Establishing secret keys from the commonly-observed randomness of reciprocal wireless propagation channels has recently received considerable attention. In this work we propose improved strategies for channel estimation between MIMO or beamforming systems for secret key generation. The amount of mutual information that can be extracted from the channel matrix estimates is determined by the quality of channel matrix estimates. By allocating increased energy to channel estimation for higher gain beamforming combinations at the expense of low-gain combinations, key establishment performance can be increased. Formalizing the notion of preferential energy allocation to the most efficient excitations is the central theme of this dissertation. For probing with beamforming systems, we formulate a theoretically optimal probing strategy that upper bounds the number of key bits that can be generated from reciprocal channel observations. Specifically, we demonstrate that the eigenvectors of the channel spatial covariance matrix should be used as beamformer weights during channel estimation and we optimize the energy allocated to channel estimation for each beamformer weight under a total energy constraint. The optimal probing strategy is not directly implementable in practice, and therefore we propose two different modifications to the optimal algorithm based on a Kronecker approximation to the spatial covariance matrix. Though these approximations are suboptimal, they each perform well relative to the upper bound. To explore how effective an array is at extracting all of the information available in the propagation environment connecting two nodes, we apply the optimal beamformer probing strategy to a vector current basis function expansion on the array volume. We prove that the resulting key rate is a key rate spatial bound that upper bounds the key rate achievable by any set of antenna arrays probing the channel with the same total energy constraint. For MIMO systems we assume the channel is separable with a Kronecker model, and then for that model we propose an improved probing strategy that iteratively optimizes the energy allocation for each node using concave maximization. The performance of this iterative approach is better than that achieved using the traditional probing strategy in many realistic probing scenarios.

As the need for more bandwidth increases, satellite communication (SatCom) terminals are forced to climb higher in frequency. Higher frequency means greater propagation losses, and so antenna gain and sensitivity have to increase. The higher the gain, the more difficult it is to point the antenna. To make matters even more challenging, consumers are requesting satellite links in harsher environments and on moving vehicle and planes. In order to meet today's challenges and improve on dish feeds, research is ongoing to replace fixed-beam feedhorns with smaller, cheaper, and lighter PCB based antennas and to develop low-cost electronically steered array feeds (ESAF). ESAFs will not only improve the signal link, but they will also aid in pointing the antenna and then tracking the satellite independent of movement. Here is presented some of the first planar antenna dish feeds developed by the Brigham Young University's SatCom Group. Included are the simulation and test procedures to determine if they are viable for SatCom use. The results show that these antennas make significant advancements in efficiencies and prove a path forward to a feedhorn replacement. Several planar designs are presented, each with a unique solution to meet all the requirements for a dish feed. Also presented is the first low-cost ESAFs developed to give commercial SatCom an electronically steerable dish. None of the designed hardware requires a redesign of current modems and receiver boxes. The research looks at keeping costs low by minimizing the required electronics. This further led to researching the limits on how simple the electronics could be. The ESAF doubled the visible area of the dish and successfully acquired and tracked a satellite as the dish moved. The ESAF also demonstrates a path forward to increase the steerable range and improve pointing and tracking.

