Multi-radio Access Technology Research Articles

Distributed load balancing algorithm considering QoS for next generation multi-RAT HetNets

In this paper, we propose a distributed load balancing algorithm for multi-radio access technology (multi-RAT) heterogeneous networks (HetNets). The random deployment of small cells and the user mobility make the network load distribution uneven, which degrades overall network capacity and the QoS for users. Furthermore, the disparate capabilities of multiple RATs such as the different propagation delays in terrestrial and non-terrestrial RATs affect the latency requirements. To balance the network load in multi-RAT HetNets, we propose a distributed game-theoretic algorithm considering QoS for users. To that end, a cost function is defined to reflect the cell load status, required data rates, and delay constraints. In the proposed algorithm, overloaded cells iteratively minimize user cost in a distributed manner by associating a user with a less-loaded cell based on its cost. We provide analysis to show that minimizing each user cost in the game theory setting achieves a balanced load distribution among cells. We show that the proposed algorithm brings each cell load to a balanced state in a finite number of iterations. Via simulation, we show that the proposed algorithm achieves superior performance in terms of even load distribution, network throughput, and the number of users with satisfactory QoS.

LATEST ADVANCES ON SECURITY ARCHITECTURE FOR 5G TECHNOLOGY AND SERVICES

The roll out of the deployment of the 5G technology has been ongoing globally. The deployment of the technologies associated with 5G has seen mixed reaction as regards its prospects to improve communication services in all spares of life amid its security concerns. The security concerns of 5G network lies in its architecture and other technologies that optimize the performance of its architecture. There are many fractions of 5G security architecture in the literature, a holistic security architectural structure will go a long way in tackling the security challenges. In this paper, the review of the security challenges of the 5G technology based on its architecture is presented along with their proposed solutions. This review was carried out with some keywords relating to 5G securities and architecture; this was used to retrieve appropriate literature for fitness of purpose. The 5G security architectures are mojorly centered around the seven network security layers; thereby making each of the layers a source of security concern on the 5G network. Many of the 5G security challenges are related to authentication and authorization such as denial-of-service attacks, man in the middle attack and eavesdropping. Different methods both hardware (Unmanned Aerial Vehicles, field programmable logic arrays) and software (Artificial intelligence, Machine learning, Blockchain, Statistical Process Control) has been proposed for mitigating the threats. Other technologies applicable to 5G security concerns includes: Multi-radio access technology, smart-grid network and light fidelity. The implementation of these solutions should be reviewed on a timely basis because of the dynamic nature of threats which will greatly reduce the occurrence of security attacks on the 5G network.

Performance Analysis of sub-6 GHz/mmWave NOMA Hybrid-HetNets Using Partial CSI

The ever-increasing number of wireless users (or devices) and their varied demand require the need for an advanced architecture for the future wireless network. To support massive connectivity, non-orthogonal multiple access (NOMA) has been recognized as a promising solution. NOMA increases the number of simultaneous connections using available resources for users with varying demands. Furthermore, recent measurements and experiments suggest that wide underutilized bandwidth available at millimeter-wave (mmWave) frequencies provide high data rate and therefore are capable of addressing the issue of spectrum scarcity at sub-6 GHz bands utilized by the 4 G network. Consequently, co-existence of multi-radio access technologies (RATs) for 5 G and beyond networks has been of interest to both industries and academia. In this context, this work studies the co-existence of the two RATs, namely, sub-6 GHz and mmWave communication using NOMA-enabled hybrid heterogeneous network (NOMA-HHN) for massive connectivity. The application of NOMA requires ordering users, which in turn requires the knowledge of users' channel state information (CSI). However, gathering and processing CSI of such a large number of users is difficult to implement in practice. Thus, a solution based on partial CSI is proposed. Additionally, a feedback scheme for user scheduling and RAT selection using dual association is proposed to reduce the initial access delay in beam-training at the mmWave network. Moreover, utilizing directional nature of the mmWave communication, random beamforming is used to reduce system overhead in a network with massive users. The analytical results are confirmed using Monte-Carlo simulation, and various significant advantages are noted for the proposed NOMA-HHN over existing architectures.

