Effects of 3D Deployments on Interference and SINR in 5G New Radio Systems

Lately, the extremely high frequency (EHF) band has become one of the factors enabling fifth-generation (5G) mobile cellular technologies. By offering large bandwidth, New Radio (NR) systems operating in the lower part of EHF band, called millimeter waves (mmWave), may satisfy the extreme requirements of future 5G networks in terms of both data transfer rate and latency at the air interface. The use of highly directional antennas in prospective mmWave-based NR communications systems raises an important question: are conventional two-dimensional (2D) cellular network modeling techniques suitable for 5G NR systems? To address this question, we introduced a novel, three-dimensional framework for evaluating the performance of emerging mmWave band wireless networks. The proposed framework explicitly takes into account the blockage effects of propagating mmWave radiation, the vertical and planar directivities at transceiver antennas, and the randomness of user equipment (UE), base station (BS), and blocker heights. The model allows for different levels of accuracy, encompassing a number of models with different levels of computational complexity as special cases. Although the main metric of interest in this thesis is the signal-to-interference-plus-noise ratio (SINR), the model can be extended to obtain the Shannon rate of the channel under investigation. The proposed model was numerically evaluated in different deployment cases and communication scenarios with a wide range of system parameters. We found that randomness of UE and BS heights and vertical directionality of the mmWave antennas are essential for accurate evaluation of system performance. We also showed that the results of traditional 2D models are too optimistic and greatly overestimate the actual SINR. In contrast, fixed-height models that ignore the impact of height on the probability of exposure to interference are too pessimistic. Furthermore, we evaluated the models that provide the best trade-off between computational complexity and accuracy in specific scenarios and provided recommendations regarding their use for practical assessment of mmWave-based NR systems

Direct communication radio Iinterface for new radio multicasting and cooperative positioning

Cotutela: Universidad de defensa UNIVERSITA’ MEDITERRANEA DI REGGIO CALABRIARecently, the popularity of Millimeter Wave (mmWave) wireless networks has increased due to their capability to cope with the escalation of mobile data demands caused by the unprecedented proliferation of smart devices in the fifth-generation (5G). Extremely high frequency or mmWave band is a fundamental pillar in the provision of the expected gigabit data rates. Hence, according to both academic and industrial communities, mmWave technology, e.g., 5G New Radio (NR) and WiGig (60 GHz), is considered as one of the main components of 5G and beyond networks. Particularly, the 3rd Generation Partnership Project (3GPP) provides for the use of licensed mmWave sub-bands for the 5G mmWave cellular networks, whereas IEEE actively explores the unlicensed band at 60 GHz for the next-generation wireless local area networks. In this regard, mmWave has been envisaged as a new technology layout for real-time heavy-traffic and wearable applications. This very work is devoted to solving the problem of mmWave band communication system while enhancing its advantages through utilizing the direct communication radio interface for NR multicasting, cooperative positioning, and mission-critical applications. The main contributions presented in this work include: (i) a set of mathematical frameworks and simulation tools to characterize multicast traffic delivery in mmWave directional systems; (ii) sidelink relaying concept exploitation to deal with the channel condition deterioration of dynamic multicast systems and to ensure mission-critical and ultra-reliable low-latency communications; (iii) cooperative positioning techniques analysis for enhancing cellular positioning accuracy for 5G+ emerging applications that require not only improved communication characteristics but also precise localization. Our study indicates the need for additional mechanisms/research that can be utilized: (i) to further improve multicasting performance in 5G/6G systems; (ii) to investigate sideline aspects, including, but not limited to, standardization perspective and the next relay selection strategies; and (iii) to design cooperative positioning systems based on Device-to-Device (D2D) technology

Facilitating Internet of Things on the Edge

The evolution of electronics and wireless technologies has entered a new era, the Internet of Things (IoT). Presently, IoT technologies influence the global market, bringing benefits in many areas, including healthcare, manufacturing, transportation, and entertainment. Modern IoT devices serve as a thin client with data processing performed in a remote computing node, such as a cloud server or a mobile edge compute unit. These computing units own significant resources that allow prompt data processing. The user experience for such an approach relies drastically on the availability and quality of the internet connection. In this case, if the internet connection is unavailable, the resulting operations of IoT applications can be completely disrupted. It is worth noting that emerging IoT applications are even more throughput demanding and latency-sensitive which makes communication networks a practical bottleneck for the service provisioning. This thesis aims to eliminate the limitations of wireless access, via the improvement of connectivity and throughput between the devices on the edge, as well as their network identification, which is fundamentally important for IoT service management. The introduction begins with a discussion on the emerging IoT applications and their demands. Subsequent chapters introduce scenarios of interest, describe the proposed solutions and provide selected performance evaluation results. Specifically, we start with research on the use of degraded memory chips for network identification of IoT devices as an alternative to conventional methods, such as IMEI; these methods are not vulnerable to tampering and cloning. Further, we introduce our contributions for improving connectivity and throughput among IoT devices on the edge in a case where the mobile network infrastructure is limited or totally unavailable. Finally, we conclude the introduction with a summary of the results achieved

Efficient radio resource management for future generation heterogeneous wireless networks

