Multi-Array 5G V2V Relative Positioning: Performance Bounds

We study the performance bounds of vehicle-to-vehicle (V2V) relative positioning for vehicles with multiple antenna arrays. The Cram\'{e}r-Rao bound for the estimation of the relative position and the orientation of the Tx vehicle is derived, when angle of arrival (AOA) measurements with or without time-difference of arrival (TDOA) measurements are used. In addition, geometrically intuitive expressions for the corresponding Fisher information are provided. The derived bounds are numerically evaluated for different carrier frequencies, bandwidths and array configurations under different V2V scenarios, i.e. overtaking and platooning. The significance of the AOA and TDOA measurements for position estimation is investigated. The achievable positioning accuracy is then compared with the present requirements of the 3rd Generation Partnership Project (3GPP) 5G New Radio (NR) vehicle-to-everything (V2X) standardization

Convergent Communication, Sensing and Localization in 6G Systems: An Overview of Technologies, Opportunities and Challenges

Herein, we focus on convergent 6G communication, localization and sensing systems by identifying key technology enablers, discussing their underlying challenges, implementation issues, and recommending potential solutions. Moreover, we discuss exciting new opportunities for integrated localization and sensing applications, which will disrupt traditional design principles and revolutionize the way we live, interact with our environment, and do business. Regarding potential enabling technologies, 6G will continue to develop towards even higher frequency ranges, wider bandwidths, and massive antenna arrays. In turn, this will enable sensing solutions with very fine range, Doppler, and angular resolutions, as well as localization to cm-level degree of accuracy. Besides, new materials, device types, and reconfigurable surfaces will allow network operators to reshape and control the electromagnetic response of the environment. At the same time, machine learning and artificial intelligence will leverage the unprecedented availability of data and computing resources to tackle the biggest and hardest problems in wireless communication systems. As a result, 6G will be truly intelligent wireless systems that will provide not only ubiquitous communication but also empower high accuracy localization and high-resolution sensing services. They will become the catalyst for this revolution by bringing about a unique new set of features and service capabilities, where localization and sensing will coexist with communication, continuously sharing the available resources in time, frequency, and space. This work concludes by highlighting foundational research challenges, as well as implications and opportunities related to privacy, security, and trust

Indoor Positioning Trends in 5G-Advanced: Challenges and Solution towards Centimeter-level Accuracy

After robust connectivity, precise positioning is evolving into an innovative component of 5G service offerings for industrial use-cases and verticals with challenging indoor radio environments. In this direction, the 3GPP Rel-16 standard has been a tipping point in specifying critical innovations, followed by enhancements in Rel-17+. In this article, we follow this path to elaborate on the 5G positioning framework, measurements, and methods before shifting the focus to carrier-phase (CP) measurements as a complementary measure for time- and angular-based positioning methods toward achieving centimeter-level accuracy. As this path is not without challenges, we discuss these and outline potential solutions. As an example of solutions, we study how phase-continuous reference signaling can counter noisy phase measurements using realistic simulations in an indoor factory (InF) scenario.Comment: 5 figures, 1 table, under review for possible publication in IEEE Communications Magazin

Convergent communication, sensing and localization in 6g systems: An overview of technologies, opportunities and challenges

Herein, we focus on convergent 6G communication, localization and sensing systems by identifying key technology enablers, discussing their underlying challenges, implementation issues, and recommending potential solutions. Moreover, we discuss exciting new opportunities for integrated localization and sensing applications, which will disrupt traditional design principles and revolutionize the way we live, interact with our environment, and do business. Regarding potential enabling technologies, 6G will continue to develop towards even higher frequency ranges, wider bandwidths, and massive antenna arrays. In turn, this will enable sensing solutions with very fine range, Doppler, and angular resolutions, as well as localization to cm-level degree of accuracy. Besides, new materials, device types, and reconfigurable surfaces will allow network operators to reshape and control the electromagnetic response of the environment. At the same time, machine learning and artificial intelligence will leverage the unprecedented availability of data and computing resources to tackle the biggest and hardest problems in wireless communication systems. As a result, 6G will be truly intelligent wireless systems that will provide not only ubiquitous communication but also empower high accuracy localization and high-resolution sensing services. They will become the catalyst for this revolution by bringing about a unique new set of features and service capabilities, where localization and sensing will coexist with communication, continuously sharing the available resources in time, frequency, and space. This work concludes by highlighting foundational research challenges, as well as implications and opportunities related to privacy, security, and trust

