Density analysis of LTE-LAA networks coexisting with WiFi sharing multiple unlicensed channels

With data traffic explosion, operating Long-Term Evolution (LTE) in the 5 GHz unlicensed band, which has already been used by WiFi networks, has been proposed. To harmoniously coexist with the incumbent WiFi networks, LTE-Licensed Assisted Access (LAA) has been proposed recently, advocating cellular networks to access the unlicensed band by employing listen-before-talk mechanism. However, the performance of LAA has not been analysed under multiple accessible unlicensed channels (UCs). In this work, we analyse the user throughput and spatial spectral efficiency (SSE) of the multi-UC coexisting LTE-LAA and WiFi networks versus the network density based on the Matern hard core process. The throughput and SSE are obtained as functions of the downlink successful transmission probability (STP), of which analytical expressions are derived and validated by Monte Carlo simulations. The results show that an optimal LTE access point (LAP) density exists to maximise the LTE-LAA user equipment (LUE) throughput, and our derived closed-form STP lower bound of LUE can be used to obtain a sufficiently accurate prediction of the optimal LAP density. Moreover, the SSE does not change much under relatively low LAP densities, and when the LAP density is larger than 1, 585 LAPs per km 2 , the SSE approaches the asymptotic SSE as the LAP density approaches infinity

Location-Enabled IoT (LE-IoT): A Survey of Positioning Techniques, Error Sources, and Mitigation

The Internet of Things (IoT) has started to empower the future of many industrial and mass-market applications. Localization techniques are becoming key to add location context to IoT data without human perception and intervention. Meanwhile, the newly-emerged Low-Power Wide-Area Network (LPWAN) technologies have advantages such as long-range, low power consumption, low cost, massive connections, and the capability for communication in both indoor and outdoor areas. These features make LPWAN signals strong candidates for mass-market localization applications. However, there are various error sources that have limited localization performance by using such IoT signals. This paper reviews the IoT localization system through the following sequence: IoT localization system review -- localization data sources -- localization algorithms -- localization error sources and mitigation -- localization performance evaluation. Compared to the related surveys, this paper has a more comprehensive and state-of-the-art review on IoT localization methods, an original review on IoT localization error sources and mitigation, an original review on IoT localization performance evaluation, and a more comprehensive review of IoT localization applications, opportunities, and challenges. Thus, this survey provides comprehensive guidance for peers who are interested in enabling localization ability in the existing IoT systems, using IoT systems for localization, or integrating IoT signals with the existing localization sensors

A comprehensive survey of V2X cybersecurity mechanisms and future research paths

Recent advancements in vehicle-to-everything (V2X) communication have notably improved existing transport systems by enabling increased connectivity and driving autonomy levels. The remarkable benefits of V2X connectivity come inadvertently with challenges which involve security vulnerabilities and breaches. Addressing security concerns is essential for seamless and safe operation of mission-critical V2X use cases. This paper surveys current literature on V2X security and provides a systematic and comprehensive review of the most relevant security enhancements to date. An in-depth classification of V2X attacks is first performed according to key security and privacy requirements. Our methodology resumes with a taxonomy of security mechanisms based on their proactive/reactive defensive approach, which helps identify strengths and limitations of state-of-the-art countermeasures for V2X attacks. In addition, this paper delves into the potential of emerging security approaches leveraging artificial intelligence tools to meet security objectives. Promising data-driven solutions tailored to tackle security, privacy and trust issues are thoroughly discussed along with new threat vectors introduced inevitably by these enablers. The lessons learned from the detailed review of existing works are also compiled and highlighted. We conclude this survey with a structured synthesis of open challenges and future research directions to foster contributions in this prominent field.This work is supported by the H2020-INSPIRE-5Gplus project (under Grant agreement No. 871808), the ”Ministerio de Asuntos Económicos y Transformacion Digital” and the European Union-NextGenerationEU in the frameworks of the ”Plan de Recuperación, Transformación y Resiliencia” and of the ”Mecanismo de Recuperación y Resiliencia” under references TSI-063000-2021-39/40/41, and the CHIST-ERA-17-BDSI-003 FIREMAN project funded by the Spanish National Foundation (Grant PCI2019-103780).Peer ReviewedPostprint (published version

