Device-to-Device Communication in 5G Cellular Networks

Owing to the unprecedented and continuous growth in the number of connected users and networked devices, the next-generation 5G cellular networks are envisaged to support enormous number of simultaneously connected users and devices with access to numerous services and applications by providing networks with highly improved data rate, higher capacity, lower end-to-end latency, improved spectral efficiency, at lower power consumption. D2D communication underlaying cellular networks has been proposed as one of the key components of the 5G technology as a means of providing efficient spectrum reuse for improved spectral efficiency and take advantage of proximity between devices for reduced latency, improved user throughput, and reduced power consumption. Although D2D communication underlaying cellular networks promises lots of potentials, unlike the conventional cellular network architecture, there are new design issues and technical challenges that must be addressed for proper implementation of the technology. These include new device discovery procedures, physical layer architecture and radio resource management schemes. This thesis explores the potentials of D2D communication as an underlay to 5G cellular networks and focuses on efficient interference management solutions through mode selection, resource allocation and power control schemes. In this work, a joint admission control, resource allocation, and power control scheme was implemented for D2D communication underlaying 5G cellular networks. The performance of the system was evaluated, and comparisons were made with similar schemes.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Advanced Technologies Enabling Unlicensed Spectrum Utilization in Cellular Networks

As the rapid progress and pleasant experience of Internet-based services, there is an increasing demand for high data rate in wireless communications systems. Unlicensed spectrum utilization in Long Term Evolution (LTE) networks is a promising technique to meet the massive traffic demand. There are two effective methods to use unlicensed bands for delivering LTE traffic. One is offloading LTE traffic toWi-Fi. An alternative method is LTE-unlicensed (LTE-U), which aims to directly use LTE protocols and infrastructures over the unlicensed spectrum. It has also been pointed out that addressing the above two methods simultaneously could further improve the system performance. However, how to avoid severe performance degradation of the Wi-Fi network is a challenging issue of utilizing unlicensed spectrum in LTE networks. Specifically, first, the inter-system spectrum sharing, or, more specifically, the coexistence of LTE andWi-Fi in the same unlicensed spectrum is the major challenge of implementing LTE-U. Second, to use the LTE and Wi-Fi integration approach, mobile operators have to manage two disparate networks in licensed and unlicensed spectrum. Third, optimization for joint data offloading to Wi-Fi and LTE-U in multi- cell scenarios poses more challenges because inter-cell interference must be addressed. This thesis focuses on solving problems related to these challenges. First, the effect of bursty traffic in an LTE and Wi-Fi aggregation (LWA)-enabled network has been investigated. To enhance resource efficiency, the Wi-Fi access point (AP) is designed to operate in both the native mode and the LWA mode simultaneously. Specifically, the LWA-modeWi-Fi AP cooperates with the LTE base station (BS) to transmit bearers to the LWA user, which aggregates packets from both LTE and Wi-Fi. The native-mode Wi-Fi AP transmits Wi-Fi packets to those native Wi-Fi users that are not with LWA capability. This thesis proposes a priority-based Wi-Fi transmission scheme with congestion control and studied the throughput of the native Wi-Fi network, as well as the LWA user delay when the native Wi-Fi user is under heavy traffic conditions. The results provide fundamental insights in the throughput and delay behavior of the considered network. Second, the above work has been extended to larger topologies. A stochastic geometry model has been used to model and analyze the performance of an MPTCP Proxy-based LWA network with intra-tier and cross-tier dependence. Under the considered network model and the activation conditions of LWA-mode Wi-Fi, this thesis has obtained three approximations for the density of active LWA-mode Wi-Fi APs through different approaches. Tractable analysis is provided for the downlink (DL) performance evaluation of large-scale LWA networks. The impact of different parameters on the network performance have been analyzed, validating the significant gain of using LWA in terms of boosted data rate and improved spectrum reuse. Third, this thesis also takes a significant step of analyzing joint multi-cell LTE-U and Wi-Fi network, while taking into account different LTE-U and Wi-Fi inter-working schemes. In particular, two technologies enabling data offloading from LTE to Wi-Fi are considered, including LWA and Wi-Fi offloading in the context of the power gain-based user offloading scheme. The LTE cells in this work are subject to load-coupling due to inter-cell interference. New system frameworks for maximizing the demand scaling factor for all users in both Wi-Fi and multi-cell LTE networks have been proposed. The potential of networks is explored in achieving optimal capacity with arbitrary topologies, accounting for both resource limits and inter-cell interference. Theoretical analyses have been proposed for the proposed optimization problems, resulting in algorithms that achieve global optimality. Numerical results show the algorithms’ effectiveness and benefits of joint use of data offloading and the direct use of LTE over the unlicensed band. All the derived results in this thesis have been validated by Monte Carlo simulations in Matlab, and the conclusions observed from the results can provide guidelines for the future unlicensed spectrum utilization in LTE networks