The complexity of advanced antenna techniques used in the new generation of wireless networks (5G) makes communication between experts and non-technical staff more difficult than ever. As cooperation between network vendors and network operators affects the adoption of the new standard, a need for a new tool has emerged to make technical presentations more engaging and compelling. This thesis presents an exploratory study that aims to examine various design options for an interactive visualization of radiowave propagation to be used by advanced antenna systems experts. Through a Research-oriented Design, functional and non-functional requirements were identified with the help of domain expert. Later, an interactive prototype was designed and developed using a participatory design approach. Qualitative and quantitative data was gathered through usability testing, System Usability Scale (SUS) questionnaires and semi-structured interviews conducted with 12 researchers and engineers at Ericsson AB a multinational telecommunication company. User evaluation proved that such a tool could facilitate communication between technical experts and non-technical staff. The developed prototype was considered intuitive and useful by the majority of study participants as measured by interviews and the SUS survey. Future research is encouraged to include the target audience representatives in order to measure their engagement while using the tool. / Komplexiteten hos avancerade antenntekniker som anvnds i den nya generationen av mobilntverk (5G), gr kommunikationen mellan experter och icke-teknisk personal svrare n ngonsin. Eftersom samarbetet mellan telekommunikationsfretag och ntoperatrer pverkar anpassningen av den nya standarden, har behovet av ett nytt verktyg uppsttt fr att gra tekniska presentationer mer engagerande och vertygande. Avhandlingen presenterar en underskande studie som syftar till att underska olika designalternativ fr en interaktiv visualisering av radiovgsfrkning som anvnds av avancerade antennsystems experter. Genom en forskningsinriktad design identifierades funktionella och icke-funktionella krav med hjlp av en domnexpert. Senare konstruerades och utvecklades en interaktiv prototyp med hjlp av en co-operativ designmetod. Kvalitativa och kvantitativa data samlades in genom anvndbarhetstester, System Usability Scale (SUS) frgeformulr och halvstrukturerade intervjuer med 12 forskare och ingenjrer p Ericsson AB ett multinationellt telekommunikationsfretag. Anvndarutvrdering visade att ett sdant verktyg skulle underltta kommunikationen mellan tekniska experter och icke-teknisk personal. Den utvecklade prototypen ansgs intuitiv och anvndbar av majoriteten av studiedeltagarna, mtt genom intervjuer och SUS-underskningen. Framtida forskning uppmuntrar till att inkludera mlgruppsrepresentanterna fr att mta deras engagemang medan de anvnder verktyget.

Recent advances in the telecommunications industry and the resulting applicationssuch as autonomous vehicles, vehicle surveillance and traffic safetyhas increased the demand for accurate and robust vehicle positioning systems.Existing Global Navigation Satellite System (GNSS) based positioning techniquesface significant performance loss in the tunnels and urban canyons.Recent researches have shown that radio-based positioning techniques are theoreticallypromising to make an accurate navigation system to fill the GNSSgaps. Fifth generation of mobile communication (5G) will utilize wide bandwidthstogether with beamforming enabled by antenna arrays to provide higherdata rates to mobile users. These features make 5G a favorable candidate forhigh accuracy positioning. On the other hand, sensor fusion is commonly employedto develop more robust and accurate navigation systems for vehicles. Inthis work, the range and angle measurements from 5G base stations are fusedwith the acceleration measurements by the means of the extended Kalman filterto generate position estimates for a moving car. The accuracy of this positioningsystem is studied with centimeter wave (cmWave) and millimeter wave(mmWave) 5G cellular networks which are set up by practical parameters. Towardsthat, the positioning system is tested in a simulation-based experimentwhere a car is moving on a highway and the 5G base stations are deployedalongside of it. Based on that, a detailed analysis of the Kalman filter’s rootmean squared error (RMSE) and the 5G’s different parameters and limitingfactors such as the line of sight (LOS) blockage is carried out. Our numericalresults show that vehicles connected to 5G can benefit from this system to enhancethe robustness and accuracy of their navigation system. / De senaste framstegen inom telekommunikationsindustrin och de resulterandeapplikationerna som autonoma fordon, fordonsövervakning och trafiksäkerhethar ökat efterfrågan på exakta fordonspositioneringssystem. ExisterandeGlobal Navigation Satellite System (GNSS) baserade positioneringsteknikerhar en betydande prestandaförlust i tunnlar och urbana kanjoner. Forskninghar visat att radiobaserade positioneringstekniker har mindre distributionskostnaderoch kan vara mer exakta än satellitbaserade navigationssystem.I den femte generation av mobilkommunikation (5G) används tekniker sommillimeterWave (mmWave) och multiple-input multiple-output (MIMO) därradio-terminaler består av stora matrisantenner och arbetar med stora bandbredder.Dessa funktioner gör 5G-system gynnsamma för positionering medhög noggrannhet. Å andra sidan har informationsfusion av Inertial NavigationSystems (INS) och andra positioneringstekniker vanligen använts för attutveckla mer robusta och exakta spårningssystem. I denna studie föreslår viett INS/5G-positioneringssystem för att spåra landfordon baserat på Kalmanfiltret. Vi adresserar systempositioneringsgränserna i termer av 5G nya radio(NR) subsystem och en detaljerad analys av beroendet av rotmedelfelteradkvadratfel (RMSE) för olika systemparametrar som utförs. Systemet testas iett enkelt simuleringsbaserat experiment som består av en rak motorväg medbasstationerna placerade bredvid det. Slutligen visar våra numeriska resultatatt det föreslagna systemet är i stånd att lokalisera ett UE-monterat fordon medsub-meter lägesfel även i närvaro av hård siktlinje blockering.

