5G User Research Articles

Blockchain Based Framework for Modeling and Evaluating 5G Spectrum Sharing

The fifth-generation (5G) cellular technology aims at providing network services at high speed with reliable Quality of Service (QoS). To enable this, 5G deploys Massive Multi-Input Multi-Out-put (MIMO) to increase the capacity of a Base Station (BS) and the efficiency of the network. Provisioning guaranteed and reliable services to support MIMO requires effective resource management. Blockchain is a highly promising solution to enable multi-dimensional management of various resources such as spectrum allocation and user association. It can potentially mitigate spectrum under-utilization and can help in scaling up the deployment of different 5G services. In this article, we present a model for Blockchain-based multi-operator service provisioning for 5G users with Intra and Inter spectrum management among multiple telecom operators. In particular, we present a Blockchain-based implementation model for spectrum sharing between the operators to minimize spectrum under-utilization.

Efficient beam selection and resource allocation scheme for WiFi and 5G coexistence at unlicensed millimetre‐wave bands

To alleviate the spectrum scarcity, the unlicensed 60 GHz band has raised increasing concerns due to its continuous large bandwidth. Considering IEEE 802.11ad/ay has already been deployed in this millimetre-wave band, the coexistence issues with new radio-based access to unlicensed spectrum should be weighed when deploying fifth generation (5G) network. Fortunately, the directional transmission on beams is able to reduce interference significantly, so beam selection can be combined with power control. To maximise spectrum efficiency (SE) of the 5G network while ensuring a friendly coexistence, the authors formulate an optimisation problem by jointly considering beam selection and resource allocation. More specifically, they design a spectrum planning mechanism to reduce the interference between 5G and WiFi, and then a block coordinate descent method is used to determine the user association, beam selection and power control for 5G users, while limiting the interferences to WiFi devices. Simulation results verify the effectiveness of the proposed algorithm in terms of complexity, convergence and SE.

Edge caching and computing in 5G for mobile augmented reality and haptic internet

Deploying cache and computing resources in 5G mobile communication networks is considered an important way to reduce network transmission delay and redundant content transmission, improve content distribution efficiency and network computing processing capabilities. Through the construction of 5G user experience models for mobile augmented reality and tactile internet, the subjective expected experience of 5G users in mobile augmented reality applications is investigated. Based on the experimental results, the composition of mobile augmented reality, and the factors that affect 5G user, mobile 5G user experience model for augmented reality is as a design goal for mobile augmented reality. And research on mobile edge cloud computing powered by renewable energy. Based on the analysis of renewable energy, a 5G user computing task delay and power grid power consumption minimization model was established. It is decomposed into two sub-problems of computational resource allocation and task placement using alternating optimization. The sub-problems of computing tasks under renewable energy supply are obtained by solving the sub-problems. The experimental results show that the offload mode proposed in this paper is superior to the other two modes when the processing ratio before and after the task is less than 1, and the user contact frequency is greater than 0.0014. At the same time, it is obtained that the service node with higher mobility and larger computing power is allocated. The more workload, the more energy can be reduced in the network, thereby improving the performance of the system.

Nanosatellite-5G Integration in the Millimeter Wave Domain: A Full Top-Down Approach

This paper presents a novel network architecture for an integrated nanosatellite (nSAT)-5G system operating in the millimeter-wave (mmWave) domain. The architecture is realized adopting a delay/disruption tolerant networking (DTN) approach allowing end users to adopt standard devices. A buffer aware contact graph routing algorithm is designed to account for the buffer occupancy of the nSATs and for the connection planning derived from their visibility periods. At the terrestrial uplink, a coded random access is employed to realize a high-capacity interface for the typically irregular traffic of 5G users, while, at the space uplink, the DTN architecture is combined with the contention resolution diversity slotted Aloha protocol to match the recent update of the DVB-RCS2 standard. To achieve a reliable testing of the introduced functionalities, an accurate analysis of the statistic of the signal to interference-plus-noise ratio and of the capture probability at each mmWave link is developed by including interference, shadowing, fading, and noise. The application of the designed architecture to data transfer services in conjunction with possible delay reduction strategies, and an extension to inter-satellite communication, are finally presented by estimating the resulting loss/delay performance through a discrete-time discrete-event platform based on the integration of Matlab with Network Simulator 3.

