Machine learning enabled Wi-Fi saturation sensing for fair coexistence in unlicensed spectrum

In the past few years, machine learning (ML) techniques have been extensively applied to provide efficient solutions to complex wireless network problems. As such, Convolutional Neural Network (CNN) and Q-learning based ML techniques are most popular to achieve harmonized coexistence of Wi-Fi with other co-located technologies such as LTE. In the existing coexistence schemes, a co-located technology selects its transmission time based on the level of Wi-Fi traffic generated in its collision domain which is determined by either sniffing the Wi-Fi packets or using a central coordinator that can communicate with the co-located networks to exchange their status and requirements through a collaboration protocol. However, such approaches for sensing traffic status increase cost, complexity, traffic overhead, and reaction time of the coexistence schemes. As a solution to this problem, this work applies a ML-based approach that is capable to determine the saturation status of a Wi-Fi network based on real-time and over-the-air collection of medium occupation statistics about the Wi-Fi frames without the need for decoding. In particular, inter-frame spacing statistics of Wi-Fi frames are used to develop a CNN model that can determine Wi-Fi network saturation. The results demonstrate that the proposed ML-based approach can accurately classify whether a Wi-Fi network is saturated or not

Measurement and Optimization of LTE Performance

4G Long Term Evolution (LTE) mobile system is the fourth generation communication system adopted worldwide to provide high-speed data connections and high-quality voice calls. Given the recent deployment by mobile service providers, unlike GSM and UMTS, LTE can be still considered to be in its early stages and therefore many topics still raise great interest among the international scientific research community: network performance assessment, network optimization, selective scheduling, interference management and coexistence with other communication systems in the unlicensed band, methods to evaluate human exposure to electromagnetic radiation are, as a matter of fact, still open issues. In this work techniques adopted to increase LTE radio performances are investigated. One of the most wide-spread solutions proposed by the standard is to implement MIMO techniques and within a few years, to overcome the scarcity of spectrum, LTE network operators will offload data traffic by accessing the unlicensed 5 GHz frequency. Our Research deals with an evaluation of 3GPP standard in a real test best scenario to evaluate network behavior and performance

Towards More Efficient 5G Networks via Dynamic Traffic Scheduling

Department of Electrical EngineeringThe 5G communications adopt various advanced technologies such as mobile edge computing and unlicensed band operations, to meet the goal of 5G services such as enhanced Mobile Broadband (eMBB) and Ultra Reliable Low Latency Communications (URLLC). Specifically, by placing the cloud resources at the edge of the radio access network, so-called mobile edge cloud, mobile devices can be served with lower latency compared to traditional remote-cloud based services. In addition, by utilizing unlicensed spectrum, 5G can mitigate the scarce spectrum resources problem thus leading to realize higher throughput services. To enhance user-experienced service quality, however, aforementioned approaches should be more fine-tuned by considering various network performance metrics altogether. For instance, the mechanisms for mobile edge computing, e.g., computation offloading to the edge cloud, should not be optimized in a specific metric's perspective like latency, since actual user satisfaction comes from multi-domain factors including latency, throughput, monetary cost, etc. Moreover, blindly combining unlicensed spectrum resources with licensed ones does not always guarantee the performance enhancement, since it is crucial for unlicensed band operations to achieve peaceful but efficient coexistence with other competing technologies (e.g., Wi-Fi). This dissertation proposes a focused resource management framework for more efficient 5G network operations as follows. First, Quality-of-Experience is adopted to quantify user satisfaction in mobile edge computing, and the optimal transmission scheduling algorithm is derived to maximize user QoE in computation offloading scenarios. Next, regarding unlicensed band operations, two efficient mechanisms are introduced to improve the coexistence performance between LTE-LAA and Wi-Fi networks. In particular, we develop a dynamic energy-detection thresholding algorithm for LTE-LAA so that LTE-LAA devices can detect Wi-Fi frames in a lightweight way. In addition, we propose AI-based network configuration for an LTE-LAA network with which an LTE-LAA operator can fine-tune its coexistence parameters (e.g., CAA threshold) to better protect coexisting Wi-Fi while achieving enhanced performance than the legacy LTE-LAA in the standards. Via extensive evaluations using computer simulations and a USRP-based testbed, we have verified that the proposed framework can enhance the efficiency of 5G.clos