In digital signal processing in general, and wireless communications in particular, the increased usage of complex signal representations, and spectrally efficient complex modulation schemes such as QPSK and QAM has necessitated the need for efficient and fast-converging complex digital signal processing techniques. In this research, novel complex adaptive digital signal processing techniques are presented, which derive optimal convergence factors or step sizes for adjusting the adaptive system coefficients at each iteration. In addition, the real and imaginary components of the complex signal and complex adaptive filter coefficients are treated as separate entities, and are independently updated. As a result, the developed methods efficiently utilize the degrees of freedom of the adaptive system, thereby exhibiting improved convergence characteristics, even in dynamic environments. In wireless communications, acceptable co-channel, adjacent channel, and image interference rejection is often one of the most critical requirements for a receiver. In this regard, the fixed-point complex Independent Component Analysis (ICA) algorithm, called Complex FastICA, has been previously applied to realize digital blind interference suppression in stationary or slow fading environments. However, under dynamic flat fading channel conditions frequently encountered in practice, the performance of the Complex FastICA is significantly degraded. In this dissertation, novel complex block adaptive ICA algorithms employing optimal convergence factors are presented, which exhibit superior convergence speed and accuracy in time-varying flat fading channels, as compared to the Complex FastICA algorithm. The proposed algorithms are called Complex IA-ICA, Complex OBA-ICA, and Complex CBC-ICA. For adaptive filtering applications, the Complex Least Mean Square algorithm (Complex LMS) has been widely used in both block and sequential form, due to its computational simplicity. However, the main drawback of the Complex LMS algorithm is its slow convergence and dependence on the choice of the convergence factor. In this research, novel block and sequential based algorithms for complex adaptive digital filtering are presented, which overcome the inherent limitations of the existing Complex LMS. The block adaptive algorithms are called Complex OBA-LMS and Complex OBAI-LMS, and their sequential versions are named Complex HA-LMS and Complex IA-LMS, respectively. The performance of the developed techniques is tested in various adaptive filtering applications, such as channel estimation, and adaptive beamforming. The combination of Orthogonal Frequency Division Multiplexing (OFDM) and the Multiple-Input-Multiple-Output (MIMO) technique is being increasingly employed for broadband wireless systems operating in frequency selective channels. However, MIMO-OFDM systems are extremely sensitive to Intercarrier Interference (ICI), caused by Carrier Frequency Offset (CFO) between local oscillators in the transmitter and the receiver. This results in crosstalk between the various OFDM subcarriers resulting in severe deterioration in performance. In order to mitigate this problem, the previously proposed Complex OBA-ICA algorithm is employed to recover user signals in the presence of ICI and channel induced mixing. The effectiveness of the Complex OBA-ICA method in performing ICI mitigation and signal separation is tested for various values of CFO, rate of channel variation, and Signal to Noise Ratio (SNR).