The heterogeneous deployment of small cells (e.g., femtocells) in the coverage area of the traditional macrocells is a cost-efficient solution to provide network capacity, indoor coverage and green communications towards sustainable environments in the future fifth generation (5G) wireless networks. However, the unplanned and ultra-dense deployment of femtocells with their uncoordinated operations will result in technical challenges such as severe interference, a significant increase in total energy consumption, unfairness in radio resource sharing and inadequate quality of service provisioning. Therefore, there is a need to develop efficient radio resource management algorithms that will address the above-mentioned technical challenges. The aim of this thesis is to develop and evaluate new efficient radio resource management algorithms that will be implemented in cognitive radio enabled femtocells to guarantee the economical sustainability of broadband wireless communications and users' quality of service in terms of throughput and fairness. Cognitive Radio (CR) technology with the Dynamic Spectrum Access (DSA) and stochastic process are the key technologies utilized in this research to increase the spectrum efficiency and energy efficiency at limited interference. This thesis essentially investigates three research issues relating to the efficient radio resource management: Firstly, a self-organizing radio resource management algorithm for radio resource allocation and interference management is proposed. The algorithm considers the effect of imperfect spectrum sensing in detecting the available transmission opportunities to maximize the throughput of femtocell users while keeping interference below pre-determined thresholds and ensuring fairness in radio resource sharing among users. Secondly, the effect of maximizing the energy efficiency and the spectrum efficiency individually on radio resource management is investigated. Then, an energy-efficient radio resource management algorithm and a spectrum-efficient radio resource management algorithm are proposed for green communication, to improve the probabilities of spectrum access and further increase the network capacity for sustainable environments. Also, a joint maximization of the energy efficiency and spectrum efficiency of the overall networks is considered since joint optimization of energy efficiency and spectrum efficiency is one of the goals of 5G wireless networks. Unfortunately, maximizing the energy efficiency results in low performance of the spectrum efficiency and vice versa. Therefore, there is an investigation on how to balance the trade-off that arises when maximizing both the energy efficiency and the spectrum efficiency simultaneously. Hence, a joint energy efficiency and spectrum efficiency trade-off algorithm is proposed for radio resource allocation in ultra-dense heterogeneous networks based on orthogonal frequency division multiple access. Lastly, a joint radio resource allocation with adaptive modulation and coding scheme is proposed to minimize the total transmit power across femtocells by considering the location and the service requirements of each user in the network. The performance of the proposed algorithms is evaluated by simulation and numerical analysis to demonstrate the impact of ultra-dense deployment of femtocells on the macrocell networks. The results show that the proposed algorithms offer improved performance in terms of throughput, fairness, power control, spectrum efficiency and energy efficiency. Also, the proposed algorithms display excellent performance in dynamic wireless environments

Improvement of 5G performance through network densification in millimetre wave band

Recently, there has been a substantial growth in mobile data traffic due to the widespread of data hungry devices such as mobiles and laptops. The anticipated high traffic demands and low latency requirements stemmed from the Internet of Things (IoT) and Machine Type Communications (MTC) can only be met with radical changes to the network paradigm such as harnessing the millimetre wave (mmWave) band in Ultra-Dense Network (UDN). This thesis presents many challenges, problems and questions that arise in research and design stage of 5G network. The main challenges of 5G in mmWave can be characterised with the following attributes: i- huge traffic demands, with very high data rate requirements, ii- high interference in UDN, iii increased handover in UDN, higher dependency on Line of Sight (LOS) coverage and high shadow fading, and iv-massive MTC traffic due to billions of connected devices. In this work, software simulation tools have been used to evaluate the proposed solutions. Therefore, we have introduced 5G network based on network densification. Network densification includes densification over frequency through mmWave, and densification over space through higher number of antennas, Higher Order Sectorisation (HOS), and denser deployment of small-cells. Our results show that the densification theme has significantly improved network capacity and user Quality of Experience (QoE). UDN network can efficiently raise the user experience to the level that 5G vision promised. However, one of the drawback of using UDN and HOS is the significant increase in Inter-Cell Interference (ICI). Therefore, ICI has been addressed in this work to increase the gain of densification. ICI can degrade the performance of wireless network, particularly in UDN due to the increased interference from surrounding cells. We have used Fractional Frequency Reuse (FFR) as ICI Coordination (ICIC) for UDN network and HOS environment. The work shows that FFR has improved the network performance in terms of cell-edge data throughput and average cell throughput, and maintain the peak data throughput at a certain threshold. Additionally, HOS has shown even greater gain over default sectored sites when the interference is carefully coordinated. To generalise the principle of densification, we have introduced Distributed Base Station (DBS) as the envisioned network architecture for 5G in mmWave. Remotely distributed antennas in DBS architecture have been harnessed in order to compensate for the high path loss that characterise mmWave propagation. The proposed architecture has significantly improved the user data throughput, decreased the unnecessary handovers as a result of dense network, increased the LOS coverage probability, and reduced the impact of shadow fading. Additionally, this research discusses the regulatory requirements at mmWave band for the Maximum Permissible Exposure (MPE). Finally, scheduling massive MTC traffic in 5G has been considered. MTC is expected to contribute to the majority of IoT traffic. In this context, an algorithm has been developed to schedule this type of traffic. The results demonstrate the gain of using distributed antennas on MTC traffic in terms of spectral efficiency, data throughput, and fairness. The results show considerable improvement in the performance metrics. The combination of these contributions has provided remarkable increase in data throughput to achieve the 5G vision of “massive” capacity and to support human and machine traffic