Enhancing the energy efficiency of radio base stations

This thesis is concerned with the energy efficiency of cellular networks. It studies the dominant power consumer in future cellular networks, the Long Term Evolution (LTE) radio Base Station (BS), and proposes mechanisms that enhance the BS energy efficiency by reducing its power consumption under target rate constraints. These mechanisms trade spare capacity for power saving. First, the thesis describes how much power individual components of a BS consume and what parameters affect this consumption based on third party experimental data. These individual models are joined into a component power model for an entire BS. The component model is an essential step in analysis but is too complex for many applications. It is therefore abstracted into a much simpler parameterized model to reduce its complexity. The parameterized model is further simplified into an affine model which can be applied in power minimization. Second, Power Control (PC) and Discontinuous Transmission (DTX) are identified as promising power-saving Radio Resource Management (RRM) mechanisms and applied to multi-user downlink transmission. PC reduces the power consumption of the Power Amplifier (PA) and is found to be most effective at high traffic loads. DTX mostly reduces the power consumption of the Baseband (BB) unit while interrupting transmission and is better applied in low traffic loads. Joint optimization of these two techniques is found to enable additional power-saving at medium traffic loads and to be a convex problem which can be solved efficiently. The convex problem is extended to provide a comprehensive power-saving Orthogonal Frequency Division Multiple Access (OFDMA) frame resource scheduler. The proposed scheduler is shown to reduce power consumption by 25-40% in computer simulations, depending on the traffic load. Finally, the thesis investigates the influence of interference on power consumption in a network of multiple power-saving BSs. It discusses three popular alternative distributed uncoordinated methods which align DTX mode between neighbouring BSs. To address drawbacks of these three, a fourth memory-based DTX alignment method is proposed. It decreases power consumption by up to 40% and retransmission probability by around 20%, depending on the traffic load

Self-optimized energy saving using cell fingerprinting for future radio access networks

