Towards Fully Secure 5G Ultra-Low Latency Communications: A Cost-Security Functions Analysis

Future components to enhance the basic,native security of 5G networks are either complex mechanisms whose impact in the requiring 5G communications are not considered,or lightweight solutions adapted to ultrareliable low-latency communications(URLLC)but whose security properties remain under discussion.Although different 5G network slices may have different requirements,in general,both visions seem to fall short at provisioning secure URLLC in the future.In this work we address this challenge,by introducing cost-security functions as a method to evaluate the performance and adequacy of most developed and employed non-native enhanced security mechanisms in 5G networks.We categorize those new security components into different groups according to their purpose and deployment scope.We propose to analyze them in the context of existing 5G architectures using two different approaches.First,using model checking techniques,we will evaluate the probability of an attacker to be successful against each security solution.Second,using analytical models,we will analyze the impact of these security mechanisms in terms of delay,throughput consumption,and reliability.Finally,we will combine both approaches using stochastic cost-security functions and the PRISM model checker to create a global picture.Our results are first evidence of how a 5G network that covers and strengthened all security areas through enhanced,dedicated non-native mechanisms could only guarantee secure URLLC with a probability of∼55%.

Uniquely Decomposable Constellation Group-Based Sparse Vector Coding for Short Packet Communications

Sparse vector coding(SVC)is emerging as a potential technology for short packet communications.To further improve the block error rate(BLER)performance,a uniquely decomposable constellation group-based SVC(UDCG-SVC)is proposed in this article.Additionally,in order to achieve an optimal BLER performance of UDCG-SVC,a problem to optimize the coding gain of UDCG-based superimposed constellation is formulated.Given the energy of rotation constellations in UDCG,this problem is solved by converting it into finding the maximized minimum Euclidean distance of the superimposed constellation.Simulation results demonstrate the validness of our derivation.We also find that the proposed UDCGSVC has better BLER performance compared to other SVC schemes,especially under the high order modulation scenarios.

Beam Position and Beam Hopping Design for LEO Satellite Communications

The numbers of beam positions(BPs)and time slots for beam hopping(BH)dominate the latency of LEO satellite communications.Aiming at minimizing the number of BPs subject to a predefined requirement on the radius of BP,a low-complexity user density-based BP design scheme is proposed,where the original problem is decomposed into two subproblems,with the first one to find the sparsest user and the second one to determine the corresponding best BP.In particular,for the second subproblem,a user selection and smallest BP radius algorithm is proposed,where the nearby users are sequentially selected until the constraint of the given BP radius is no longer satisfied.These two subproblems are iteratively solved until all the users are selected.To further reduce the BP radius,a duplicated user removal algorithm is proposed to decrease the number of the users covered by two or more BPs.Aiming at minimizing the number of time slots subject to the no co-channel interference(CCI)constraint and the traffic demand constraint,a low-complexity CCI-free BH design scheme is proposed,where the BPs having difficulty in satisfying the constraints are considered to be illuminated in priory.Simulation results verify the effectiveness of the proposed schemes.

A Collaborative Machine Learning Scheme for Traffic Allocation and Load Balancing for URLLC Service in 5G and Beyond

Key challenges for 5G and Beyond networks relate with the requirements for exceptionally low latency, high reliability, and extremely high data rates. The Ultra-Reliable Low Latency Communication (URLLC) use case is the trickiest to support and current research is focused on physical or MAC layer solutions, while proposals focused on the network layer using Machine Learning (ML) and Artificial Intelligence (AI) algorithms running on base stations and User Equipment (UE) or Internet of Things (IoT) devices are in early stages. In this paper, we describe the operation rationale of the most recent relevant ML algorithms and techniques, and we propose and validate ML algorithms running on both cells (base stations/gNBs) and UEs or IoT devices to handle URLLC service control. One ML algorithm runs on base stations to evaluate latency demands and offload traffic in case of need, while another lightweight algorithm runs on UEs and IoT devices to rank cells with the best URLLC service in real-time to indicate the best one cell for a UE or IoT device to camp. We show that the interplay of these algorithms leads to good service control and eventually optimal load allocation, under slow load mobility. .