Using hypergraph theory to model coexistence management and coordinated spectrum allocation for heterogeneous wireless networks operating in shared spectrum

Electromagnetic waves in the Radio Frequency (RF) spectrum are used to convey wireless transmissions from one radio antenna to another. Spectrum utilisation factor, which refers to how readily a given spectrum can be reused across space and time while maintaining an acceptable level of transmission errors, is used to measure how efficiently a unit of frequency spectrum can be allocated to a specified number of users. The demand for wireless applications is increasing exponentially, hence there is a need for efficient management of the RF spectrum. However, spectrum usage studies have shown that the spectrum is under-utilised in space and time. A regulatory shift from static spectrum assignment to DSA is one way of addressing this. Licence exemption policy has also been advanced in Dynamic Spectrum Access (DSA) systems to spur wireless innovation and universal access to the internet. Furthermore, there is a shift from homogeneous to heterogeneous radio access and usage of the same spectrum band. These three shifts from traditional spectrum management have led to the challenge of coexistence among heterogeneous wireless networks which access the spectrum using DSA techniques. Cognitive radios have the ability for spectrum agility based on spectrum conditions. However, in the presence of multiple heterogeneous networks and without spectrum coordination, there is a challenge related to switching between available channels to minimise interference and maximise spectrum allocation. This thesis therefore focuses on the design of a framework for coexistence management and spectrum coordination, with the objective of maximising spectrum utilisation across geographical space and across time. The amount of geographical coverage in which a frequency can be used is optimised through frequency reuse while ensuring that harmful interference is minimised. The time during which spectrum is occupied is increased through time-sharing of the same spectrum by two or more networks, while ensuring that spectrum is shared by networks that can coexist in the same spectrum and that the total channel load is not excessive to prevent spectrum starvation. Conventionally, a graph is used to model relationships between entities such as interference relationships among networks. However, the concept of an edge in a graph is not sufficient to model relationships that involve more than two entities, such as more than two networks that are able to share the same channel in the time domain, because an edge can only connect two entities. On the other hand, a hypergraph is a generalisation of an undirected graph in which a hyperedge can connect more than two entities. Therefore, this thesis investigates the use of hypergraph theory to model the RF environment and the spectrum allocation scheme. The hypergraph model was applied to an algorithm for spectrum sharing among 100 heterogeneous wireless networks, whose geo-locations were randomly and independently generated in a 50 km by 50 km area. Simulation results for spectrum utilisation performance have shown that the hypergraph-based model allocated channels, on average, to 8% more networks than the graph-based model. The results also show that, for the same RF environment, the hypergraph model requires up to 36% fewer channels to achieve, on average, 100% operational networks, than the graph model. The rate of growth of the running time of the hypergraph-based algorithm with respect to the input size is equal to the square of the input size, like the graph-based algorithm. Thus, the model achieved better performance at no additional time complexity.Electromagnetic waves in the Radio Frequency (RF) spectrum are used to convey wireless transmissions from one radio antenna to another. Spectrum utilisation factor, which refers to how readily a given spectrum can be reused across space and time while maintaining an acceptable level of transmission errors, is used to measure how efficiently a unit of frequency spectrum can be allocated to a specified number of users. The demand for wireless applications is increasing exponentially, hence there is a need for efficient management of the RF spectrum. However, spectrum usage studies have shown that the spectrum is under-utilised in space and time. A regulatory shift from static spectrum assignment to DSA is one way of addressing this. Licence exemption policy has also been advanced in Dynamic Spectrum Access (DSA) systems to spur wireless innovation and universal access to the internet. Furthermore, there is a shift from homogeneous to heterogeneous radio access and usage of the same spectrum band. These three shifts from traditional spectrum management have led to the challenge of coexistence among heterogeneous wireless networks which access the spectrum using DSA techniques. Cognitive radios have the ability for spectrum agility based on spectrum conditions. However, in the presence of multiple heterogeneous networks and without spectrum coordination, there is a challenge related to switching between available channels to minimise interference and maximise spectrum allocation. This thesis therefore focuses on the design of a framework for coexistence management and spectrum coordination, with the objective of maximising spectrum utilisation across geographical space and across time. The amount of geographical coverage in which a frequency can be used is optimised through frequency reuse while ensuring that harmful interference is minimised. The time during which spectrum is occupied is increased through time-sharing of the same spectrum by two or more networks, while ensuring that spectrum is shared by networks that can coexist in the same spectrum and that the total channel load is not excessive to prevent spectrum starvation. Conventionally, a graph is used to model relationships between entities such as interference relationships among networks. However, the concept of an edge in a graph is not sufficient to model relationships that involve more than two entities, such as more than two networks that are able to share the same channel in the time domain, because an edge can only connect two entities. On the other hand, a hypergraph is a generalisation of an undirected graph in which a hyperedge can connect more than two entities. Therefore, this thesis investigates the use of hypergraph theory to model the RF environment and the spectrum allocation scheme. The hypergraph model was applied to an algorithm for spectrum sharing among 100 heterogeneous wireless networks, whose geo-locations were randomly and independently generated in a 50 km by 50 km area. Simulation results for spectrum utilisation performance have shown that the hypergraph-based model allocated channels, on average, to 8% more networks than the graph-based model. The results also show that, for the same RF environment, the hypergraph model requires up to 36% fewer channels to achieve, on average, 100% operational networks, than the graph model. The rate of growth of the running time of the hypergraph-based algorithm with respect to the input size is equal to the square of the input size, like the graph-based algorithm. Thus, the model achieved better performance at no additional time complexity