Space-Time-Frequency Machine Learning for Improved 4G/5G Energy Detection

In this paper, the future Fifth Generation (5G New Radio) radio communication system has been considered, coexisting and sharing the spectrum with the incumbent Fourth Generation (4G) Long-Term Evolution (LTE) system. The 4G signal presence is detected in order to allow for opportunistic and dynamic spectrum access of 5G users. This detection is based on known sensing methods, such as energy detection, however, it uses machine learning in the domains of space, time and frequency for sensing quality improvement. Simulation results for the considered methods: k-Nearest Neighbors and Random Forest show that these method significantly improves the detection probability.

Actual Output Power Levels of User Equipment in 5G Commercial Networks and Implications on Realistic RF EMF Exposure Assessment

Here, the results on actual output power levels of the fifth generation (5G) user equipment (UE) operating in commercial 5G networks are presented. Using a network management platform, output power data for several UE were collected over fifteen days. Out of about 545 million power samples obtained from UE operating in two 5G commercial networks, the time-averaged output power, of relevance for electromagnetic field (EMF) exposure assessment, was found to be always less than 43% of the maximum time-averaged UE output power considering time division duplexing. In addition, 95% of the time-averaged power samples were found to be less than 8% of the maximum while the mean value was less than 2%. Despite very conservative assumptions in the applied method, the time-averaged 5G UE output power levels were found to be well below the maximum. These results are in line with the output power levels observed for 3G and 4G UE in previous studies and is of importance to characterize the actual EMF exposure of 5G devices during operation.

5G New Radio Prototype Implementation Based on SDR

The fifth generation (5G) New Radio (NR) has been developed to provide significant improvements in scalability, flexibility, and efficiency in terms of power usage and spectrum as well. To meet the 5G vision, service and performance requirements, various candidate technologies have been proposed in 5G new radio; some are extensions of 4G and, some are developed explicitly for 5G. These candidate technologies include non-Orthogonal Multiple Access (NOMA), and Low Density Parity Check (LDPC) channel coding. In addition, deploying software defined radio (SDR) instead of traditional hardware modules. In this paper we build an open source SDR-based platform to realize the transceiver of the physical downlink shared channel (PDSCH) of 5G NR according to Third Generation Partnership Project (3GPP) standard. We provide a prototype for pairing between two 5G users using NOMA technique. In addition, a suitable design for LDPC channel coding is performed. The intermediate stage of segmentation, rate matching and interleaving are also carried out in order to realize a standard NR frame. Finally, experiments are carried out in both simulation and real time scenario on the designed 5G NR for the purpose of system performance evaluation, and to demonstrate its potential in meeting future 5G mobile network challenges.

Autonomic protection of multi-tenant 5G mobile networks against UDP flooding DDoS attacks

There is a lack of effective security solutions that autonomously, without any human intervention, detect and mitigate DDoS cyber-attacks. The lack is exacerbated when the network to be protected is a 5G mobile network. 5G networks push multi-tenancy to the edge of the network. Both the 5G user mobility and multi-tenancy are challenges to be addressed by current security solutions. These challenges lead to an insufficient protection of 5G users, tenants and infrastructures. This research proposes a novel autonomic security system, including the design, implementation and empirical validation to demonstrate the efficient protection of the network against Distributed Denial of Service (DDoS) attacks by applying countermeasures decided on and taken by an autonomic system, instead of a human. The self-management architecture provides support for all the different phases involved in a DDoS attack, from the detection of an attack to its final mitigation, through making the appropriate autonomous decisions and enforcing actions. Empirical experiments have been performed to protect a 5G multi-tenant infrastructure against a User Datagram Protocol (UDP) flooding attack, as an example of an attack to validate the design and prototype of the proposed architecture. Scalability results show self-protection against DDoS attacks, without human intervention, in around one second for an attack of 256 simultaneous attackers with 100 Mbps bandwidth per attacker. Furthermore, results demonstrate the proposed approach is flow-, user- and tenant-aware, which allows applying different protection strategies within the infrastructure.

Proactive Caching for Vehicular Multi-View 3D Video Streaming via Deep Reinforcement Learning

This paper investigates the problem of proactive caching for multi-view 3D videos in the fifth generation (5G) networks. We establish a mathematical model for this problem, and point out that it is difficult to solve the problem with traditional dynamic programming, then we propose a deep reinforcement learning approach to solve it. First, we model the proactive caching system for multi-view 3D videos as a Markov decision process jointing views selection and local memory allocation. Then, we present an actor-critic, model-free algorithm based on the deep deterministic policy gradient to find effective proactive caching policy. Since the action space is affected by the system state, we embed dynamic k-Nearest Neighbor algorithm into actor-critic algorithm to implement the deep reinforcement learning algorithm working in an action space of variable size. Finally, the numerical results are given to demonstrate that the proposed solution can effectively maintain high-quality user experience for high-mobility 5G users moving among small cells. We also investigate the impact of configuration of critical parameters on the performance of the algorithm.

