Recent Advances in Cellular D2D Communications

Device-to-device (D2D) communications have attracted a great deal of attention from researchers in recent years. It is a promising technique for offloading local traffic from cellular base stations by allowing local devices, in physical proximity, to communicate directly with each other. Furthermore, through relaying, D2D is also a promising approach to enhancing service coverage at cell edges or in black spots. However, there are many challenges to realizing the full benefits of D2D. For one, minimizing the interference between legacy cellular and D2D users operating in underlay mode is still an active research issue. With the 5th generation (5G) communication systems expected to be the main data carrier for the Internet-of-Things (IoT) paradigm, the potential role of D2D and its scalability to support massive IoT devices and their machine-centric (as opposed to human-centric) communications need to be investigated. New challenges have also arisen from new enabling technologies for D2D communications, such as non-orthogonal multiple access (NOMA) and blockchain technologies, which call for new solutions to be proposed. This edited book presents a collection of ten chapters, including one review and nine original research works on addressing many of the aforementioned challenges and beyond

An adaptive social-aware device-to-device communication mechanism for wireless networks

Device-to-Device (D2D) communication is an essential element in 5G networks, which enables users to communicate either directly without network assistance or with minimum signaling through a base station. For an effective D2D communication, related problems in mode and peer selection need to be addressed. In mode selection, the problem is how to guarantee selection always chooses the best available mode. In peer selection, the problem is how to select optimum peers among surrounding peers in terms of connection conditions and social relationships between peers. The main objectives of this research are to identify mode selection between devices and establishing a connection with the best D2D pair connection without privacy leakage. Multi-Attribute Decision Making and Social Choice theories are applied to achieve the objectives. Mode selection scheme is based on Received Signal Strength (RSS), delay and bandwidth attributes to choose and switch among the available modes intelligently based on the highest ranking. Then, the peering selection scheme is proposed using RSS, delay, bandwidth and power attribute to find an optimum peer with concerning social relationship, by evaluating trust level between peers and excluding the untrusted peers from ranking which will increase the optimum quality of D2D connection. The proposed schemes are validated and tested using MATLAB. Two main scenarios, namely crowded network and user speed were considered to evaluate the proposed mechanism with three existing approaches where the selection is based on a single attribute. The obtained results showed that the proposed mechanism outperforms other approaches in terms of delay, signal to noise ratio, delivery ratio and throughput with better performance up to 70%. The proposed mechanism provides a smooth switching between different modes and employs an automatic peering selection with trusted peers only. It can be applied in different types of network that serves the massive number of users with different movement speed of the user

Opportunistic Spectrum Utilization for Vehicular Communication Networks

Recently, vehicular networks (VANETs), has become the key technology of the next-generation intelligent transportation systems (ITS). By incorporating wireless communication and networking capabilities into automobiles, information can be efficiently and reliably disseminated among vehicles, road side units, and infrastructure, which enables a number of novel applications enhancing the road safety and providing the drivers/passengers with an information-rich environment. With the development of mobile Internet, people want to enjoy the Internet access in vehicles just as anywhere else. This fact, along with the soaring number of connected vehicles and the emerging data-craving applications and services, has led to a problem of spectrum scarcity, as the current spectrum bands for VANETs are difficult to accommodate the increasing mobile data demands. In this thesis, we aim to solve this problem by utilizing extra spectrum bands, which are not originally allocated for vehicular communications. In this case, the spectrum usage is based on an opportunistic manner, where the spectrum is not available if the primary system is active, or the vehicle is outside the service coverage due to the high mobility. We will analyze the features of such opportunistic spectrum, and design efficient protocols to utilize the spectrum for VANETs. Firstly, the application of cognitive radio technologies in VANETs, termed CR-VANETs, is proposed and analyzed. In CR-VANETs, the channel availability is severely affected by the street patterns and the mobility features of vehicles. Therefore, we theoretically analyze the channel availability in urban scenario, and obtain its statistics. Based on the knowledge of channel availability, an efficient channel access scheme for CR-VANETs is then designed and evaluated. Secondly, using WiFi to deliver mobile data, named WiFi offloading, is employed to deliver the mobile data on the road, in order to relieve the burden of the cellular networks, and provide vehicular users with a cost-effective data pipe. Using queueing theory, we analyze the offloading performance with respect to the vehicle mobility model and the users' QoS preferences. Thirdly, we employ device-to-device (D2D) communications in VANETs to further improve the spectrum efficiency. In a vehicular D2D (V-D2D) underlaying cellular network, proximate vehicles can directly communicate with each other with a relatively small transmit power, rather than traversing the base station. Therefore, many current transmissions can co-exist on one spectrum resource block. By utilizing the spatial diversity, the spectrum utilization is greatly enhanced. We study the performance of the V-D2D underlaying cellular network, considering the vehicle mobility and the street pattern. We also investigate the impact of the preference of D2D/cellular mode on the interference and network throughput, and obtain the theoretical results. In summary, the analysis and schemes developed in this thesis are useful to understand the future VANETs with heterogeneous access technologies, and provide important guidelines for designing and deploying such networks

D4.3 Final Report on Network-Level Solutions

Research activities in METIS reported in this document focus on proposing solutions to the network-level challenges of future wireless communication networks. Thereby, a large variety of scenarios is considered and a set of technical concepts is proposed to serve the needs envisioned for the 2020 and beyond. This document provides the final findings on several network-level aspects and groups of solutions that are considered essential for designing future 5G solutions. Specifically, it elaborates on: -Interference management and resource allocation schemes -Mobility management and robustness enhancements -Context aware approaches -D2D and V2X mechanisms -Technology components focused on clustering -Dynamic reconfiguration enablers These novel network-level technology concepts are evaluated against requirements defined by METIS for future 5G systems. Moreover, functional enablers which can support the solutions mentioned aboveare proposed. We find that the network level solutions and technology components developed during the course of METIS complement the lower layer technology components and thereby effectively contribute to meeting 5G requirements and targets.Aydin, O.; Valentin, S.; Ren, Z.; Botsov, M.; Lakshmana, TR.; Sui, Y.; Sun, W.... (2015). D4.3 Final Report on Network-Level Solutions. http://hdl.handle.net/10251/7675

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Resource Allocation for D2D Communications Based on Matching Theory

PhDDevice-to-device (D2D) communications underlaying a cellular infrastructure takes advantage of the physical proximity of communicating devices and increasing resource utilisation. However, adopting D2D communications in complex scenarios poses substantial challenges for the resource allocation design. Meanwhile, matching theory has emerged as a promising framework for wireless resource allocation which can overcome some limitations of game theory and optimisation. This thesis focuses on the resource allocation optimisation for D2D communications based on matching theory. First, resource allocation policy is designed for D2D communications underlaying cellular networks. A novel spectrum allocation algorithm based on many-to-many matching is proposed to improve system sum rate. Additionally, considering the quality-of-service (QoS) requirements and priorities of di erent applications, a context-aware resource allocation algorithm based on many-to-one matching is proposed, which is capable of providing remarkable performance enhancement in terms of improved data rate, decreased packet error rate (PER) and reduced delay. Second, to improve resource utilisation, joint subchannel and power allocation problem for D2D communications with non-orthogonal multiple access (NOMA) is studied. For the subchannel allocation, a novel algorithm based on the many-to-one matching is proposed for obtaining a suboptimal solution. Since the power allocation problem is non-convex, sequential convex programming is adopted to transform the original power allocation problem to a convex one. The proposed algorithm is shown to enhance the network sum rate and number of accessed users. Third, driven by the trend of heterogeneity of cells, the resource allocation problem for NOMA-enhanced D2D communications in heterogeneous networks (HetNets) is investigated. In such a scenario, the proposed resource allocation algorithm is able to closely approach the optimal solution within a limited number of iterations and achieves higher sum rate compared to traditional HetNets schemes. Thorough theoretical analysis is conducted in the development of all proposed algorithms, and performance of proposed algorithm is evaluated via comprehensive simulations. This thesis concludes that matching theory based resource allocation for D2D communications achieves near-optimal performance with acceptable complexity. In addition, the application of D2D communications in NOMA and HetNets can improve system performance in terms of sum rate and users connectivity

Integrating Drones and Wireless Power Transfer into Beyond 5G Networks

As fifth generation (5G) standards have been established and 5G commercial products are just around the corner, both academia and industry have started to look at requirements for beyond 5G networks. Network flexibility and long battery life are among the key requirements for beyond 5G wireless communication systems. These critical requirements, which have not been sufficiently addressed in the previous generations, are the focus of this thesis. The first half of this thesis explores two important use cases of drones to provide flexible communication networks. First, the performance of a cellular network with underlay drone cell for temporary events inside a stadium is studied. Using stochastic geometry, a general analytical framework is proposed to analyze the uplink and the downlink coverage probabilities for both the aerial and the terrestrial systems. Our results show that for urban environment and dense urban environment, the drone is best deployed at a low height (e.g., 200 m or lower), regardless of the distance between the center of the stadium and the terrestrial base station. However, for suburban environment and high-rise urban environment, the best drone altitude varies. Second, the performance of emergency information dissemination in public safety scenarios using drone is studied. A drone-assisted multihop multicast device-to-device (D2D) network is considered, where an emergency alert message broadcasted by a drone at the first time slot is multicasted by the D2D users that have successfully received the message through multihop. The impact of different system parameters on the link and the network performance is investigated. Our results demonstrate that a higher drone altitude provides better link and network coverage probabilities and lower mean local delay. Under practical setups, the cell edge user located 2 km from the ground projection of the drone has a link coverage probability around 90% after 5 time slots and a mean local delay of 2.32 time slots with a drone height as low as 200 m. The second half of this thesis investigates wireless power transfer networks. Specifically, the use of power beacons in a millimeter wave wireless ad hoc network is considered, where transmitters adopt the harvest-then-transmit protocol. First, the characteristic of the aggregate received power from power beacons is analyzed and the lognormal distribution is found to provide the best complementary cumulative distribution function approximation compared to other distributions considered in the literature. Then, a tractable model with discrete transmit power for each transmitter is proposed to compute the channel coverage probability and the total coverage probability. Our results show that our model provides a good accuracy and reveal the impact of different system parameters on the total coverage probability. Our results also illustrate that under practical setups, for power beacon transmit power of 50 dBm and transmitters with maximum transmit power between 20 - 40 dBm, which are safe for human exposure, the total coverage probability is around 90%. Thus, it is feasible and safe to power transmitters in a millimeter wave ad hoc network using power beacons

Enabling Cyber-Physical Communication in 5G Cellular Networks: Challenges, Solutions and Applications

Cyber-physical systems (CPS) are expected to revolutionize the world through a myriad of applications in health-care, disaster event applications, environmental management, vehicular networks, industrial automation, and so on. The continuous explosive increase in wireless data traffic, driven by the global rise of smartphones, tablets, video streaming, and online social networking applications along with the anticipated wide massive sensors deployments, will create a set of challenges to network providers, especially that future fifth generation (5G) cellular networks will help facilitate the enabling of CPS communications over current network infrastructure. In this dissertation, we first provide an overview of CPS taxonomy along with its challenges from energy efficiency, security, and reliability. Then we present different tractable analytical solutions through different 5G technologies, such as device-to-device (D2D) communications, cell shrinking and offloading, in order to enable CPS traffic over cellular networks. These technologies also provide CPS with several benefits such as ubiquitous coverage, global connectivity, reliability and security. By tuning specific network parameters, the proposed solutions allow the achievement of balance and fairness in spectral efficiency and minimum achievable throughout among cellular users and CPS devices. To conclude, we present a CPS mobile-health application as a case study where security of the medical health cyber-physical space is discussed in details

Statistical Performance Evaluation for Energy Harvesting Communications based on Large Deviation Theorem

Energy harvesting (EH) is a promising technology for enhancing a network’s quality of service (QoS). EH-based communication systems are studied by tackling the challenges of energy-outage probability and energy conditioning. These issues motivate this research to develop new solutions for increasing the lifetime of device batteries by leveraging renewable energy sources available in the surrounding environment, for instance, from solar and radio-frequency (RF) energy through harvesting. This dissertation studies an energy outage problem and user QoS requirements for energy harvesting communications. In the first part of this dissertation, the performance of an energy harvesting communication link is analysed by allowing a certain level of energy-outage. In EH systems, energy consumed from the battery depends on the QoS required by the end user and on the channel state information. At the same time, the energy arrival to the battery depends on the strength of the power source, solar in this case, and is independent of the fading channel conditions and the required QoS. Due to the independence between the energy arrival into the battery and the energy consumed from there, it is challenging to estimate the exact status of the available energy in the battery. An energy outage is experienced when there is no further energy for the system to utilise for data transmission. In this part, a thorough study was carried out to analyse the required energy harvesting (EH) rate for satisfying the QoS requirements when a level of energy-outage is allowed in a point-to-point EH-based communication system equipped with a finite-sized battery. Furthermore, an expression relating the rate of the incoming energy with the fading channel conditions and the minimum required QoS of the system was provided to analyse the performance of the EH-based communication system under energy constraints. Finally, numerical results confirm the proposed mechanism’s analytical findings and correctness. In the second part of this dissertation, the performance of point-to-point communications is investigated in which the source node can harvest and store energy from RF signals and then use the harvested energy to communicate with its end destination. The continuous availability of RF energy has proved advantageous as a wireless power source to support low-power devices, making RF-based energy harvesting an alternative and viable solution for powering next-generation wireless networks, particularly for Internet-of-Things (IoT) applications. Specifically, the point-to-point RF-based energy-harvesting communication is considered, where the transmitter, which can be an IoT sensor, implements a time-switching protocol between the energy harvesting and the information transfer, and we focus on analysing the system performance while aiming to guarantee the required QoS of the end user subject to system constraint energy outage. The time-switching circuit at the source node allows the latter to switch between harvesting energy from a distant RF energy source and transmitting data to its target destination using the scavenged energy. Using a duality principle between the physical energy queue and a proposed virtual energy queue and assuming that a certain level of energy outage can be tolerated in the communication process, the system performance was evaluated with a novel analytical framework that leverages tools for the large deviation principle. In the third and last part of this dissertation, an empirical study of the RF-EH model is presented for ensuring the QoS constraints during an energy-outage for Simultaneous Wireless Information and Power Transfer (SWIPT) network. We consider a relay network over a Rayleigh fading channel where the relay lacks a permanent power source. Thus, we obtain energy from wireless energy harvesting (EH) of the source’s signals to maintain operation. This process is performed using a time-switching protocol at the relay for enhancing the quality of service (QoS) in SWIPT networks. A numerical approach is incorporated to evaluate the performance of the proposed RF-EH model in terms of different evaluation parameters such as time-switching protocol, transmit power and outage. The assumptions of the large deviation principle are satisfied using a proposed virtual energy queuing model, which is then used for the performance analysis. We established a closed-form expression for the system’s probability of experiencing an energy outage and the energy consumed by the relay battery