View on 5G Architecture: Version 2.0

The 5G Architecture Working Group as part of the 5GPPP Initiative is looking at capturing novel trends and key technological enablers for the realization of the 5G architecture. It also targets at presenting in a harmonized way the architectural concepts developed in various projects and initiatives (not limited to 5GPPP projects only) so as to provide a consolidated view on the technical directions for the architecture design in the 5G era. The first version of the white paper was released in July 2016, which captured novel trends and key technological enablers for the realization of the 5G architecture vision along with harmonized architectural concepts from 5GPPP Phase 1 projects and initiatives. Capitalizing on the architectural vision and framework set by the first version of the white paper, this Version 2.0 of the white paper presents the latest findings and analyses with a particular focus on the concept evaluations, and accordingly it presents the consolidated overall architecture design

Channel parameter tuning in a hybrid Wi-Fi-Dynamic Spectrum Access Wireless Mesh Network

This work addresses Channel Assignment in a multi-radio multi-channel (MRMC) Wireless Mesh Network (WMN) using both Wi-Fi and Dynamic Spectrum Access (DSA) spectrum bands and standards. This scenario poses new challenges because nodes are spread out geographically so may have differing allowed channels and experience different levels of external interference in different channels. A solution must meet two conflicting requirements simultaneously: 1) avoid or minimise interference within the network and from external interference sources, and 2) maintain connectivity within the network. These two requirements must be met while staying within the link constraints and the radio interface constraints, such as only assigning as many channels to a node as it has radios. This work's original contribution to the field is a unified framework for channel optimisation and assignment in a WMN that uses both DSA and traditional Wi-Fi channels for interconnectivity. This contribution is realised by providing and analysing the performance of near-optimal Channel Assignment (CA) solutions using metaheuristic algorithms for the MRMC WMNs using DSA bands. We have created a simulation framework for evaluating the algorithms. The performance of Simulated Annealing, Genetic Algorithm, Differential Evolution, and Particle Swarm Optimisation algorithms have been analysed and compared for the CA optimisation problem. We introduce a novel algorithm, used alongside the metaheuristic optimisation algorithms, to generate feasible candidate CA solutions. Unlike previous studies, this sensing and CA work takes into account the requirement to use a Geolocation Spectrum Database (GLSD) to get the allowed channels, in addition to using spectrum sensing to identify and estimate the cumulative severity of both internal and external interference sources. External interference may be caused by other secondary users (SUs) in the vicinity or by primary transmitters of the DSA band whose emissions leak into adjacent channels, next-toadjacent, or even into further channels. We use signal-to-interference-plus-noise ratio (SINR) as the optimisation objective. This incorporates any possible source or type of interference and makes our method agnostic to the protocol or technology of the interfering devices while ensuring that the received signal level is high enough for connectivity to be maintained on as many links as possible. To support our assertion that SINR is a reasonable criterion on which to base the optimisation, we have carried out extensive outdoor measurements in both line-of-sight and wooded conditions in the television white space (TVWS) DSA band and the 5 GHz Wi-Fi band. These measurements show that SINR is useful as a performance measure, especially when the interference experienced on a link is high. Our statistical analysis shows that SINR effectively differentiates the performance of different channels and that SINR is well correlated with throughput and is thus a good predictor of end-user experience, despite varying conditions. We also identify and analyse the idle times created by Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) contention-based Medium Access Control (MAC) operations and propose the use of these idle times for spectrum sensing to measure the SINR on possible channels. This means we can perform spectrum sensing with zero spectrum sensing delay experienced by the end user. Unlike previous work, this spectrum sensing is transparent and can be performed without causing any disruption to the normal data transmission of the network. We conduct Markov chain analysis to find the expected length of time of a sensing window. We also derive an efficient minimum variance unbiased estimator of the interference plus noise and show how the SINR can be found using this estimate. Our estimation is more granular, accurate, and appropriate to the problem of Secondary User (SU)-SU coexistence than the binary hypothesis testing methods that are most common in the literature. Furthermore, we construct confidence intervals based on the probability density function derived for the observations. This leads to finding and showing the relationships between the number of sampling windows and sampling time, the interference power, and the achievable confidence interval width. While our results coincide with (and thus are confirmed by) some key previous recommendations, ours are more precise, granular, and accurate and allow for application to a wider range of operating conditions. Finally, we present alterations to the IEEE 802.11k protocol to enable the reporting of spectrum sensing results to the fusion or gateway node and algorithms for distributing the Channel Assignment once computed. We analyse the convergence rate of the proposed procedures and find that high network availability can be maintained despite the temporary loss of connectivity caused by the channel switching procedure. This dissertation consolidates the different activities required to improve the channel parameter settings of a multi-radio multi-channel DSA-WMN. The work facilitates the extension of Internet connectivity to the unconnected or unreliably connected in rural or peri-urban areas in a more cost-effective way, enabling more meaningful and affordable access technologies. It also empowers smaller players to construct better community networks for sharing local content. This technology can have knock-on effects of improved socio-economic conditions for the communities that use it