5G Evolution: A View on 5G Cellular Technology Beyond 3GPP Release 15

The 5G System is being developed and enhanced to provide unparalleled connectivity to connect everyone and everything, everywhere. The first version of the 5G System, based on the Release 15 (“Rel-15”) version of the specifications developed by 3GPP, comprising the 5G Core (5GC) and 5G New Radio (NR) with 5G User Equipment (UE), is currently being deployed commercially throughout the world both at sub-6 GHz and at mmWave frequencies. Concurrently, the second phase of 5G is being standardized by 3GPP in the Release 16 (“Rel-16”) version of the specifications which will be completed by March 2020. While the main focus of Rel-15 was on enhanced mobile broadband services, the focus of Rel-16 is on new features for URLLC (Ultra-Reliable Low Latency Communication) and Industrial IoT, including Time Sensitive Communication (TSC), enhanced Location Services, and support for Non-Public Networks (NPNs). In addition, some crucial new features, such as NR on unlicensed bands (NR-U), Integrated Access & Backhaul (IAB) and NR Vehicle-to-X (V2X), are also being introduced as part of Rel-16, as well as enhancements for massive MIMO, wireless and wireline convergence, the Service Based Architecture (SBA) and Network Slicing. Finally, the number of use cases, types of connectivity and users, and applications running on top of 5G networks, are all expected to increase dramatically, thus motivating additional security features to counter security threats which are expected to increase in number, scale and variety. In this paper, we discuss the Rel-16 features and provide an outlook towards Rel-17 and beyond, covering both new features and enhancements of existing features. 5G Evolution will focus on three main areas: enhancements to features introduced in Rel-15 and Rel-16, features that are needed for operational enhancements, and new features to further expand the applicability of the 5G System to new markets and use cases.

Analysis of Impacts of Expected RF EMF Exposure Restrictions on Peak EIRP of 5G User Equipment at 28 GHz and 39 GHz Bands

Above 6 GHz, radio frequency (RF) electromagnetic field (EMF) exposure from the mobile communication user equipment (UE) should be assessed in terms of incident power density, rather than specific absorption rate as below 6 GHz. Such regulatory RF EMF restrictions will constrain the transmit power of the UE and its peak equivalent isotropically radiated power (EIRP). This paper provides an analysis of the peak EIRP levels of UE containing code-book-based beamforming arrays at 28 GHz and 39 GHz. Different types of antenna elements, incremental element spacing, 4- and 8-element array configurations, and realistic housing integration are considered. The analysis and results show that in realistic housing integration, the 3GPP requirements on minimum peak EIRP can be generally met under the expected RF EMF exposure restrictions.

Towards the transversal detection of DDoS network attacks in 5G multi-tenant overlay networks

Currently, there is no any effective security solution which can detect cyber-attacks against 5G networks where multitenancy and user mobility are some unique characteristics that impose significant challenges over such security solutions. This paper focuses on addressing a transversal detection system to be able to protect at the same time, infrastructures, tenants and 5G users in both edge and core network segments of the 5G multi-tenant infrastructures. A novel approach which significantly extends the capabilities of a commonly used IDS, to accurately identify attacking nodes in a 5G network, regardless of multiple network traffic encapsulations, has been proposed in this paper. The proposed approach is suitable to be deployed in almost all 5G network segments including the Mobile Edge Computing. Both architectural design and data models are described in this contribution. Empirical experiments have been carried out a realistic 5G multi-tenant infrastructures to intensively validate the design of the proposed approach regarding scalability and flexibility.