Age of Processing-Based Data Offloading for Autonomous Vehicles in MultiRATs Open RAN

Today, vehicles use smart sensors to collect data from the road environment. This data is often processed onboard of the vehicles, using expensive hardware. Such onboard processing increases the vehicle’s cost, quickly drains its battery, and exhausts its computing resources. Therefore, offloading tasks onto the cloud is required. Still, data offloading is challenging due to low latency requirements for safe and reliable vehicle driving decisions. Moreover, age of processing was not considered in prior research dealing with low-latency offloading for autonomous vehicles. This paper proposes an age of processing-based offloading approach for autonomous vehicles using unsupervised machine learning, Multi-Radio Access Technologies (multi-RATs), and Edge Computing in Open Radio Access Network (O-RAN). We design a collaboration space of edge clouds to process data in proximity to autonomous vehicles. To reduce the variation in offloading delay, we propose a new communication planning approach that enables the vehicle to optimally preselect the available RATs such as Wi-Fi, LTE, or 5G to offload tasks to edge clouds when its local resources are insufficient. We formulate an optimization problem for age-based offloading that minimizes elapsed time from generating tasks and receiving computation output. To handle this non-convex problem, we develop a surrogate problem. Then, we use the Lagrangian method to transform the surrogate problem to unconstrained optimization problem and apply the dual decomposition method. The simulation results show that our approach significantly minimizes the age of processing in data offloading with 90.34% improvement over similar method.

Location-Based Discovery and Network Handover Management for Heterogeneous IEEE 802.11ah IoT Applications

Low-Power Wide-Area Network (LPWAN) multi-Radio Access Technology (RAT) devices combine features of different low-power network technologies to flexibly manage heterogeneous requirements stemming from various Internet of Things (IoT) applications. IEEE 802.11ah is a novel technology that is envisioned to provide a “bridge” between Wi-Fi and s, thus it has been often considered as one of the supporting technologies in multi-RAT devices. In such multi- RAT scenarios, network discovery and handover procedures need to be utilized for determining the availability of a given technology and managing if the connection to the technology should be initiated. However, traditional discovery and handover procedures, such as beacon listening, have to be performed periodically and, therefore, consume substantial amount of energy, making them unsuitable for battery-powered IoT devices. To address this issue, we present a mechanism that is able to make more optimal discovery and handover decisions by leveraging the physical location information of the multi- RAT devices. We demonstrate how this approach is feasible in performing energy efficient handovers between a technology (NB-IoT) and IEEE 802.11ah based on estimated location. We do that by showing that the location-based procedure substantially reduces the energy consumption of the mobile device compared to the traditional discovery based on periodical listening for beacons, while maintaining comparable duration of the device’s association to IEEE 802.11ah. Moreover, we evaluate the energy and delay overheads caused by the localization service, showing only slight effects on the performance of the mechanism.

Multi-Radio Access Software-Defined Vehicular Network

With the promising advances in the telecommunication and automotive industries, there are increasing concerns on the reliability of Intelligent Transportation Systems (ITS) applications and standardization efforts. Nowadays, vehicles are empowered with innovative communications and sensing capabilities to accelerate next-generation Connected and Autonomous Vehicles (CAV) or Vehicle-to-Everything (V2X) communications. Furthermore, V2X is based on many radio access technologies including Dedicated Short-Range Communications (DSRC), Cellular-V2X, and millimeter-wave. It is expected that a single technology is incapable to support the diverse QoS and reliability requirements of vehicular safety and non-safety applications. Therefore, recent research works have investigated and developed different approaches to enable multi-radio access technologies (Multi-RAT) in V2X networks to support these multitudes of requirements. In addition, the heterogeneity of diverse radio access technologies and rigidity in their deployment increases the complexity of the network management. Complications may also arise from inefficient resource utilization due to the complexity of an optimum RAT selection or multi-link establishment through Multi-RATs. Therefore, a global monitoring paradigm such as Software-Defined Vehicular Network (SDVN) has been identified as a solution to reduce this bottleneck, by adding flexibility and agility to the vehicular network. This paper extensively reviews recent related works on Multi-RAT V2X networks focusing on the opportunistic selection mechanism of RAT, allocation of radio resources, and simultaneous establishment of multi-link over a heterogeneous network. Consequently, we have outlined the SDVN architecture, layers, features, and significance towards enhancing the performance of such Multi-RAT networks. Finally, several potential challenges with probable solutions and opportunities are discussed.

