results show that higher user utility and improved QoS performance are obtained with the hybrid pricing model. Additionally, reasonable operators' revenue is guaranteed with the hybrid pricing model.

Yes / In this research work, a planar crossed exponentially tapered slot antenna with a multi-resonance function is introduced. The presented antenna design is ascertained on a low-cost Rogers 5870 dielectric with a circular schematic. The antenna is designed to support several frequency spectrums of the current and future wireless communications. The configuration of the design contains a pair of crossed exponentially tapered slots intersected by a star-shaped slot in the back layer and a bowtie-shaped radiation stub with a discrete feeding point extended among the stub parts. The crossed exponential slots exhibit a wide impedance, and the star slot generates an extra resonance at the upper frequencies. For S11 ≤ -6, the antenna provides a wide operation band of 1.7 to 5.9 GHz supporting several frequency bands of 3G, 4G, and 5G communication. The fundamental characteristics of the proposed slot radiator are studied, and good performances have been achieved. / European Union’s Horizon 2020 research and innovation programme under grant agreement H2020-MSCA-ITN-2016 SECRET-722424.

Cognitive Radio (CR) is considered to be a novel approach to improve the underutilization of precious radio resources by exploiting the unused licensed spectrum in dynamically changing environments. Designing efficient resource allocation algorithms for dynamic spectrum sharing and for power allocation in OFDM-CR networks is still a challenging problem. In this thesis, we specifically deal with these two problems. Dynamic spectrum sharing for the unlicensed secondary users (SU)s with device coordination could minimize the wastage of the spectrum. But this is a feasible approach only if the network considers the fairness criterion. We study the dynamic spectrum sharing problem for device coordinated cognitive radio networks with respect to fairness. We propose a simple modified proportional fair algorithm for a dynamic spectrum sharing scenario with two constraints, time and utility. Utility is measured by the amount of data processed and time is measured as the duration of a slot. This algorithm could result in variable or fixed length time slots. We will discuss the several controls possible on the algorithm and the possible extension of this algorithm for multicarrier OFDM based CR systems. Traditional water-filling algorithm is inefficient for OFDM-CR networks due to the interaction with primary users (PU)s. We consider reliability/availability of subcarriers or primary user activity for power allocation. We model this aspect mathematically with a risk-return model by defining a general rate loss function. We then propose optimal and suboptimal algorithms to allocate power under a fixed power budget for such a system with linear rate loss. These algorithms as we will see allocate more power to more reliable subcarriers in a water-filling fashion with different water levels. We compare the performance of these algorithms for our model with respect to water-filling solutions. Simulations show that suboptimal schemes perform closer to optimal scheme although they could be implemented with same complexity as water-filling algorithm. We discuss the linearity of loss function and guidelines to choose its coefficients by obtaining upper bounds on them. Finally we extend this model for interference-limited OFDM-CR systems.

No description available.

The design of emergent wireless sensor networks operating near the ground requires channel models that account for previously unconsidered propagation phenomena. Most models used for link planning and radio design of the last century were designed for use in situations where the transmitters were at least tens of meters above the earth surface. However, near the earth surface, the specifics of the ground composition and atmospheric effects have been postulated to play a significant role. This dissertation describes the first set of investigations in this emergent environment. A novel computational electromagnetics model is presented that can calculate electromagnetic fields of a dipole embedded in planar-stratified propagation medium that represents the ground and near-surface atmosphere. It is the first available electromagnetic model to efficiently combine a spectral-domain solution in arbitrary multilayers of lossy-dielectric media with high-order quadrature routines to synthesize the fields of an impressed dipole. For the first time, high-order asymptotic quadrature is used to efficiently obtain solutions at arbitrary ranges from the dipole source. A measurements-based model of the near-ground atmosphere is derived, and results of modeling the atmosphere are used to predict the performance of an ultra-high-frequency radio system operating near the ground surface. Finally, a study is conducted to determine the effects of varying key parameters in the near ground channel, including atmospheric conditions, ground conditions, and frequency. The primary result is that ultra-high-frequency near-earth narrowband channels are largely insensitive to large-scale refractive effects that occur naturally on Earth; however, as the transmitter frequency increases into the super-high-frequency and millimeter wave regimes, refractive effects have significant effects on the radio propagation environment.