Quasi-Color-Free LD-Based Long-Reach 28-GHz MMWoF With 512-QAM OFDM

By using a 512-quadrature amplitude modulating-orthogonal frequency division multiplexing (512-QAM OFDM) data stream with universal filtered multicarrier (UFMC) process to directly encode a quasi-color-free laser diode (QCFLD) with dual-mode carrier, a long-reach 28-GHz millimeter-wave over fiber (MMWoF) link over 50-km single-mode fiber (SMF) is demonstrated for future fiber network with 5G wireless link. At the fiber-wired optical transmission stage, the dual-mode QCFLD can support raw data rates up to 54, 42, and 24 Gbit/s after 0, 25, and 50-km SMF transmissions. The data-rate degradation results from chromatic dispersion induced power fading effect. The 28-GHz MMW carrier optically heterodyned at remote node with a carrier-to-noise ratio of 53.5 dB is generated after 25-km SMF propagation, which achieves 6-m free-space transmission at 16 Gbit/s. Lengthening the SMF to 50 km still allows the MMWoF for wireless transmission at 16-Gbit/s over 5 m and 14-Gbit/s over 10 m. To favor the 5G wireless access with high data capacity, the UFMC processed QAM-OFDM was further adopted for noise suppression via sidelobe filtering operation. By lengthening the cyclic prefix and the filter window for the OFDM, the tradeoff between data quality and net-data-rate ratio without and with UFMC process is discussed. With UFMC, the MMWoF transmission capacity can deliver 3-GHz wide 32-QAM UFMC processed OFDM data at 15 Gbit/s over 50 km in SMF and 10 m in free space. Even within a limited subcarrier bandwidth as narrow as 140 MHz for practical 5G users, the 512-QAM UFMC data can be allocated to provide a raw data rate of 1.26 Gbit/s.

RF Compliance Study of Temperature Elevation in Human Head Model Around 28 GHz for 5G User Equipment Application: Simulation Analysis

The crowdedness of current cellular bands and the demand for higher transmission speed prompt the use of the millimeter-wave spectrum for the next-generation mobile communication. In the millimeter-wave frequencies, the dosimetric quantity for human exposure to electromagnetic fields changes from the specific absorption rate to incident power density. In this paper, we used 28-GHz beam-steering patch arrays, a dipole antenna, and plane waves to investigate the temperature elevation in a multi-layer model of human head and its correlation with power density metrics. The power density averaged over one square-centimeter in free space and the peak temperature elevation in tissue at 28 GHz have good correlation. The peak temperature elevation indicated by the power density averaged one square-centimeter also agrees well with the peak temperature elevation induced by the plane waves. The results show that the averaging area of a few square-centimeters may be a good candidate for the spatial-average power density. The findings provide valuable input to the ongoing revision and updating of relevant safety standards and guidelines.

Power Density Measurements at 15 GHz for RF EMF Compliance Assessments of 5G User Equipment

In this paper, different measurement schemes are studied in order to investigate the possibilities and limitations of scalar- and vector-based measurement systems for radio frequency electromagnetic fields compliance assessments of fifth generation mobile communication user equipment (UE). Two UE antenna array designs, transmitting at 15 GHz and employing patch and notch antenna elements, are considered for different phase excitations. Using free space power density as the exposure metric, the maximum permissible transmitted power of UE, compliant with the maximum permissible exposure limits specified by the U.S. Federal Communications Commission (FCC) and the basic restrictions of the International Commission on Non-Ionizing Radiation Protection, is determined. The accuracy of different measurement schemes is assessed using numerical simulation. Verifying measurements is carried out in a semianechoic chamber. The results indicate that, for UE employing array antennas and intended to be used in immediate vicinity of the human body, scalar measurement systems used in combination with straightforward field combination techniques will lead to overly conservative results. A more accurate and less conservative approach for these products is to conduct separate measurements for different excitations in order to span the space of possible excitations. This will result in a more complicated measurement setup and increase the measurement time, which points to a need for very fast measurement systems.

Wavelet‐based cognitive SCMA system for mmWave 5G communication networks

Fifth generation (5G) communication networks can achieve high spectral efficiency using sparse code multiple access (SCMA) scheme when large number of users are trying to transmit their data simultaneously. The sparsity of SCMA codewords offers the possibility of applying a low-complexity message passing algorithm as an alternative to maximum likelihood detector. However, the requirement of densely deployed 5G users is to opportunistically explore new frequencies via cognitive features to overcome spectrum scarcity challenges. In this study, spectrum sensing enables cognitive radio capabilities for the SCMA system applied in millimetre wave (mmWave) 5G communications. Proposed cognitive SCMA system can sense the spectrum holes and adapt the transmission in order to utilise the available subcarriers. Besides, wavelet packet transform based techniques are used instead of conventional Fourier-based spectrum sensing (FSS) and orthogonal frequency-division multiple access (OFDMA). Wavelet packet spectrum sensing offers more accurate estimation of frequency and power compared with FSS. On the other hand, wavelet packet multiple access is more flexible and robust against interference compared with OFDMA. The simulation results verify that the proposed method can significantly improve the performance of SCMA system in terms of probabilities of false alarm and detection, and symbol error rate.