Systematic Approaches for Telemedicine and Data Coordination for COVID-19 in Baja California, Mexico

Conference proceedings info: ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologies Raleigh, HI, United States, March 24-26, 2023 Pages 529-542We provide a model for systematic implementation of telemedicine within a large evaluation center for COVID-19 in the area of Baja California, Mexico. Our model is based on human-centric design factors and cross disciplinary collaborations for scalable data-driven enablement of smartphone, cellular, and video Teleconsul-tation technologies to link hospitals, clinics, and emergency medical services for point-of-care assessments of COVID testing, and for subsequent treatment and quar-antine decisions. A multidisciplinary team was rapidly created, in cooperation with different institutions, including: the Autonomous University of Baja California, the Ministry of Health, the Command, Communication and Computer Control Center of the Ministry of the State of Baja California (C4), Colleges of Medicine, and the College of Psychologists. Our objective is to provide information to the public and to evaluate COVID-19 in real time and to track, regional, municipal, and state-wide data in real time that informs supply chains and resource allocation with the anticipation of a surge in COVID-19 cases. RESUMEN Proporcionamos un modelo para la implementación sistemática de la telemedicina dentro de un gran centro de evaluación de COVID-19 en el área de Baja California, México. Nuestro modelo se basa en factores de diseño centrados en el ser humano y colaboraciones interdisciplinarias para la habilitación escalable basada en datos de tecnologías de teleconsulta de teléfonos inteligentes, celulares y video para vincular hospitales, clínicas y servicios médicos de emergencia para evaluaciones de COVID en el punto de atención. pruebas, y para el tratamiento posterior y decisiones de cuarentena. Rápidamente se creó un equipo multidisciplinario, en cooperación con diferentes instituciones, entre ellas: la Universidad Autónoma de Baja California, la Secretaría de Salud, el Centro de Comando, Comunicaciones y Control Informático. de la Secretaría del Estado de Baja California (C4), Facultades de Medicina y Colegio de Psicólogos. Nuestro objetivo es proporcionar información al público y evaluar COVID-19 en tiempo real y rastrear datos regionales, municipales y estatales en tiempo real que informan las cadenas de suministro y la asignación de recursos con la anticipación de un aumento de COVID-19. 19 casos.ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologieshttps://doi.org/10.1007/978-981-99-3236-