Interference Management Techniques for Cellular Wireless Communication Systems

The growing demand for higher capacity wireless networks can be met by increasing the frequency bandwidth, spectral efficiency, and base station density. Flexible spectrum access, multiantenna, and multicarrier techniques are key enablers in satisfying the demand. In addition, automation of tasks related to network planning, optimization, interference management, and maintenance are needed in order to ensure cost-efficiency. Effective, dynamic, and automated interference management tailored for bursty and local data traffic plays a central role in the task. Adjacent channel interference (ACI) management is an enabler for flexible spectrum use and uncoordinated network deployments. In this thesis the impact of ACI in local area time division duplex (TDD) cellular systems is demonstrated. A method is proposed where the transmitters optimize their transmitted spectral shape on-line, such that constraints on ACI induced by power amplifier non-linearity are met. The proposed method increases the fairness among spectrum sharing transceivers when ACI is a limiting factor. A novel interference-aware scheduling technique is proposed and analyzed. The technique manages co-channel interference (CCI) in a decentralized fashion, relying on beacon messages sent by data receivers. It is demonstrated that the proposed technique is an enabler for fair spectrum sharing among operators, independent adaptation of uplink/downlink switching points in TDD networks, and it provides overall more fair and spectrally efficient wireless access. Especially, the technique is able to improve the cell-edge throughput tremendously. New services are emerging that generate local traffic among the users in addition to the data traffic between the users and the network. Such device-to-device (D2D) traffic is effectively served by direct transmissions. The thesis demonstrates the possibilities for allowing such direct D2D transmissions on a shared band together with the cellular communication. It is shown that interference management is needed in order to facilitate reliable and efficient shared band operation. For this purpose, three methods are proposed that provide interference aware power control, interference aware multiuser and multiband resource allocation, and interference avoiding spatial precoding. It is shown that enabling direct transmission itself provides most of the gains in system capacity, while the interference management schemes are more important in promoting fairness and reliability.Langattomien tietoliikenneverkkojen käyttö kasvaa erittäin nopeasti mobiilien internet-palvelujen ja älykkäiden päätelaitteiden suosion myötä. Järjestelmien tiedonsiirtokapasiteettiä voidaan lisätä kasvattamalla kaistanleveyttä, spektritehokkuutta ja tukiasemaverkon tiheyttä. Kehityksen mahdollistaa mm. joustava taajuuksien käyttö ja moniantenni- ja monikantoaaltotekniikat. Lisäksi radioverkkojen suunnitteluun, optimointiin, ylläpitoon ja interferenssinhallintaan liittyvien tehtävien automatisoinnilla voidaan pienentää verkko-operaattoreiden kustannuksia. Tässä hetkellisen ja paikallisen tietoliikenteen tehokas, dynaaminen ja automatisoitu interferenssinhallinta on keskeisessä asemassa. Viereisen kanavan interferenssin hallinta mahdollistaa osaltaan joustavan spektrinkäytön ja koordinoimattoman verkkojen asennuksen. Väitöskirjassa on analysoitu viereisen kanavan interferenssin vaikutusta aikajakoiseen dupleksilähetykseen perustuvien paikallisten radioverkkojen toimintaan. Lisäksi väitöskirjassa on kehitetty menetelmä, jolla voidaan hallita interferenssiä reaaliaikaisesti. Menetelmä maksimoi lähetetyn signaalin spektritehokkuuden siten, että tehovahvistimen epälineaarisuuden aiheuttama viereisen kanavan interferenssi on rajoitettu. Väitöskirjassa on kehitetty ja analysoitu uudenlainen interferenssitietoinen lähetysten ajoitustekniikka. Tekniikka hallitsee reaaliaikaisesti ja hajautetusti saman kanavan interferenssiä vastaanottimien lähettämien majakkasignaalien avulla. Esitetyt simulaatiot osoittavat, että tämä mahdollistaa operaattoreiden välisen taajuuskaistojen jaon, ja alas- ja yloslinkkien aikajaon joustavan säädön. Tämän lisäksi on mahdollista saavuttaa korkeampi yleinen spektritehokkuus. Erityisesti tiedonsiirtonopeus solujen reunoille kasvaa esitetyn tekniikan avulla huomattavasti. Uudenlaiset tietoliikennepalvelut lisäävät laitteidenvälisen paikallisen tietoliikenteen määrää. Spektrinkäytön kannalta tämä liikenne on tehokkainta lähettää suoraan laitteesta toiseen. Väitöskirjassa on tutkittu joustavaa spektrinkäyttöä suorien laitteidenvälisten lähetysten ja soluverkon välillä. Interferenssin hallinta takaa luotettavan ja tehokkaan spektrin yhteiskäytön. Tätä varten väitöskirjassa on kehitetty kolme menetelmää, jotka perustuvat tehonsäätöön, lähetysten ajoitukseen ja moniantennilähetykseen