DRL-Based Joint RAT Association, Power and Bandwidth Optimization for Future HetNets

Multi-radio access technologies (RATs) networks, where various heterogeneous networks (HetNets) coexist, are in service nowadays and considered a main enabling technology for future networks. In such networks, managing radio resources is challenge. In this letter, we address the problem of RATs-edge devices (EDs) association and joint power and bandwidth allocation in multi-RAT multi-homing HetNets. The problem is formulated as mixed-integer non-linear programming, whose objective is to cost-effectively maximize the network constrained sum-rate. Due to the high complexity of the problem, we propose a multi-agent deep reinforcement learning (DRL)-based scheme to solve it. Simulation results show that our proposed scheme efficiently learns the optimal policy and enhances the network sum-rate by 80.95% compared to key benchmarks.

A novel approach to fairness-aware energy efficiency in multi-RAT heterogeneous networks

Heterogeneous cellular networks are a viable solution in response to the growing demand for broadband services in the new-generation wireless networks. It is more challenging to manage resources (e.g., user association and power control) in multi-radio access technology (multi-RAT) HetNets than in conventional single-tier cellular networks due to the higher computational complexity and energy efficiency constraints. In addition, given the novel services and resource limitation of the user layer, energy efficiency and fairness assurance are critical issues in the uplink. Considering the uplink fairness criterion, this paper proposes a dynamic optimization model which maximizes the total uplink/downlink energy efficiency in addition to providing the essential coverage and capacity of heterogeneous cellular networks. Based on the non-convex characteristics of the energy efficiency maximization model, the mathematical model can be formulated into two subproblems, i.e., resource optimization and user association. In this approach, a subgradient method is applied for fair resource management and also successive convex approximation and dual decomposition methods are adopted to solve the proportional fairness problem. The simulation results exhibit a considerable throughput increase of 25% and 18% on average for random and hotspot user distributions, respectively. Based on the numerical results, the adaptive radio resource management method reduces the rate of vertical handoffs between RATs, which leads to more stable communications for the users. It also proved that the proposed approach managed to significantly improve the total network energy efficiency by up to 40%.

MEC-based architecture for interoperable and trustworthy internet of moving things

The expansion of the Internet of Moving Things (IoMT) leads to limitless and continuous working playgrounds exploited by highly dynamic end devices. This requires the adoption of multi-Radio Access Technologies (RATs)-based strategies to provide IoMT units with ubiquitous connectivity. To this end, the development of secure bootstrapping and authentication mechanisms is necessary to permit the secure operation of end devices. Given the transmission and power limitations of these elements, current cryptographic solutions do not address these stringent requirements. For that reason, in the study we present a Multi-Access Edge Computing (MEC)-based end-to-end architecture that enables an efficient and secure authentication and key agreement between end devices and network servers over heterogeneous resource-limited networks such as the Low Power Wide Area Networks (LPWANs). Our proposal is based on the Authentication, Authorization, and Accounting (AAA) architecture and the recent Internet Engineering Task Force initiatives Static Context Header Compression and Low-Overhead CoAP-EAP. The results obtained from experimental tests reveal the validity of the proposal as it enables constrained IoMT devices to gain IPv6 connectivity as well as performs end-to-end secure authentication with notable reliability and controlled latency.

Multi-RAT Orchestration Method for Heterogeneous Wireless Networks

Currently, energy efficiency (EE) of wireless communication is essential where many wireless networks with different Radio Access Technologies (RATs) coexist together. The RATs can be effectively selected and managed on a higher level to achieve maximum EE and save energy, e.g., save batteries. The approach to wireless traffic steering in mobile networks with a proof-of-concept solution is presented in this paper, owing to the developed high-level multi-RAT (multi-Radio Access Technology) heterogonous network orchestration approach. Based on the high-level network orchestrator, which traces network indicators, it is possible to decrease the user mobile terminal energy consumption, keeping traffic speed at an adequate level. The solution discussed was implemented in an experimental testbed with Software Defined Radio transmission systems. Downlink and uplink data links were toggled among different RATs according to the decisions that were taken by the end-to-end multi-RAT orchestrator based on the received proper network traffic-related indicators. The authors focused on finding an adequate algorithm that allowed for reduced power usage in the user terminal and made the attempt to verify how to reach the power reduction without introducing RAT-specific rules. The results showed that the proposed orchestration EE reduction was observed (from 11% to 42% for two different scenarios) in relation to the single LTE network deployment. The orchestration compared to the Wi-Fi network does not provide EE gain (−7% and 0%, respectively), but allows the user to achieve a higher data rate (23% and 39% gain, respectively), thus keeping the energy efficiency at almost the same level.