Técnicas de gestão de feixe de onda para sistemas Massive MIMO nas redes 5G NR

The use of Millimeter wave (mmWave) spectrum frequencies is seen as a key enabler technology for the future wireless communication systems to overcome the bandwidth shortage of the sub 6GHz microwave spectrum band, enabling high speed data transmissions in the 5G/6G systems. Nevertheless, mmWave propagation characteristics are associated to significant free-path losses and many more attenuations that become even more harsher as the frequency increases, rendering the communication challenging at this frequencies. To overcome these distinct disadvantages, multiple antenna arrays are employed to allow beamforming techniques for the transmission of narrower concentrated beams in more precise directions and less interference levels between them, consequently improving the link budget. Thus, to constantly assure that the communication with each device is done using the beam pair that allows the best possible connectivity, a set of Beam Management control procedures is necessary to assure an efficient beamformed connection establishment and its continuous maintenance between the device and the network. This dissertation will address the description of the Initial Beam Establishment (IBE) BM procedure, focusing the selection of the most suitable transmit-receive beam pair available after completed beam sweeping techniques to measure the different power levels of the received signal. The main goal is to design a new 3GPP-standard compliant beam pair selection algorithm based on SSS angle estimation (BSAE), that makes use of multiple Synchronization Signal Blocks (SSBs) to maximize the Reference Signal Received Power (RSRP) value at the receiver, through the selected beam pair. This optimization is done using the Secondary Synchronization Signals (SSSs) present in each SSB to perform channel estimation in the digital domain (comprising the effects of the analog processing). Afterwards, the combination of those estimations were used to perform the equivalent channel propagation matrix estimation without the analog processing effects. Finally, through the channel propagation matrix, the angle that maximizes the RSRP was determined to compute the most suitable beam through the aggregated response vector. The obtained results show that the proposed algorithm achieves better performance levels compared to a conventional beam pair selection algorithm. Furthermore, a comparison with an optimal case is also done, i.e., the situation where the channel is known, and the optimal beam pair angle can be determined. Therefore, the similar performance results compared to the optimal case indicates that the proposed algorithm is interesting for practical 5G mmWave mMIMO implementations, according to 3GPP-compliant standards.O uso de frequências na banda das ondas milimétricas é visto como uma tecnologia chave para os futuros sistemas de comunicação móveis, tendo em vista a ultrapassar o problema da escassez de banda a sub-6 GHz, e por permitir as elevadas taxas de dados requeridas para sistemas 5G/6G. Contudo, a propagação deste tipo de ondas está associado a perdas acentuadas em espaço livre e várias atenuações que se tornam cada vez mais significativas com o aumento do valor da frequência, impondo obstáculos à comunicação. Para ultrapassar estas adversidades, agregados constituídos por múltiplos elementos de antena são implementados por forma a permitir técnicas de formação de feixe e possibilitar a transmissão de feixes mais estreitos e altamente direcionais, diminuindo os níveis de interferência e melhorando consequentemente o link budget. Deste modo, para assegurar constantemente que a comunicação efetuada em cada dispositivo ocorre utilizando o conjunto de feixes que proporciona o melhor nível de conectividade, é então necessário um conjunto de procedimentos de controlo de gestão de feixe, assegurando um estabelecimento eficiente da comunicação e a sua contínua manutenção entre um dispositivo e a rede. Esta dissertação descreve o procedimento de gestão de feixe conhecido como estabelecimento inicial de feixe, focando o processo de seleção do melhor par de feixe de transmissão-receção disponível após o uso de técnicas de varrimento de feixe por fim a efetuar medições dos diferentes níveis de potência do sinal recebido. O principal objetivo passa pela conceção de um novo algoritmo de estabelecimento de par de feixes baseado em estimações de ângulo (BSAE), que explora o uso de múltiplos SSBs definidos pelo 3GPP, por forma a maximizar o RSRP no recetor, através do feixe selecionado. Esta otimização é feita usando os sinais de sincronização secundários (SSSs) presentes em cada SSB para efetuar uma estimação de canal no domínio digital (que contém o efeito do processamento analógico). Depois, combinando essas estimações, foi feita uma estimação da matriz do canal de propagação, sem o efeito desse processamento analógico. Finalmente, através da matriz do canal de propagação, foi determinado o ângulo que maximiza o RSRP, e calculado o feixe através do vetor de resposta do agregado. Os resultados obtidos demonstram que o algoritmo proposto atinge melhor desempenho quando comparado com o algoritmo convencional de seleção de par de feixes. Foi feita ainda uma comparação com o caso ótimo, isto é, com o caso em que se conhece completamente o canal e se obtém um ângulo ótimo. Os resultados obtidos pelo algoritmo proposto foram muito próximos do caso ótimo, pelo que é bastante interessante para sistemas práticos 5G mmWave mMIMO, que estejam de acordo com o padrão 3GPP.Mestrado em Engenharia Eletrónica e Telecomunicaçõe