FAIR SHARING of CHANNEL RESOURCES in the COEXISTENCE of HETEROGENEOUS WIRELESS NETWORKS

Increasing spectrum resources in cellular networks are always needed to carry the exponential data traffic growth in wireless cellular networks. Limited spectrum resources in the licensed band have necessitated Long-Term Evolution (LTE) to explore available unlicensed spectrum where an incumbent WiFi system already exists. With the deployment of Licensed Assisted Access (LAA) that utilizes Listen Before Talk (LBT) for channel access in the unlicensed spectrum along with an incumbent WiFi, the coexistence of LAA and WiFi with acceptable fairness is a major challenge. In this work, we address the issues of licensed assisted access coexisting with incumbent WiFi in an unlicensed spectrum and provide solutions to dynamically tune system parameters of LAA stations to achieve maximum total throughput from the overall system taking into account fair allocation of throughput and airtime across different networks and stations. One major system parameter we study is the contention window size for back-off. Using the method of coupled Markov Chain, we show how an inherent trade-off between throughput and airtime fairness can be managed by adjusting the CW size of LAA. For single-channel, we show how coexistence with WiFi can be managed better with LAA-Cat3 than LAA-Cat4 when total throughput and fairness are to be taken into account. For multi-carrier sensing, we establish better coexistence by optimizing contention window sizes of each LAA station separately using an assignment technique based on a genetic algorithm. We extend our work into dual-carrier aggregation where some stations have the ability to combine two independent channels into a single aggregated channel to achieve higher performance. We show that in such a dual-carrier aggregation scenario, the distribution of stations (partition) over an individual and aggregated channel, and the system parameters (contention window size and load intensity) could be optimized to ensure fair allocation of resources without affecting the secondary channel too much

Cooperative Radio Communications for Green Smart Environments

The demand for mobile connectivity is continuously increasing, and by 2020 Mobile and Wireless Communications will serve not only very dense populations of mobile phones and nomadic computers, but also the expected multiplicity of devices and sensors located in machines, vehicles, health systems and city infrastructures. Future Mobile Networks are then faced with many new scenarios and use cases, which will load the networks with different data traffic patterns, in new or shared spectrum bands, creating new specific requirements. This book addresses both the techniques to model, analyse and optimise the radio links and transmission systems in such scenarios, together with the most advanced radio access, resource management and mobile networking technologies. This text summarises the work performed by more than 500 researchers from more than 120 institutions in Europe, America and Asia, from both academia and industries, within the framework of the COST IC1004 Action on "Cooperative Radio Communications for Green and Smart Environments". The book will have appeal to graduates and researchers in the Radio Communications area, and also to engineers working in the Wireless industry. Topics discussed in this book include: • Radio waves propagation phenomena in diverse urban, indoor, vehicular and body environments• Measurements, characterization, and modelling of radio channels beyond 4G networks• Key issues in Vehicle (V2X) communication• Wireless Body Area Networks, including specific Radio Channel Models for WBANs• Energy efficiency and resource management enhancements in Radio Access Networks• Definitions and models for the virtualised and cloud RAN architectures• Advances on feasible indoor localization and tracking techniques• Recent findings and innovations in antenna systems for communications• Physical Layer Network Coding for next generation wireless systems• Methods and techniques for MIMO Over the Air (OTA) testin

Cooperative Radio Communications for Green Smart Environments

The demand for mobile connectivity is continuously increasing, and by 2020 Mobile and Wireless Communications will serve not only very dense populations of mobile phones and nomadic computers, but also the expected multiplicity of devices and sensors located in machines, vehicles, health systems and city infrastructures. Future Mobile Networks are then faced with many new scenarios and use cases, which will load the networks with different data traffic patterns, in new or shared spectrum bands, creating new specific requirements. This book addresses both the techniques to model, analyse and optimise the radio links and transmission systems in such scenarios, together with the most advanced radio access, resource management and mobile networking technologies. This text summarises the work performed by more than 500 researchers from more than 120 institutions in Europe, America and Asia, from both academia and industries, within the framework of the COST IC1004 Action on "Cooperative Radio Communications for Green and Smart Environments". The book will have appeal to graduates and researchers in the Radio Communications area, and also to engineers working in the Wireless industry. Topics discussed in this book include: • Radio waves propagation phenomena in diverse urban, indoor, vehicular and body environments• Measurements, characterization, and modelling of radio channels beyond 4G networks• Key issues in Vehicle (V2X) communication• Wireless Body Area Networks, including specific Radio Channel Models for WBANs• Energy efficiency and resource management enhancements in Radio Access Networks• Definitions and models for the virtualised and cloud RAN architectures• Advances on feasible indoor localization and tracking techniques• Recent findings and innovations in antenna systems for communications• Physical Layer Network Coding for next generation wireless systems• Methods and techniques for MIMO Over the Air (OTA) testin

Traffic Learning: A Deep Learning Approach for Obtaining Accurate Statistical Information of the Channel Traffic in Spectrum Sharing Systems

In recent works, the statistical information of the channel traffic has been increasingly exploited to make effective decisions in spectrum sharing systems. However, these statistics cannot be obtained perfectly under (realistic) Imperfect Spectrum Sensing (ISS). Therefore, in this work we study comprehensively the approaches in the literature that correct the estimation of the channel traffic statistics under ISS, namely the closed-form expression approach and the algorithmic reconstruction approach. Then, we introduce a novel approach named Traffic Learning as a Deep Learning (DL) approach for providing accurate estimation of the channel traffic statistics under ISS. For this novel approach, deep neural networks using Multilayer Perceptron (MLP) models are found for the estimation of several statistical metrics. In addition, we show that utilising effective features from spectrum sensing observations can lead to a considerable improvement in statistics estimation for each, mean, variance, minimum and distribution of the channel traffic under ISS, outperforming the existing approaches in the literature, which are based on either closed-form expressions or reconstruction algorithms