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The impedance matching concept is employed in this paper to select the optimum gain of a VSC-HVDC damping controller. The damping controller of the DC link is based on control of active power in proportion to the difference in local frequency at the VSC-HVDC converter stations. To explain impedance matching, the small-disturbance electro-mechanical dynamics of a power system is transformed to an e
Managing variability in control programs often requires code duplication or that all variants are anticipated in advance. In this paper, we present a new approach to obtaining modular functionality reuse across variants. Using the language mechanisms diagram inheritance and connection interception, a feature model and an interactive feature-selection wizard can be automatically derived from the co
This paper presents a structured optimization framework for reducing the computational complexity of LDPC decoders. Subject to specified performance constraints and adaptive to environment conditions, the proposed framework leverages the adjustable performance-complexity tradeoffs of the decoder to deliver satisfying performance with minimum computational complexity. More specifically, two constra
This paper sets up a framework for designing a massive multiple-input multiple-output (MIMO) testbed by investigating hardware and system-level requirements such as processing complexity, duplexing mode and frame structure. Taking these into account, a generic system and processing partitioning is proposed which allows flexible scaling and processing distribution onto a multitude of physically sep
The first measured results for massive multiple input, multiple-output (MIMO) performance in a line-of-sight (LOS) scenario with moderate mobility are presented, with 8 users served in real-time using a 100 antenna base Station (BS) at 3.7 GHz. When such a large number of channels dynamically change, the inherent propagation and processing delay has a critical relationship with the rate of change,
Employing a large number of antennas at the base station, massive MIMO significantly improves spectral efficiency and transmit power efficiency. On the other hand, massive MIMO also introduces unprecedented implementation challenges, especially in terms of processing and storage of large-size channel state information (CSI) matrices. Since on-chip memory is generally very expensive and has limited
Variance-reduced stochastic gradient methods have gained popularity in recent times. Several variants exist with different strategies for storing and sampling gradients, and this work concerns the interactions between these two aspects. We present a general proximal variance-reduced gradient method and analyze it under strong convexity assumptions. Special cases of the algorithm include SAGA, L-SV
In this technical note, we introduce a novel approach to studying consensus of continuous-time nonlinear systems with varying topology based on Hilbert metric. We demonstrate that this metric offers significant flexibility in analyzing consensus properties, while effectively handling nonlinearities and time dependencies. Notably, our approach relaxes key technical assumptions from some standard re
This thesis, comprising four research papers, contributes to the field of systematic and computer-aided analyses and design of first-order methods. The first two papers focus on developing new methodologies, while the remaining two apply these techniques to refine complexity and convergence results, as well as to design new methods. A central theme of the work is the use of Lyapunov-type analyses,
With the increase of devices connected to 5G services, the importance of tuning User Equipment (UE) to their assigned frequency slot becomes increasingly vital. This paper approached this issue by securing the control signals sent through a Serial Peripheral Interface (SPI) in digital beamforming radios. This was done by securing three distinct components: the transmitting end of the channel, the
When patients experience peripheral vestibular or certain central disorders causing dizziness or vertigo, this is sometimes associated with experiencing also disrupted spatial orientation, which may be accentuated by exposure to a distorted visual environment. This study explores the impact of sensorimotor factors and sex on spatial orientation in sitting and standing positions. In the Rod-and-Fra
Lattice-based cryptography is in the process of being standardized. Several proposals to deal with side-channel information using lattice reduction exist. However, it has been shown that algorithms based on Bayesian updating are often more favorable in practice. In this work, we define distribution hints; a type of hint that allows modelling probabilistic information. These hints generalize most p
As a prominent category of side-channel attacks (SCAs), plaintext-checking (PC) oracle-based SCAs offer the advantages of generality and operational simplicity on a targeted device. At TCHES 2023, Rajendran et al. and Tanaka et al. independently proposed the multiple-valued (MV) PC oracle, significantly reducing the required number of queries (a.k.a., traces) in the PC oracle. However, in practice
The Hamming Quasi-Cyclic (HQC) key encapsulation mechanism (KEM), recently selected by NIST for standardization in the Post-Quantum Cryptography (PQC) process, distinguishes itself through its efficiency, robust design based on hard decoding problems in coding theory, and well-characterized decryption failure rates. Despite its selection, practical security concerns arise from implementation threa
We study a network formation game where n players, identified with the nodes of a directed graph to be formed, choose where to wire their outgoing links in order to maximize their PageRank centrality. Specifically, the action of every player i consists in the wiring of a predetermined number di of directed out-links, and her utility is her own PageRank centrality in the network resulting from the
In this paper, we propose a scheme to identify discrete-time, multi-input/multi-output switched-linear systems (MIMO-SLSs) from input-output measurements. The key step is an observer-based transformation to a switched auto-regressive with exogenous input (SARX) model. This transformation converts the state-space (SS) identification problem into a MIMO-SARX identification problem by compressing in
Artificial intelligence (AI) and machine learning (ML) are rapidly permeating nearly every aspect of modern life, frompersonal devices and autonomous systems to industrial automation and environmental monitoring. The growing demandfor intelligence at the network edge is reshaping how computing hardware is conceived and built. Edge AI platforms areexpected to deliver high throughput within tight en
Combinatorial optimization provides a powerful framework for solving complex optimization problems with general-purpose solvers by modelling the problem in an abstract language. Due to breakthroughs in algorithms to solve combinatorial optimization problems in last decades, combinatorial optimization has become a valid approach to solve many real world problems efficiently. Key application areas a
In the era of artificial intelligence of things (AIoT), distributed processing on local devices is growing in popularity. This stems from the need to reduce data transfer to and from central servers, with concerns about privacy and latency encouraging the processing of AI applications on edge devices. However, the computational demands of these applications require an increase in the processing ca