Output Power Levels of 4G User Equipment and Implications on Realistic RF EMF Exposure Assessments

The aim of this paper is to present results on output power level distributions of 4G user equipment (UE) using data applications based on a very large number of samples collected over seven days in a long-term evolution (LTE) operating network. The output power data have been obtained through network-based measurements conducted for about 7000 UE connected to 41 LTE radio base stations located in rural, suburban, urban, and indoor environments in Sweden. More than 300 000 power samples were collected. In rural environments, the 95th percentile time-averaged output power values were found to be 2.2% of the maximum available power for LTE UE, while the corresponding values were less than 1% in other environments. The mean output powers in all the environments were found to be less than 1% of the maximum available output power. These values are in line with results obtained for 3G UE despite an almost tenfold increase in the achievable peak data throughput. The findings show that knowledge on realistic power levels is important for accurate assessments of the radio frequency electromagnetic field exposure from mobile communication equipment.

SDN Enabled 5G-VANET: Adaptive Vehicle Clustering and Beamformed Transmission for Aggregated Traffic

With the anticipated arrival of autonomous vehicles, supporting vehicle generated data traffic due to the dramatically increased use of in-vehicle mobile Internet access will become extremely challenging in 5G-based vehicular networks. This is mainly due to the high mobility of vehicles on the road and the high complexity of 5G HetNets. In order to support the increasing traffic and improve Het- Net management, an SDN enabled 5G VANET is proposed in this article, where neighboring vehicles are clustered adaptively according to real-time road conditions using SDN's global information gathering and network control capabilities. With proposed dual cluster head design and dynamic beamforming coverage, both trunk link communication quality and network robustness of vehicle clusters are significantly enhanced. Furthermore, an adaptive transmission scheme with selective modulation and power control is proposed to improve the capacity of the trunk link between the cluster head and base station. With cooperative communication between the mobile gateway candidates, the latency of traffic aggregation and distribution is also reduced. Computer simulation results show that the proposed design substantially improved 5G users' bit error rate and trunk link throughput rate.

Proactive Caching for Mobile Video Streaming in Millimeter Wave 5G Networks

Mobile video streaming is fundamental to advanced applications in the fifth generation (5G) networks. Millimeter wave (mmWave) communication represents a leading 5G technology, which provides rich bandwidth and, therefore, great potentials for high-quality mobile video streaming. However, mobile video streaming in mmWave 5G networks faces fundamental challenges due to mmWave antenna directivity and high user mobility. As such, users typically have short connection durations and frequent handoffs, making video streaming suffer from long handoff delays and connection latency. In this paper, we tackle the issues by developing a caching-based mmWave framework, which precaches video contents at the base station for handoff users and thus significantly reduces the connection and retrieval delays. As a result, high-mobility users with frequent handoffs can enjoy continuous high-quality video streaming. Specifically, we model the proposed system as a cache management problem and attain optimal video streaming quality by using Markov decision process to dynamically allocate proper cache memory space of each base station to mobile users. A cell-by-cell decomposition method is proposed to solve the dynamic programming problem with significantly reduced computational complexity. Using extensive simulations, we demonstrate that the proposed solution can effectively maintain high-quality mobile video streaming for high-mobility 5G users moving among mmWave small cells with directional antenna.

Personal Mobile Radars with Millimeter-Wave Massive Arrays for Indoor Mapping

The adoption of millimeter-wave technology could open the possibility to integrate massive antenna arrays inside future 5G user mobile devices, with the possibility to enable new interesting applications. Within this context, in this paper we put forth the concept of a personal mobile radar operating at millimeter-waves and consisting of a massive array for accurate environmental mapping. Frequency selectivity and phase quantization effects are accounted for to characterize the achievable angle and range resolution necessary to collect environmental information. Successively, we propose an effective grid-based Bayesian mapping approach by introducing a new state-space model, which profits of the beneficial effects of the massive antenna array characteristics. Numerical results show that the idea herein investigated is feasible, and that a significant mapping performance is attainable even employing coarse antenna arrays provided that the number of antenna elements is sufficiently high.