Environmental sustainability and the strongly raising energy bill of network operators demand the implementation of energy reduction strategies in future radio access systems. The sharp rise in energy consumption, mostly caused by the exponential increase of data traffic, demands the deployment of a huge number of additional base stations (BSs). As the BS consumes the largest share of the energy in a cellular network, they offer a high energy saving potential. Energy consumption can be reduced in a self-organized way by adapting the network capacity in response to the instantaneous traffic demand. Thus, cells are deactivated and reactivated in line with the changing traffic demand. In this thesis, we concentrate on the complex problem of how to identify cells to be reactivated in situations of rising traffic demand. Reliable cell identification under any given traffic condition is the key for the self-optimized energy saving approach. The fingerprint method is used to identify the best fitting cell to take over the increasing traffic volume from highly loaded neighbor cells. The first step is to generate the cell individual fingerprints. Cells are found to be characterized by the received signal strength (RSS) measured by mobile device as observed in the neighbor cells. Consequently, a fingerprint consists of the list of neighbor cells and the associated RSS metrics that map the neighbor cell RSS distributions. The second step is to identify and subsequently activate the most suitable sleeping cell to relieve the active cell in overload. Initially, the overloaded cell requests mobiles to measure the RSS of the active neighbor cells. The measurement samples are matched with each cell fingerprint representing a sleeping cell. The cell fingerprint that corresponds best to the sample is expected to provide the best radio conditions. Results show that the accuracy increases with traffic load and number of metrics used for the matching, both of which provide more matching events. Finally, a simple model is created to evaluate the energy saving potential of cell fingerprinting. Input for the model is the hit rate of the most suitable cell achieved during the preceding cell fingerprinting simulation studies. The saving potential approaches closely the optimum results, if the most suitable cell would have been known.Ökologische Nachhaltigkeit, aber auch die steigenden Energiekosten, verlangen nach neuen Strategien zur Senkung des Stromverbrauchs zukünftiger Mobilfunknetze. Der Anstieg des Stromverbrauchs wird weitgehend durch das exponentiell wachsende Datenvolumen und den dadurch zusätzlich benötigten Basisstationen (BS) verursacht. Die BS bietet als größter Stromverbraucher eines Mobilfunknetzes ein hohes Einsparpotential. Durch selbstorganisierte Verfahren kann die verfügbare Netzkapazität kontinuierlich an die aktuell benötigte Kapazität angepasst werden, indem Funkzellen deaktiviert und bei Bedarf reaktiviert werden. Die zentrale Fragestellung dieser Arbeit ist, wie bei steigenden Datenverkehrsaufkommen geeignete, inaktive Zellen identifiziert und somit reaktiviert werden können. Voraussetzung dafür ist es, eine zuverlässige Zell-Identifizierung unter jeder beliebigen Verkehrsbedingung zu gewährleisten. Dafür wird das Fingerprinting-Verfahren eingesetzt. Als ersten Schritt generiert jede Zelle ihren individuellen "Fingerabdruck". Dafür messen die mobilen Endgeräte im gesamten Zellbereich die Empfangsfeldstärke der Nachbarzellen. Dementsprechend besteht der "Fingerabdruck" einer Zelle aus der Liste der Nachbarzellen und Metriken, die die Verteilung der Empfangsfeldstärke der jeweiligen Nachbarzelle abbilden. Als zweiter Schritt wird die inaktive Zelle identifiziert, die am besten geeignet ist, das zunehmende Datenvolumen zu übernehmen. Dafür fordert die überlastete Zelle Endgeräte auf, die Empfangsfeldstärke der aktiven Nachbarzellen zu messen. Diese Messwerte werden mit den Messwerten jedes "Fingerabdrucks" einer inaktiven Nachbarzelle verglichen. Die inaktive Zelle, deren "Fingerabdruck" am besten mit den Messwerten der Endgeräte übereingestimmt, verfügt über die besten Funkbedingungen, um Endgeräte der überlasteten Zelle zu bedienen. Die erzielten Ergebnisse zeigen, dass die Genauigkeit die passende Zelle zu identifizieren, sowohl von der Anzahl aktiver Nachbarzellen als auch von der Anzahl und Art der Metriken abhängt. Abschließend wird das Einsparpotential durch Einsatz von Fingerprinting berechnet. Als Input werden die in den vorangegangenen Simulationsstudien ermittelten Genauigkeiten der Zell-Identifizierung eingesetzt. Das Einsparpotential nähert sich dabei der maximal erzielbaren Stromeinsparung an