Reliable and Energy-Aware Job Offloading at Terahertz Frequencies for Mobile Edge Computing

In this paper,we co-design the transmission power and the offloading strategy for job offloading to a mobile edge computing(MEC)server at Terahertz(THz)frequencies.The goal is to minimize the communication energy consumption while providing ultra-reliable low end-to-end latency(URLLC)services.To that end,we first establish a novel reliability framework,where the end-to-end(E2E)delay equals a weighted sum of the local computing delay,the communication delay and the edge computing delay,and the reliability is defined as the probability that the E2E delay remains below a certain pre-defined threshold.This reliability gives a full view of the statistics of the E2E delay,thus constituting advancement over prior works that have considered only average delays.Based on this framework,we establish the communication energy consumption minimization problem under URLLC constraints.This optimization problem is non-convex.To handle that issue,we first consider the special single-user case,where we derive the optimal solution by analyzing the structure of the optimization problem.Further,based on the analytical result for the single-user case,we decouple the optimization problem for multi-user scenarios into several sub-optimization problems and propose a sub-optimal algorithm to solve it.Numerical results verify the performance of the proposed algorithm.

Novel MAC Layer Proposal for URLLC in IndustrialWireless Sensor Networks

Ultra-reliable and low-latency communications(URLLC) has become a fundamental focus of future industrial wireless sensor net-works(IWSNs). With the evolution of automation and process control in industrial environments, the need for increased reliabilityand reduced latencies in wireless communications is even pronounced. Furthermore, the 5G systems specifically target the URLLCin selected areas and industrial automation might turn into a suitable venue for future IWSNs, running 5G as a high speed inter-process linking technology. In this paper, a hybrid multi-channel scheme for performance and throughput enhancement of IWSNsis proposed. The scheme utilizes the multiple frequency channels to increase the overall throughput of the system along with theincrease in reliability. A special purpose frequency channel is defined, which facilitates the failed communications by retransmis-sions where the retransmission slots are allocated according to the priority level of failed communications of different nodes. Ascheduler is used to formulate priority based scheduling for retransmission in TDMA based communication slots of this channel.Furthermore, in carrier-sense multiple access with collision avoidance(CSMA/CA) based slots, a frequency polling is introducedto limit the collisions. Mathematical modelling for performance metrics is also presented. The performance of the proposed schemeis compared with that of IEEE802.15.4e, where the performance is evaluated on the basis of throughput, reliability and the num-ber of nodes accommodated in a cluster. The proposed scheme offers a notable increase in the reliability and throughput over theexisting IEEE802.15.4e Low Latency Deterministic Networks(LLDN) standard.

Wireless Network Requirements and Solutions for the Future Circular Collider:A Hostile Indoor Environment

The European organization for nuclear research(CERN)is planning a high performance particle collider by 2050,which will update the currently used Large Hadron Collider(LHC).The design of the new experiment facility includes the definition of a suitable communication infrastructure to support the future needs of scientists.The huge amount of data collected by the measurement devices call for a data rate of at least 1 Gb/s per node,while the need of timely control of instruments requires a low latency of the order of 0.01μs.Moreover,the main tunnel will be 100 km long,and will need appropriate coverage for voice and data traffic,in a special underground environment subject also to strong radiations.Reliable voice,data and video transmission in a tunnel of this length is necessary to ensure timely and localized intervention,reducing access time.In addition,using wireless communication for voice,control and data acquisition of accelerator technical systems could lead to a significant reduction in cabling costs,installation times and maintenance efforts.The communication infrastructure of the Future Circular Collider(FCC)tunnel must be able to circumvent the problems of radioactivity,omnipresent in the tunnel.Current technologies transceivers cannot transmit in such a severely radioactive environment.This is due to the immediate destruction of any active or passive equipment by radioactivity.The scope of this paper is to determine the feasibility of robust wireless transmission in an underground radioactive tunnel environment.The network infrastructure design to meet the demand will be introduced,and the performance of different wireless technologies will be evaluated.

Dynamic resource allocation schemes for eMBB and URLLC services in 5G wireless networks

The fifth generation(5G)of wireless networks features three core use cases,namely ultra-reliable and low latency communications(URLLC),massive machine type communications(mMTC),and enhanced mobile broadband(eMBB).These use cases co-exist in many practical scenarios and compete for the same set of time and frequency resources,resulting in a natural trade-off in their performance.In this paper,a network supporting both URLLC and eMBB modes of operation is studied.To guarantee the ultra low latency requirement of URLLC,a dynamic resource allocation scheme indicated by a two-dimensional bitmap is proposed.This approach is capable to achieve finer granularity as well as lower false cancellation rate compared to the state-of-the-art methods.A novel power control and indication method is also proposed to dynamically provide different power control parameters to the user equipment(UE),while guaranteeing the reliability requirement of URLLC and minimizing the impact to eMBB.In addition,we devise a dynamic selection mechanism(DSM)to accommodate diverse scenarios,which is empowered with load prediction to become more intelligent.Our extensive system-level simulation results for eMBB-URLLC co-existence scenarios showcase that the perceived throughput of eMBB UEs is increased by 45.3%,while about 13.3% more UEs are enjoying URLLC services with at most 84% transmit power savings compared to the state-of-the-art methods.