Direct communication radio Iinterface for new radio multicasting and cooperative positioning

Cotutela: Universidad de defensa UNIVERSITA’ MEDITERRANEA DI REGGIO CALABRIARecently, the popularity of Millimeter Wave (mmWave) wireless networks has increased due to their capability to cope with the escalation of mobile data demands caused by the unprecedented proliferation of smart devices in the fifth-generation (5G). Extremely high frequency or mmWave band is a fundamental pillar in the provision of the expected gigabit data rates. Hence, according to both academic and industrial communities, mmWave technology, e.g., 5G New Radio (NR) and WiGig (60 GHz), is considered as one of the main components of 5G and beyond networks. Particularly, the 3rd Generation Partnership Project (3GPP) provides for the use of licensed mmWave sub-bands for the 5G mmWave cellular networks, whereas IEEE actively explores the unlicensed band at 60 GHz for the next-generation wireless local area networks. In this regard, mmWave has been envisaged as a new technology layout for real-time heavy-traffic and wearable applications. This very work is devoted to solving the problem of mmWave band communication system while enhancing its advantages through utilizing the direct communication radio interface for NR multicasting, cooperative positioning, and mission-critical applications. The main contributions presented in this work include: (i) a set of mathematical frameworks and simulation tools to characterize multicast traffic delivery in mmWave directional systems; (ii) sidelink relaying concept exploitation to deal with the channel condition deterioration of dynamic multicast systems and to ensure mission-critical and ultra-reliable low-latency communications; (iii) cooperative positioning techniques analysis for enhancing cellular positioning accuracy for 5G+ emerging applications that require not only improved communication characteristics but also precise localization. Our study indicates the need for additional mechanisms/research that can be utilized: (i) to further improve multicasting performance in 5G/6G systems; (ii) to investigate sideline aspects, including, but not limited to, standardization perspective and the next relay selection strategies; and (iii) to design cooperative positioning systems based on Device-to-Device (D2D) technology

ML-Enabled Outdoor User Positioning in 5G NR Systems via Uplink SRS Channel Estimates

Cellular user positioning is a promising service provided by Fifth Generation New Radio (5G NR) networks. Besides, Machine Learning (ML) techniques are foreseen to become an integrated part of 5G NR systems improving radio performance and reducing complexity. In this paper, we investigate ML techniques for positioning using 5G NR fingerprints consisting of uplink channel estimates from the physical layer channel. We show that it is possible to use Sounding Reference Signals (SRS) channel fingerprints to provide sufficient data to infer user position. Furthermore, we show that small fully-connected moderately Deep Neural Networks, even when applied to very sparse SRS data, can achieve successful outdoor user positioning with meter-level accuracy in a commercial 5G environment.Comment: 6 pages, 8 figures, Accepted to be published in IEEE International Conference on Communications 2023, Rome, Ital

D2D-based Cooperative Positioning Paradigm for Future Wireless Systems: A Survey

Emerging communication network applications require a location accuracy of less than 1m in more than 95% of the service area. For this purpose, 5G New Radio (NR) technology is designed to facilitate high-accuracy continuous localization. In 5G systems, the existence of high-density small cells and the possibility of the device-to-device (D2D) communication between mobile terminals paves the way for cooperative positioning applications. From the standardization perspective, D2D technology is already under consideration (5G NR Release 16) for ultra-dense networks enabling cooperative positioning and is expected to achieve the ubiquitous positioning of below one-meter accuracy, thereby fulfilling the 5G requirements. In this survey, the strengths and weaknesses of D2D as an enabling technology for cooperative cellular positioning are analyzed (including two D2D approaches to perform cooperative positioning); lessons learned and open issues are highlighted to serve as guidelines for future research