Heterogeneous SDN controller placement problem—The Wi-Fi and 4G LTE-U case

The widespread deployment of 5G wireless networks has brought about a radical change in the nature of mobile data consumption. It requires the deployment of Long Term Evolution to the unlicensed spectrum (LTE-U) to alleviate the shortage of available licensed spectrum while Wi-Fi is the most dominant radio access technology in the unlicensed spectrum. This has led to suggestions concerning the coexistence of multi radio access technologies such as Wi-Fi and LTE-U. Clearly, Software Defined Networks (SDN) can utilize the LTE-U radio bandwidth efficiently. The SDN paradigm decouples the network’s control logic from the underlying routers and switches, which promotes centralization of network control. The controller placement problem is crucial to SouthBound interface optimization and involves the location of the controllers, their number and the assignment function of switches to controllers. In this paper, a novel strategy is presented to address the wireless controller placement problem, which improves the throughput, link failure probability and the transparency on the SouthBound interface in cases where hybrid providers choose either LTE-U or Wi-Fi as link layer technologies. The problem of determining the placement of LTE-U and Wi-Fi based controllers is modeled and two heuristic solutions are proposed. Simulations show that the proposed algorithms provide a fast and efficient solution.

Machine learning-based radio access technology selection in the Internet of moving things

The Internet of Moving Things (IoMT) takes a step further with respect to traditional static IoT deployments. In this line, the integration of new eco-friendly mobility devices such as scooters or bicycles within the Cooperative-Intelligent Transportation Systems (C-ITS) and smart city ecosystems is crucial to provide novel services. To this end, a range of communication technologies is available, such as cellular, vehicular WiFi or Low-Power Wide-Area Network (LPWAN); however, none of them can fully cover energy consumption and Quality of Service (QoS) requirements. Thus, we propose a Decision Support System (DSS), based on supervised Machine Learning (ML) classification, for selecting the most adequate transmission interface to send a certain message in a multi-Radio Access Technology (RAT) set up. Different ML algorithms have been explored taking into account computing and energy constraints of IoMT enddevices and traffic type. Besides, a real implementation of a decision tree-based DSS for micro-controller units is presented and evaluated. The attained results demonstrate the validity of the proposal, saving energy in communication tasks as well as satisfying QoS requirements of certain urgent messages. The footprint of the real implementation on an Arduino Uno is 444 bytes and it can be executed in around 50 µs.

CARAMEL: results on a secure architecture for connected and autonomous vehicles detecting GPS spoofing attacks

The main goal of the H2020-CARAMEL project is to address the cybersecurity gaps introduced by the new technological domains adopted by modern vehicles applying, among others, advanced Artificial Intelligence and Machine Learning techniques. As a result, CARAMEL enhances the protection against threats related to automated driving, smart charging of Electric Vehicles, and communication among vehicles or between vehicles and the roadside infrastructure. This work focuses on the latter and presents the CARAMEL architecture aiming at assessing the integrity of the information transmitted by vehicles, as well as at improving the security and privacy of communication for connected and autonomous driving. The proposed architecture includes: (1) multi-radio access technology capabilities, with simultaneous 802.11p and LTE-Uu support, enabled by the connectivity infrastructure; (2) a MEC platform, where, among others, algorithms for detecting attacks are implemented; (3) an intelligent On-Board Unit with anti-hacking features inside the vehicle; (4) a Public Key Infrastructure that validates in real-time the integrity of vehicle’s data transmissions. As an indicative application, the interaction between the entities of the CARAMEL architecture is showcased in case of a GPS spoofing attack scenario. Adopted attack detection techniques exploit robust in-vehicle and cooperative approaches that do not rely on encrypted GPS signals, but only on measurements available in the CARAMEL architecture.