The growing adoption of millimeter wave (mmWave) turns efficient beamforming and beam management procedures into key enablers for 5th Generation (5G) and Beyond 5G (B5G) mobile networks. Recent research has sought to optimize beam management in modern Radio Access Network (RAN) architectures, where open, virtualized, disaggregated and multi-vendor environments are considered, and management platforms allow the use of Artificial Intelligence (AI) and Machine Learning (ML)-based solutions. Moreover, beam management represents some fundamental use cases defined by Open RAN Alliance (O-RAN). This work analyses beam management strategies in Open RAN and proposes solutions for codebook-based mmWave systems inspired by two use cases from O-RAN: the Grid of Beams (GoB) Optimization and the AI/ML-assisted Beam Selection. For the GoB Optimization use case, a scenario subject to constraints on the use of the full GoB due to overhead during beam selection is considered. An Advantage Actor Critic (A2C) learning-based framework is proposed to optimize the GoB, as well as the transmission power in a mmWave network. The proposed technique improves Energy Efficiency (EE) and ensures fair coverage is maintained. The simulations show that A2C-based joint optimization of GoB and transmission power is more effective than using Equally Spaced Beams (ESB) and fixed power, or the optimization of GoB and transmission power disjointly. Compared to the ESB and fixed transmission power strategy, the proposed approach achieves more than twice the average EE in the scenarios under test, and it is closer to the maximum theoretical EE. In the case of the AI/ML-assisted Beam Selection use case, the overhead during beam selection is addressed by a multi-modal sensing-aided ML-based method. When using sensing information sources external to the RAN in a multi-vendor disaggregated environment, such methods must account for privacy and data ownership issues. A Distributed Machine Learning (DML) strategy based on Split Learning (SL) is proposed to this end. The solution can cope with deployment challenges in novel RAN architectures and is applied to single and multi-level beam selection decisions, where the latter considers hierarchical codebook structures. With the proposed approach, accuracy levels above 90% can be achieved, while overhead decreases by 85% or more. SL achieves performance comparable to the centralized learning-based strategies, with the added value of accounting for privacy and data ownership issues.

Radio frequency interference (RFI) is undesired and commonplace. Using a subspace projection method to spatially remove the interference from a phased array system gives results of a 30 dB interference null rejection (INR). Unmanned systems have been developed to observe underwater activity and communicate their observations to passing aircraft. These systems are currently limited by their use of a single transmitter. The uplink can be improved by using a dual-antenna beam steering approach to maximize the signal-to-noise ratio (SNR) the aircraft receives. This approach demonstrates an increase in SNR of 3 dB when compared to a single transmitter.

Yes / Recent studies and research have centred on new solutions in different elements and stages to the increasing energy and data rate demands for the fifth generation and beyond (B5G). Based on a new-efficient digital beamforming approach for 5G wireless communication networks, this work offers a compact-size circular patch antenna operating at 60 GHz and covering a 4 GHz spectrum bandwidth. Massive Multiple Input Multiple Output (M–MIMO) and beamforming technology build and simulate an active multiple beams antenna system. Thirty-two linear and sixty-four planar antenna array configurations are modelled and constructed to work as base stations for 5G mobile communication networks. Furthermore, a new beamforming approach called Projection Noise Correlation Matrix (PNCM) is presented to compute and optimise the fed weights of the array elements. The key idea of the PNCM method is to sample a portion of the measured noise correlation matrix uniformly in order to provide the best representation of the entire measured matrix. The sampled data will then be utilised to build a projected matrix using the pseudoinverse approach in order to determine the best fit solution for a system and prevent any potential singularities caused by the matrix inversion process. The PNCM is a low-complexity method since it avoids eigenvalue decomposition and computing the entire matrix inversion procedure and does not require including signal and interference correlation matrices in the weight optimisation process. The suggested approach is compared to three standard beamforming methods based on an intensive Monte Carlo simulation to demonstrate its advantage. The experiment results reveal that the proposed method delivers the best Signal to Interference Ratio (SIR) augmentation among the compared beamformers

京都大学 / 0048 / 新制・課程博士 / 博士(情報学) / 甲第21218号 / 情博第671号 / 新制||情||116(附属図書館) / 京都大学大学院情報学研究科通信情報システム専攻 / (主査)教授 佐藤 亨, 教授 山本 衛, 教授 松田 哲也 / 学位規則第4条第1項該当 / Doctor of Informatics / Kyoto University / DFAM

Global Navigation Satellite Systems (GNSS) are vital tools for accurate navigation and timing for both civil and military use. Due to the low power of the GNSS signals, these systems are sensitive to interference attacks. For wideband GNSS jamming, adaptive antenna arrays are commonly used to suppress interference.  This thesis focuses on how distortions induced by adaptive antenna arrays can affect the performance of a GNSS receiver and how prone different beamforming algorithms are to suffer from such distortions. To investigate this, simulations in software have been performed for static scenarios with two different beamforming algorithms and four different antenna arrays. The results show that the method for interference suppression that uses constraints in direction and frequency achieves a higher signal-to-interference-plus-noise ratio, more stable acquisition over the hemisphere, and less fluctuating code delay error than the method that only minimizes the power of the output signal.