Quantifying Potential Energy Efficiency Gain in Green Cellular Wireless Networks

Conventional cellular wireless networks were designed with the purpose of providing high throughput for the user and high capacity for the service provider, without any provisions of energy efficiency. As a result, these networks have an enormous Carbon footprint. In this paper, we describe the sources of the inefficiencies in such networks. First we present results of the studies on how much Carbon footprint such networks generate. We also discuss how much more mobile traffic is expected to increase so that this Carbon footprint will even increase tremendously more. We then discuss specific sources of inefficiency and potential sources of improvement at the physical layer as well as at higher layers of the communication protocol hierarchy. In particular, considering that most of the energy inefficiency in cellular wireless networks is at the base stations, we discuss multi-tier networks and point to the potential of exploiting mobility patterns in order to use base station energy judiciously. We then investigate potential methods to reduce this inefficiency and quantify their individual contributions. By a consideration of the combination of all potential gains, we conclude that an improvement in energy consumption in cellular wireless networks by two orders of magnitude, or even more, is possible.Comment: arXiv admin note: text overlap with arXiv:1210.843

User-oriented mobility management in cellular wireless networks

2020 Spring.Includes bibliographical references.Mobility Management (MM) in wireless mobile networks is a vital process to keep an individual User Equipment (UE) connected while moving within the network coverage area—this is required to keep the network informed about the UE's mobility (i.e., location changes). The network must identify the exact serving cell of a specific UE for the purpose of data-packet delivery. The two MM procedures that are necessary to localize a specific UE and deliver data packets to that UE are known as Tracking Area Update (TAU) and Paging, which are burdensome not only to the network resources but also UE's battery—the UE and network always initiate the TAU and Paging, respectively. These two procedures are used in current Long Term Evolution (LTE) and its next generation (5G) networks despite the drawback that it consumes bandwidth and energy. Because of potentially very high-volume traffic and increasing density of high-mobility UEs, the TAU/Paging procedure incurs significant costs in terms of the signaling overhead and the power consumption in the battery-limited UE. This problem will become even worse in 5G, which is expected to accommodate exceptional services, such as supporting mission-critical systems (close-to-zero latency) and extending battery lifetime (10 times longer). This dissertation examines and discusses a variety of solution schemes for both the TAU and Paging, emphasizing a new key design to accommodate 5G use cases. However, ongoing efforts are still developing new schemes to provide seamless connections to the ever-increasing density of high-mobility UEs. In this context and toward achieving 5G use cases, we propose a novel solution to solve the MM issues, named gNB-based UE Mobility Tracking (gNB-based UeMT). This solution has four features aligned with achieving 5G goals. First, the mobile UE will no longer trigger the TAU to report their location changes, giving much more power savings with no signaling overhead. Instead, second, the network elements, gNBs, take over the responsibility of Tracking and Locating these UE, giving always-known UE locations. Third, our Paging procedure is markedly improved over the conventional one, providing very fast UE reachability with no Paging messages being sent simultaneously. Fourth, our solution guarantees lightweight signaling overhead with very low Paging delay; our simulation studies show that it achieves about 92% reduction in the corresponding signaling overhead. To realize these four features, this solution adds no implementation complexity. Instead, it exploits the already existing LTE/5G communication protocols, functions, and measurement reports. Our gNB-based UeMT solution by design has the potential to deal with mission-critical applications. In this context, we introduce a new approach for mission-critical and public-safety communications. Our approach aims at emergency situations (e.g., natural disasters) in which the mobile wireless network becomes dysfunctional, partially or completely. Specifically, this approach is intended to provide swift network recovery for Search-and-Rescue Operations (SAROs) to search for survivors after large-scale disasters, which we call UE-based SAROs. These SAROs are based on the fact that increasingly almost everyone carries wireless mobile devices (UEs), which serve as human-based wireless sensors on the ground. Our UE-based SAROs are aimed at accounting for limited UE battery power while providing critical information to first responders, as follows: 1) generate immediate crisis maps for the disaster-impacted areas, 2) provide vital information about where the majority of survivors are clustered/crowded, and 3) prioritize the impacted areas to identify regions that urgently need communication coverage. UE-based SAROs offer first responders a vital tool to prioritize and manage SAROs efficiently and effectively in a timely manner