Cognitive Radio (CR) is considered to be a novel approach to improve the underutilization of precious radio resources by exploiting the unused licensed spectrum in dynamically changing environments. Designing efficient resource allocation algorithms for dynamic spectrum sharing and for power allocation in OFDM-CR networks is still a challenging problem. In this thesis, we specifically deal with these two problems. Dynamic spectrum sharing for the unlicensed secondary users (SU)s with device coordination could minimize the wastage of the spectrum. But this is a feasible approach only if the network considers the fairness criterion. We study the dynamic spectrum sharing problem for device coordinated cognitive radio networks with respect to fairness. We propose a simple modified proportional fair algorithm for a dynamic spectrum sharing scenario with two constraints, time and utility. Utility is measured by the amount of data processed and time is measured as the duration of a slot. This algorithm could result in variable or fixed length time slots. We will discuss the several controls possible on the algorithm and the possible extension of this algorithm for multicarrier OFDM based CR systems. Traditional water-filling algorithm is inefficient for OFDM-CR networks due to the interaction with primary users (PU)s. We consider reliability/availability of subcarriers or primary user activity for power allocation. We model this aspect mathematically with a risk-return model by defining a general rate loss function. We then propose optimal and suboptimal algorithms to allocate power under a fixed power budget for such a system with linear rate loss. These algorithms as we will see allocate more power to more reliable subcarriers in a water-filling fashion with different water levels. We compare the performance of these algorithms for our model with respect to water-filling solutions. Simulations show that suboptimal schemes perform closer to optimal scheme although they could be implemented with same complexity as water-filling algorithm. We discuss the linearity of loss function and guidelines to choose its coefficients by obtaining upper bounds on them. Finally we extend this model for interference-limited OFDM-CR systems.

Cognitive Radio (CR) is considered to be a novel approach to improve the underutilization of precious radio resources by exploiting the unused licensed spectrum in dynamically changing environments. Designing efficient resource allocation algorithms for dynamic spectrum sharing and for power allocation in OFDM-CR networks is still a challenging problem. In this thesis, we specifically deal with these two problems. Dynamic spectrum sharing for the unlicensed secondary users (SU)s with device coordination could minimize the wastage of the spectrum. But this is a feasible approach only if the network considers the fairness criterion. We study the dynamic spectrum sharing problem for device coordinated cognitive radio networks with respect to fairness. We propose a simple modified proportional fair algorithm for a dynamic spectrum sharing scenario with two constraints, time and utility. Utility is measured by the amount of data processed and time is measured as the duration of a slot. This algorithm could result in variable or fixed length time slots. We will discuss the several controls possible on the algorithm and the possible extension of this algorithm for multicarrier OFDM based CR systems. Traditional water-filling algorithm is inefficient for OFDM-CR networks due to the interaction with primary users (PU)s. We consider reliability/availability of subcarriers or primary user activity for power allocation. We model this aspect mathematically with a risk-return model by defining a general rate loss function. We then propose optimal and suboptimal algorithms to allocate power under a fixed power budget for such a system with linear rate loss. These algorithms as we will see allocate more power to more reliable subcarriers in a water-filling fashion with different water levels. We compare the performance of these algorithms for our model with respect to water-filling solutions. Simulations show that suboptimal schemes perform closer to optimal scheme although they could be implemented with same complexity as water-filling algorithm. We discuss the linearity of loss function and guidelines to choose its coefficients by obtaining upper bounds on them. Finally we extend this model for interference-limited OFDM-CR systems. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate