Technology For 5G Networks Research Articles

Empirical Experience and Experimental Evaluation of Open5GCore over Hypervisor and Container

One of the most important technologies for future 5G networks is to utilize Network Function Virtualization (NFV) to virtualize the network components. NFV provides flexibility, short time to market, and low cost solution to build network services, which are important features of 5G networks. Although the idea of virtualization is just being applied to cellular networks, it has been used in the community of cloud computing. There are two main virtualization techniques, hypervisor and container. In this paper, we present our practical experience of virtualizing Open5GCore, a commercial product of SDN‐enabled Evolved Packet Core (EPC), over hypervisor and container. In addition to describing how to virtualize Open5GCore, we also present the experimental performance evaluation of the systems. Finally, some important lessons learned are provided.

Beam Management for Millimeter-Wave Beamspace MU-MIMO Systems

Millimeter-wave (mm-wave) communication has attracted increasing attention as a promising technology for 5G networks. One of the key architectural features of mm-wave is the possibility of using large antenna arrays at both the transmitter and receiver sides. Therefore, by employing directional beamforming, both mm-wave base stations (MBSs) and mm-wave user equipments (MUEs) are capable of supporting multi-beam simultaneous transmissions. However, most of the existing research results have only considered a single beam. Thus, the potentials of mm-wave have not been fully exploited yet. In this context, in order to improve the performance of short-range indoor mm-wave networks with multiple reflections, we investigate the challenges and potential solutions of downlink multi-user multi-beam transmission, which can be described as a beamspace multi-user multiple-input multiple-output (MU-MIMO) technique. We first exploit the characteristic of MBS/MUEs supporting multiple beams simultaneously to improve the efficiency of multi-user BF training. Then, we analyze the inter-user interference to avoid beam selection conflicts. Furthermore, we propose blockage control strategies and multi-user multi-beam power allocation solutions for the beamspace MU-MIMO. The theoretical and numerical results demonstrate that the beamspace MU-MIMO compared with single beam transmission can largely improve the rate performance and robustness of mm-wave networks.

Technological Trends for 5G Networks Influence of E-Health and IoT Applications

The fifth generation of mobile communications networks (5G) is currently in the standardization process, which is expected to be completed in 2020. For this new generation, new applications and scenarios are imposing new performance requirements in addition to higher data rates. Specifically, the Internet of Things (IoT) and e-health applications have very important economic roles in 5G networks and define particular performance requirements that must be considered when defining the technologies for 5G networks. In this paper, the author discusses the influence of e-health and IoT applications on the technological trends for 5G networks.

Resource Management for Cognitive IoT Systems With RF Energy Harvesting in Smart Cities

The number of Internet of Things (IoT) nodes is increasing in modern cities which demands spectrum and energy efficiency. Fifth-generation (5G) networks are considered as a key paradigm for the realization of future IoT applications. Particularly, cognitive radio and non-orthogonal multiple access are candidate technologies for 5G networks that can improve spectral efficiency and accommodate a large number of IoT devices. Furthermore, radio frequency (RF) energy harvesting can increase the energy efficiency of IoT networks. In this paper, we propose a resource management scheme for cognitive IoT network with RF energy harvesting in 5G networks. The objective is to maximize the throughput while assuring quality-of-service requirements in terms of data rate and minimum residual energy constraint on each IoT node. We use mixed integer linear programming and greedy approaches to solve the optimization problem. We then present the simulation results of the proposed scheme to exhibit the significant positive impact on the performance of the IoT network.

Cooperative Full Duplex Device to Device Communication Underlaying Cellular Networks

Recently, device-to-device (D2D) communication and full duplex communication are both considered key technologies for 5G networks. In this paper, two novel cooperative modes are developed for full duplex D2D communication underlaying cellular networks: the network MU-MIMO based mode (N-mode) and the sequential forwarding mode (S-mode). In the N-mode, two D2D users work as network MIMO to forward the data to cellular users and thus leverage the channel diversity. In the S-mode, the spatial distribution of D2D users and cellular users is explored to improve the transmission rate. Based on these modes, two D2D users share the downlink resources with two nearby cellular users simultaneously to achieve both proximity gain and reuse gain. Moreover, these modes are well suited for edge cellular users. To optimize the performance of the two modes, optimal power allocation is conducted by considering the influence of residual self-interference at full duplex radios and the requirements of the minimum transmission rate for both cellular users and D2D users. Simulation results show that, compared with the dedicated mode, the sum rate of cooperative modes in the perfect self-interference cancellation case can achieve 32% overall improvement and about 70% improvement in the scenario with non-edge D2D users and edge cellular users. With residual self-interference at a full duplex radio, the overall performance improvement is reduced to 15%. However, the cooperative modes can still achieve 40% improvement in the scenario with non-edge D2D users and edge cellular users.

Prospective Positioning Architecture and Technologies in 5G Networks

Accurate and real-time positioning is highly demanded by location-based services in 5G networks, which are currently being standardized and developed to achieve significant performance improvement over existing cellular networks. In 5G networks, many new envisioned technologies, for example, massive Multiple Input Multiple Output (MIMO), millimeter Wave (mmWave) communication, ultra dense network (UDN), and device-to-device (D2D) communication, are introduced to not only enhance communication performance but also offer the possibility to increase positioning accuracy. In this article, we provide an extensive overview of positioning architectures in previous generations of cellular networks to show a road map of how positioning technologies have evolved in past decades. With this insight, we then propose a general positioning architecture for 5G networks, by exploiting the new features of emerging technologies wherein. We also investigate positioning technologies that have great potential in achieving sub-meter accuracy in 5G networks, and discuss some of the new challenges and open issues.

Second-Order Statistics Channel Model for 5G Millimeter-Wave Mobile Communications

Millimeter waves (mmWs) are considered as one of the most promising technologies for future 5G networks. The current study presents a three-dimensional (3D) geometry-based channel model for a fixed-to-mobile non-isotropic Ricean mmW scattering environment. According to this 3D reference model, the mmW complex faded envelope impulse response has been derived. This impulse response has been employed in estimating the second-order statistics of the mmW channel model. These statistics comprise both the 3D faded envelope level crossing rate (LCR) and the average fade duration (AFD). As a consequence, these statistics may contribute to the 5G network planning and engineering, especially for studying the phenomenon of fading with time, the 5G system characteristics, the handoff scenarios, and the relationship between the mobile user velocity and the fading rate. Furthermore, this study also provides a stochastic sum-of-sinusoids mmW channel simulator for comparison with analytical results. Numerical results validated the proposed analytical model and revealed the effect of channel parameters on both LCR and AFD in the mmW bands.

Toward green 5G heterogeneous small-cell networks: power optimization using load balancing technique

The overwhelming demand for data by an ever-increasing number of users is a great challenge wireless cellular networks are faced with. One potential solution to this issue is deploying a massive number of small cells (SCs) in the existing macro network. As SC overlay has a big role in the future wireless networks that can overcome the data traffic upsurge at little power cost, heterogeneous network (HetNet) has been viewed as a promising technology for 5G networks that extends cell coverage, improves network capacity and offloads the network traffic from the macro cell (MC) to the SCs. However, the hyper-dense SCs and their uncorrelated operation raise an important question about the joint power consumption of the macro base station (MBS) and the small base stations (SBSs) in the HetNet since the aggregate power consumption of the dense SBSs cannot be ignored. Recently, the SC sleeping technique has become a hot topic for saving energy in HetNets. To minimize power consumption in HetNets, we propose three algorithms to dynamically adapt the operation of the SBSs to active/sleep (on/off) for non-uniform user distribution in the HetNet. We investigate the general optimal power minimization problem for HetNet that requires relatively high computational complexity. Taking into account the additional increase of the traffic load brought to the MBS, a key design principle of the proposed algorithms is to switch off the SBSs gradually based on their locations, user densities in their coverage areas or the highest power that can be saved by switching some of them off, respectively. Then, we enhance the mathematical framework to make the analysis more realistic by considering the offloading between the SCs and the MBS that occurs when the traffic load exceeds SCs’ capacity. In this paper, based on the fact that user densities of SCs and MC change with time, we model the traffic on the European traffic profile and portray the power consumption of the HetNet throughout the day. Simulation results show that by applying SC sleeping and our proposed algorithms, the HetNet can save about 20% power daily. The performances of our proposed algorithms are close to that of the optimal algorithm and their computational complexities are remarkably lower.

Network Slicing Based 5G and Future Mobile Networks: Mobility, Resource Management, and Challenges

5G networks are expected to be able to satisfy users' different QoS requirements. Network slicing is a promising technology for 5G networks to provide services tailored for users' specific QoS demands. Driven by the increased massive wireless data traffic from different application scenarios, efficient resource allocation schemes should be exploited to improve the flexibility of network resource allocation and capacity of 5G networks based on network slicing. Due to the diversity of 5G application scenarios, new mobility management schemes are greatly needed to guarantee seamless handover in network-slicing-based 5G systems. In this article, we introduce a logical architecture for network-slicing-based 5G systems, and present a scheme for managing mobility between different access networks, as well as a joint power and subchannel allocation scheme in spectrum-sharing two-tier systems based on network slicing, where both the co-tier interference and cross-tier interference are taken into account. Simulation results demonstrate that the proposed resource allocation scheme can flexibly allocate network resources between different slices in 5G systems. Finally, several open issues and challenges in network-slicing-based 5G networks are discussed, including network reconstruction, network slicing management, and cooperation with other 5G technologies.

Coverage Analysis for Millimeter Wave Networks: The Impact of Directional Antenna Arrays

Millimeter wave (mm-wave) communications is considered a promising technology for 5G networks. Exploiting beamforming gains with large-scale antenna arrays to combat the increased path loss at mm-wave bands is one of its defining features. However, previous works on mm-wave network analysis usually adopted oversimplified antenna patterns for tractability, which can lead to significant deviation from the performance with actual antenna patterns. In this paper, using tools from stochastic geometry, we carry out a comprehensive investigation on the impact of directional antenna arrays in mm-wave networks. We first present a general and tractable framework for coverage analysis with arbitrary distributions for interference power and arbitrary antenna patterns. It is then applied to mm-wave ad hoc and cellular networks, where two sophisticated antenna patterns with desirable accuracy and analytical tractability are proposed to approximate the actual antenna pattern. Compared with previous works, the proposed approximate antenna patterns help to obtain more insights on the role of directional antenna arrays in mm-wave networks. In particular, it is shown that the coverage probabilities of both types of networks increase as a non-decreasing concave function with the antenna array size. The analytical results are verified to be effective and reliable through simulations, and numerical results also show that large-scale antenna arrays are required for satisfactory coverage in mm-wave networks.

Mirror-image-based disjoint multi-paths routing algorithm for maximizing communication efficiency

The growing demands of high-speed and stable next generation 5G cellular networks become the main stream in these years. In order to overcome a bottleneck of high-speed communication which is caused by limited spectrum resources, cognitive radio (CR) network has been proposed as a promising technology in 5G networks. However, in CR networks, primary user (PU) networks lead another novel NP-Hard routing problem on continuous data transmission, especially for some low-latency scenario. To settle this problem, a new mirror-image-based disjoint multi-path routing algorithm (MIDMRA) is presented in this paper. A mirror image algorithm is employed in MIDMRA to simplify the routing challenge of CR network’s multi-channel environment, and an Optimal Path Selection mechanism is equipped to evaluate relationship between CR nodes and PUs when paths are being selected. Through theoretical and simulation analyses, MIDMRA has better performances on continuous communication under PU interferences than other multi-path routing algorithms.

Wavefront spatial‐phase modulation in visible optical communications

AbstractVisible light communications (VLC) are an essential technology in the future 5G networks. In this article, for the first time to best of our knowledge, we introduce the concept of wavefront spatial‐phase modulation VLC transmission, using spatial light modulators. The implemented system exhibits a signal to noise ratio of 18 dB, with a total capacity higher than 1 Gbaud/s.

Cooperative localization in 5G networks: A survey

In upcoming 5G networks, key prospects such as increased bandwidth, smaller cells, higher mobile terminal (MT) densities, multiple radio access technologies, and the capability of device-to-device communication are beneficial for localization. Meanwhile, technologies suggested in 5G, such as massive multiple-in multiple-out, would also benefit from the accurate locations of MTs. Therefore, an opportunity to develop and integrate mobile localization technology in 5G networks has presented itself at this early stage. This paper reviews recent literature relating to localization in 5G networks, and emphasizes the prospect for implementing cooperative localization, which exploits the location information from additional measurements between MTs. To evaluate the accuracy of cooperative localization, a performance evaluation approach is also suggested.

Technologies for 5G Networks: Challenges and Opportunities

Mobile data traffic has grown substantially owing to the widespread use of data-hungry devices such as smart handsets and laptops. This has encouraged researchers and system designers to develop more efficient network designs. The authors review the technologies that can support speeds of multiple Gbps for future fifth-generation (5G) networks. They examine the many challenges, problems, and questions that arise in the research and design stage, and conclude that the anticipated high-traffic demands and low-latency requirements stemming from the Internet of Things (IoT) and machine-to-machine (M2M) communications can be met only with radical changes to the network paradigm. These include harnessing the millimeter-wave band for the dense deployment of small cells. Future wireless systems will include myriad smart features and applications to make 5G the most intelligent and dominant wireless technology thus far.

Current Status and Performance Analysis of Optical Camera Communication Technologies for 5G Networks

This paper investigates optical camera communication (OCC) technologies, targeting new spectrum, multiple-input-multiple-output diversity, transmission access, and novel architectures with augmented reality user experience for the extended 5G wireless network. It provides the current OCC research status and trend pertaining to these technologies, especially an inside view on the revision of IEEE 802.15.7-2011 known as the IEEE 802.15.7m (TG7m) Optical Wireless Communication Task Group. Such standardization activities have a major impact on the development of OCC technologies. In addition, it provides a detailed review of the related literature. Herein, OCC technologies are classified into five categories to elucidate their operations and technical characteristics. Furthermore, a concise performance analysis, numerical simulations, and some comparison of the results obtained for associated systems are presented, and the future directions of research and development are discussed.

Alternating Minimization Algorithms for Hybrid Precoding in Millimeter Wave MIMO Systems

Millimeter wave (mmWave) communications has been regarded as a key enabling technology for 5G networks. In contrast to conventional multiple-input-multiple-output (MIMO) systems, precoding in mmWave MIMO cannot be performed entirely at baseband using digital precoders, as only a limited number of signal mixers and analog-to-digital converters (ADCs) can be supported considering their cost and power consumption. As a cost-effective alternative, a hybrid precoding transceiver architecture, combining a digital precoder and an analog precoder, has recently received considerable attention. However, the optimal design of such hybrid precoders has not been fully understood. In this paper, treating the hybrid precoder design as a matrix factorization problem, effective alternating minimization (AltMin) algorithms will be proposed for two different hybrid precoding structures, i.e., the fully-connected and partially-connected structures. In particular, for the fully-connected structure, an AltMin algorithm based on manifold optimization is proposed to approach the performance of the fully digital precoder, which, however, has a high complexity. Thus, a low-complexity AltMin algorithm is then proposed, by enforcing an orthogonal constraint on the digital precoder. Furthermore, for the partially-connected structure, an AltMin algorithm is also developed with the help of semidefinite relaxation. For practical implementation, the proposed AltMin algorithms are further extended to the broadband setting with orthogonal frequency division multiplexing (OFDM) modulation. Simulation results will demonstrate significant performance gains of the proposed AltMin algorithms over existing hybrid precoding algorithms. Moreover, based on the proposed algorithms, simulation comparisons between the two hybrid precoding structures will provide valuable design insights.

Interference Reduction by Millimeter Wave Technology for 5G-Based Green Communications

The primary goal of this paper is the optimization of data transmissions and connections between 5G base stations (BSs) as well as the improvement of access technologies and transmission methods in consideration of massive multi-input multi-output, a key technology in 5G networks. In order to reach an access technology supported by multiple BSs and small cells, we use 5G millimeter wave (mmWave), due to its high directivity and sensitivity to blockage, to enhance the connection system. In the simulation, we will consider extremely high-frequency band and small angle of mmWave, and arrange obstructions in the environment in view of high attenuation characteristics in mmWave signals. After a wave beam penetrates through a wall, the power of the wave sharply decreases. For reduction of energy consumption, the wave therefore will select an mmWave BS with poor signal quality but without blockage to transmit data. Because the number of macro-cells will affect the communication quality and the computational complexity, this paper especially focuses on three factors of a network: delay, capacity, and path loss, and purposes to figure out the most energy-efficient BS densities for 5G-based green communications.

Real-Time Positioning Based on Millimeter Wave Device to Device Communications

Current generation mobile wireless communication networks are not suitable for real-time positioning applications because timing information is not readily available. Fifth generation (5G) cellular networks provide device to device real-time communications which can be used for real-time positioning. Millimeter-wave (mmWave) transmission is regarded as a key technology in 5G networks. In this paper, several 73-GHz mmWave waveforms are investigated. A new threshold selection algorithm for energy detector-based ranging is proposed which employs a dynamic threshold based on an artificial neural network. The positioning performance using this algorithm with mmWave waveforms is investigated.

Facing the Millimeter-Wave Cell Discovery Challenge in 5G Networks With Context-Awareness

The introduction of millimeter-wave (mm-wave) technologies in the future 5G networks poses a rich set of network access challenges. We need new ways of dealing with legacy network functionalities to fully unleash their great potential, among them the cell discovery procedure is one of the most critical. In this paper, we propose novel cell discovery algorithms enhanced by the context information available through a C-/U-plane-split heterogeneous network architecture. They rely on a geo-located context database to overcome the severe effects of obstacle blockages. Moreover, we investigate the coordination problem of multiple mm-wave base stations that jointly process user access requests. We show that optimizing the resource allocated to the discovery has a great importance in defining perceived latency and supported user request rate. We have performed complete and accurate numerical simulations to provide a clear overview of the main challenging aspects. The results show that the proposed solutions have an outstanding performance with respect to basic discovery approaches and can fully enable mm-wave cell discovery in 5G networks.

Vehicle Positioning Using 5G Millimeter-Wave Systems

Recent growth in traffic and the resulting congestion and accidents has increased the demand for vehicle positioning systems. Existing global navigation satellite systems were designed for line of sight environments and thus accurately determining the location of a vehicle in urban areas with tall buildings or regions with dense foliage is difficult. Fifth generation (5G) cellular networks provide device-to-device communication capabilities which can be exploited to determine the real-time location of vehicles. Millimeter-wave (mmWave) transmission is regarded as a key technology for 5G networks. This paper examines vehicle positioning using 5G mmWave signals. Both a correlation receiver and an energy detector are considered for timing estimation. Furthermore, fixed and dynamic thresholds for energy detection are examined. It is shown that a correlation receiver can provide excellent ranging accuracy but has high computational complexity, whereas an energy detector has low computational complexity and provides good ranging accuracy. Furthermore, the Gaussian raised-cosine pulse (RCP), Gaussian pulse, and Sinc-RCP impulse radio waveforms provide the best performance.