A low cost PON-FSO based fronthaul solution for 5G CRAN architecture

The continuous growth in mobile network traffic driven by the extensive range of new user applications, for instance, interactive e-learning, social networking sites, remote medical service and machine-to-machine communication has pushed the mobile network operators to enhance their network capacity. The main solution to deal with this problem is to deploy thousands of low power small cell base stations through Centralized Radio Access Network (C-RAN) architecture. The C-RAN offers a green solution for the deployment of small cells with advanced wireless features such as coordinated multipoint, joint scheduling, and multi-radio access technology. However, the provision of fronthaul connections to these small cells at a reasonable cost is a big concern for mobile operators especially when fronthaul link requires high capacity. Therefore, in this work, we present the hybrid fronthaul approach for C-RAN architecture based on Passive Optical Network (PON) and Free Space Optics (FSO) to enhance flexibility and minimize deployment costs of fronthaul network. The paper aims to examine the Total Cost of Ownership (TCO) of fronthaul networks taking into account both capital expenditure and operational expenditure costs, moreover, the efficacy of our proposed model is also analyzed by using optisystem simulator. The proposed model, in terms of TCO, is compared with the standalone PON based fronthaul system in green field scenarios. The numerical results revealed that the hybrid PON-FSO based fronthaul solution can save up to 42.89% TCO associated with small cell fronthaul architecture.

Interleaver Assignment Solution for Multi Radio Access Technology Supported 5G Networks

Fifth Generation (5G) communication networks support multiple radio access technologies, popularly known as multi-RAT, to facilitate services to all the mobile subscribers irrespective of their subscription for any old generation network. Unique interleaver assignment to each active mobile subscriber within intra-RAT communication is comparatively easy task. However, the same becomes a challenging issue when multi-RAT supported communication is required to be dealt with. This paper reveals a theoretical backend control signaling solution to overcome this challenge. The proposed solution is named as Store-Regenerate-Recall (SRR) technique for interleaver assignment in multi-RAT supported 5G network. This solution is quite effective and easy-to-implement for handling interleaver assignment issue at the 5G network end in multi-RAT scenarios without any subscriber identity clash. Overall, the method is of great significance when multi-carrier multi-RAT solutions are intended to be developed for 5G networks.

MULTI-RAT BASED ADAPTIVE QUALITY OF SERVICE (QOS) MANAGEMENT IN WBAN

Wireless body area network (WBAN), a sub-branch of wireless sensor networks (WSN), helps continuous monitoring of various conditions and states of a human body. It has vast application areas, including self-care, battlefield, health, sports, assisted living, and entertainment. In WBAN, sensors (e.g., ECG, EEG, EMG, and temperature) may transmit sensed information of the subject under observation to a personal server which directs it to the main server for the analysis. The requirement of an application in terms of reliability and delay varies depending on the situation and environment. For instance, the high network delay and jitter for a health application may lead to a human death due to urgent response requirement. The major challenge faced by WBAN is to offer high Quality of Service (QoS). To ensure high QoS in WBAN, different techniques are proposed but all these techniques have considered different layers for different radio technologies. The current study put forwards an adaptive Multi-Radio Access Technologies (multi-RAT) based platform for the WBAN. Multi-RAT proposes a convergence/adaptation layer to entertain increasing request rate of WBAN applications. As a result, throughput, delay, and blocking probability for each request are minimized.

Performance Analysis of NOMA Enabled Hybrid Network With Limited Feedback

This paper investigates the coexistence of multi radio access technology (RAT) using Ultra High Frequency (UHF) small base station (SBS) and millimeter Wave (mmWave) SBS tier in a heterogeneous network (HetNet). To support large number of users, non-orthogonal multiple access (NOMA) is used in the SBS tier. For NOMA, the SBS needs to obtain users’ channel state information (CSI) to determine their ordering. Acquiring CSI at the SBS is a challenging task due to the massively increased number of users. The existing literature uses limited feedback from the users as a potential solution to assist the SBS in user ordering, when perfect CSI is not known at the base station. The limited feedback from the users in the existing literature is used only for user ordering. However, in the proposed work, unlike using limited feedback only for user ordering, the usage of limited feedback from the users is twofold. The first one is for the user ordering and the second is for the RAT selection. The impact of the proposed feedback system is analyzed in a NOMA enabled hybrid UHF/mmWave downlink HetNet. Numerical results show that the proposed feedback system achieves significant improvement in the outage probability.

