A Robust Maximum Likelihood Scheme for PSS Detection and Integer Frequency Offset Recovery in LTE Systems

Before establishing a communication link in a cellular network, the user terminal must activate a synchronization procedure called initial cell search in order to acquire specific information about the serving base station. To accomplish this task, the primary synchronization signal (PSS) and secondary synchronization signal (SSS) are periodically transmitted in the downlink of a long term evolution (LTE) network. Since SSS detection can be performed only after successful identification of the primary signal, in this work, we present a novel algorithm for joint PSS detection, sector index identification, and integer frequency offset (IFO) recovery in an LTE system. The proposed scheme relies on the maximum likelihood (ML) estimation criterion and exploits a suitable reduced-rank representation of the channel frequency response, which proves robust against multipath distortions and residual timing errors. We show that a number of PSS detection methods that were originally introduced through heuristic reasoning can be derived from our ML framework by simply selecting an appropriate model for the channel gains over the PSS subcarriers. Numerical simulations indicate that the proposed scheme can be effectively applied in the presence of severe multipath propagation, where existing alternatives provide unsatisfactory performance

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

PROCESS FOR BREAKING DOWN THE LTE SIGNAL TO EXTRACT KEY INFORMATION

The increasingly important role of Long Term Evolution (LTE) has increased security concerns among the service providers and end users and made security of the network even more indispensable. The main thrust of this thesis is to investigate if the LTE signal can be broken down in a methodical way to obtain information that would otherwise be private; e.g., the Global Positioning System (GPS) location of the user equipment/base station or identity (ID) of the user. The study made use of signal simulators and software to analyze the LTE signal to develop a method to remove noise, breakdown the LTE signal and extract desired information. From the simulation results, it was possible to extract key information in the downlink like the Downlink Control Information (DCI), Cell-Radio Network Temporary Identifier (C-RNTI) and physical Cell Identity (Cell-ID). This information can be modified to cause service disruptions in the network within a reasonable amount of time and with modest computing resources.Defence Science and Technology Agency, SingaporeApproved for public release; distribution is unlimited

Development of Multiple Protocols in Novel Simulation Environment

abstract: When one considers the current state of wireless communications, it becomes clear that it is both absolutely amazing and something of a mess. Present communications standards are the result of local optimizations over time that led to a confusing set of suboptimal and fragile wireless standards. Starting from a clean sheet of paper, Bliss Laboratory for Information, Signals, and Systems (BLISS) is considering a fluid set of communications standards co-optimized with flexible but power-efficient computational implementations that will enable the next revolution of wireless communications. The main aim is to enable much higher data rates and much lower data rates with corresponding lower power consumption as the needs of the users vary. The thesis mainly looks at the different sections of the work done, to prime the development of the protocol development engine. It discusses channel modeling, and system integration of receiver and channel noise. It also proposes a Carrier-Sense Multiple Access (CSMA) Media Access Control (MAC) layer protocol implementation for (Wireless Fidelity) Wi-Fi protocol. This work also talks about the Graphical User Interface (GUI), which is a part of Protocol Development Kit (PDK) - a combination of the Protocol Recommendation Engine (PRE) and simulation package to aid the development of protocols. It also sheds light on the Automatic Dependent Surveillance - Broadcast (ADS-B) radio protocol, that will eventually replace radar as Air Traffic Control's (ATC) primary tool for separating aircraft. All the algorithms used in this thesis, to define radio operation were in principle defined by mathematical descriptions; however, to test and implement these algorithms they had to be converted to a computer language. There were multiple phases of this conversion. In the first phase, the implementation of these algorithms was done in Matrix Laboratory (MATLAB). To aid this development, basic radio finite state machines and radio algorithmic tools were provided.Dissertation/ThesisMasters Thesis Electrical Engineering 201

Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks

Soaring capacity and coverage demands dictate that future cellular networks need to soon migrate towards ultra-dense networks. However, network densification comes with a host of challenges that include compromised energy efficiency, complex interference management, cumbersome mobility management, burdensome signaling overheads and higher backhaul costs. Interestingly, most of the problems, that beleaguer network densification, stem from legacy networks' one common feature i.e., tight coupling between the control and data planes regardless of their degree of heterogeneity and cell density. Consequently, in wake of 5G, control and data planes separation architecture (SARC) has recently been conceived as a promising paradigm that has potential to address most of aforementioned challenges. In this article, we review various proposals that have been presented in literature so far to enable SARC. More specifically, we analyze how and to what degree various SARC proposals address the four main challenges in network densification namely: energy efficiency, system level capacity maximization, interference management and mobility management. We then focus on two salient features of future cellular networks that have not yet been adapted in legacy networks at wide scale and thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and device-to-device (D2D) communications. After providing necessary background on CoMP and D2D, we analyze how SARC can particularly act as a major enabler for CoMP and D2D in context of 5G. This article thus serves as both a tutorial as well as an up to date survey on SARC, CoMP and D2D. Most importantly, the article provides an extensive outlook of challenges and opportunities that lie at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201

Towards large-scale and collaborative spectrum monitoring systems using IoT devices

Mención Internacional en el título de doctorThe Electromagnetic (EM) spectrum is well regulated by frequency assignment authorities, national regulatory agencies and the International Communication Union (ITU). Nowadays more and more devices such as mobile phones and Internet-of-Things (IoT) sensors make use of wireless communication. Additionally we need a more efficient use and a better understanding of the EM space to allocate and manage efficiently all communications. Governments and telecommunication operators perform spectrum measurements using expensive and bulky equipments scheduling very specific and limited spectrum campaigns. However, this approach does not scale as it can not allow to widely scan and analyze the spectrum 24/7 in real time due to the high cost of the large deployment. A pervasive deployment of spectrum sensors is required to solve this problem, allowing to monitor and analyze the EM radio waves in real time, across all possible frequencies, and physical locations. This thesis presents ElectroSense, a crowdsourcing and collaborative system that enables large scale deployments using Internet-of-Things (IoT) spectrum sensors to collect EM spectrum data which is analyzed in a big data infrastructure. The ElectroSense platform seeks a more efficient, safe and reliable real-time monitoring of the EM space by improving the accessibility and the democratization of spectrum data for the scientific community, stakeholders and the general public. In this work, we first present the ElectroSense architecture, and the design challenges that must be faced to attract a large community of users and all potential stakeholders. It is envisioned that a large number of sensors deployed in ElectroSense will be at affordable cost, supported by more powerful spectrum sensors when possible. Although low-cost Radio Frequency (RF) sensors have an acceptable performance for measuring the EM spectrum, they present several drawbacks (e.g. frequency range, Analog-to-Digital Converter (ADC), maximum sampling rate, etc.) that can negatively affect the quality of collected spectrum data as well as the applications of interest for the community. In order to counteract the above-mentioned limitations, we propose to exploit the fact that a dense network of spectrum sensors will be in range of the same transmitter(s). We envision to exploit this idea to enable smart collaborative algorithms among IoT RF sensors. In this thesis we identify the main research challenges to enable smart collaborative algorithms among low-cost RF sensors. We explore different crowdsourcing and collaborative scenarios where low-cost spectrum sensors work together in a distributed manner. First, we propose a fast and precise frequency offset estimation method for lowcost spectrum receivers that makes use of Long Term Evolution (LTE) signals broadcasted by the base stations. Second, we propose a novel, fast and precise Time-of-Arrival (ToA) estimation method for aircraft signals using low-cost IoT spectrum sensors that can achieve sub-nanosecond precision. Third, we propose a collaborative time division approach among sensors for sensing the spectrum in order to reduce the network uplink bandwidth for each spectrum sensor. By last, we present a methodology to enable the signal reconstruction in the backend. By multiplexing in frequency a certain number of non-coherent low-cost spectrum sensors, we are able to cover a signal bandwidth that would not otherwise be possible using a single receiver. At the time of writing we are the first looking at the problem of collaborative signal reconstruction and decoding using In-phase & Quadrature (I/Q) data received from low-cost RF sensors. Our results reported in this thesis and obtained from the experiments made in real scenarios, suggest that it is feasible to enable collaborative spectrum monitoring strategies and signal decoding using commodity hardware as RF sensing sensors.Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Bozidar Radunovic.- Secretario: Paolo Casari.- Vocal: Fco. Javier Escribano Aparici