Enabling Roaming Across Heterogeneous IoT Wireless Networks: LoRaWAN MEETS 5G

Despite the latest research efforts to foster mobility and roaming in heterogeneous Low Power Wide Area Networks (LP-WANs) networks, handover roaming of Internet of Things (IoT) devices is not a success mainly due to fragmentation and difficulties to establish trust across different network domains as well as the lack of interoperability of different LP-WANs wireless protocols. To cope with this issue, this paper proposes a novel handover roaming mechanism for Low Range Wide Area Network (LoRaWAN) protocol that relies on the trusted 5G network to perform IoT device's authentication and key management, thereby extending the mobility and roaming capabilities of LoRaWAN to global scale. The proposal enables interoperability between 5G network and LoRaWAN, whereby multi Radio Access Technologies IoT (multi-RAT IoT) devices can exploit both technologies interchangeably, thereby fostering novel IoT mobility and roaming use cases for LP-WANs not experimented so far. Two integration approaches for LoRaWAN and 5G have been proposed, either assuming 5G spectrum connectivity with standard 5G authentication or performing 5G authentication over the LoRaWAN network. The solution has been deployed, implemented and validated in a real and integrated 5G-LoRaWAN testbed, showing its feasibility and security viability.

Location-Based Discovery and Vertical Handover in Heterogeneous Low-Power Wide-Area Networks

Low-power wide-area network (LPWAN) multi-radio access technology (RAT) devices promise enabling Internet of Things (IoT) use-cases that simultaneously require high coverage and data rates, and low energy consumption. For such devices, active probing is usually used for discovering if communication between a mobile terminal (MT) and a base station (BS) or a handover of the MT across LPWAN technologies should be initiated. Because of continuous probing, this procedure increases signaling overhead and energy consumption of the MT. Assuming that the location information of the MT is required for enabling an IoT use-case, this information can potentially also be used for enhancing the discovery and vertical handover procedures in heterogeneous LPWANs. Hence, we propose a location-based mechanism for making discovery and handover decisions in outdoor LPWANs. We do that under the assumption that the location of the MT can be estimated with a certain level of localization errors, while the perfectly accurate location information of the BSs are known to the MT. The mechanism grounds the decisions on the expected SNR between the MT and the BS, which removes the need for continuous probing. If the location information of the MT can be estimated with GPS-like accuracy, we demonstrate that the mechanism can achieve more than 90% correct discovery decisions. We also show that the mechanism is highly accurate in determining if a handover between technologies should be initiated. For an order of magnitude less accurate location information (e.g., for SigFox-based fingerprinting), we show that the mechanism can still make reasonable discovery decisions.

Coordinated tethering for devices with multi-RAT capabilities: An algorithmic solution and performance analysis

One challenging requirement of the Internet of Things (IoTs) is related to the capability of the wireless access network to be able to provide internet connectivity to a very large number of devices, compared to conventional cellular use cases. With the WiFi technology being the spearhead of the wireless local area networks (WLANs), the exploitation of already deployed WLANs has gained ground as a practical and efficient approach towards increasing the spectral efficiency of wireless networks. Based on the coordinated tethering concept, we introduce a purely wireless heterogeneous network deployment, where cellular and WLAN radio resources are optimally coordinated towards the universal maximization of the user’s throughput. The wireless users (smartphones, IoT devices, etc.) are coordinated by the evolved node B (eNB) about their role in the network (access point (AP) or normal user) and the access technology they have to employ. The performance of the new approach has been investigated based on a theoretical framework that has been developed. In this context, closed-form expressions are derived for important statistical characteristics of the system’s output signal-to-interference plus noise ratio (SINR) for the single-user case with multiple interferers. Then, this approach is extended to a multi-user multi-cellular system and a greedy algorithm is proposed for optimizing the system performance. Various numerical and simulation results have presented, which show that the proposed multi-cellular multi-radio access technology (RAT) scheme with coordinated tethering may increase spectral efficiency.