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Technology scaling in advanced CMOS nodes has been very successful in reducing the cost and increasing the operating frequency, however, it has also resulted in reduced transistor intrinsic gain and increased thermal noise coefficient, and most importantly, deteriorated linearity performance. At the same time, advanced wireless communication standards offer ever increasing data rates and pose more

In this work, we analyze the use of a WiFi network deployed in a large-scale technical university. To this extent, we leverage three weeks of WiFi traffic data logs and characterize the spatio-temporal correlation of the traffic at different granularities (each individual access point, groups of access points, entire network). The spatial correlation of traffic across nearby access points is also

Many popular first order algorithms for convex optimization, such as forward-backward splitting, Douglas-Rachford splitting, and the alternating direction method of multipliers (ADMM), can be formulated as averaged iteration of a nonexpansive mapping. In this paper we propose a line search for averaged iteration that preserves the theoretical convergence guarantee, while often accelerating practic

This paper presents a 2-dimension (2-D) Vernier time-to-digital converter (TDC) which uses two 3-stage gated-ring-oscillators (GROs) in the X/Y Vernier branches. The already small Vernier quantization noise (~10.6ps) is improved by the 1st-order noise shaping of the GRO. Moreover, since all delay differences between X phases and Y phases can be used (rather than only the diagonal line of the 1-dim

This paper presents a convex-optimization-based technique to obtain parameters for a PID feedback controller, used to control the infusion rate of the anesthetic drug propofol. The controller design is based on a set of identified patient models, relating propofol infusion to an EEG-based conciousness index. The main contribution lies in the method automatically taking inter-patient variability in

Numerous auto-scaling strategies have been proposed in the past few years for improving various Quality of Service (QoS) indicators of cloud applications, for example, response time and throughput, by adapting the amount of resources assigned to the application to meet the workload demand. However, the evaluation of a proposed auto-scaler is usually achieved through experiments under specific cond

Nonlinear Model Predictive Control (NMPC) is a control strategy based on repeatedly solving an optimal control problem. In this paper we present a new MPC framework for the JModelica.org platform, developed specifically for use in NMPC schemes. The new framework utilizes the fact that the optimal control problem to be solved does not change between solutions, thus decreasing the computation time n

This paper presents a hierarchical approach to feedback-based trajectory generation for improved vehicle autonomy. Hierarchical vehicle-control structures have been used before—for example, in electronic stability control systems, where a low-level control loop tracks high-level references. Here, the control structure includes a nonlinear vehicle model already at the high level to generate optimiz

As automatic sensing and Information and Communication Technology (ICT) get cheaper, building monitoring data is easier to obtain. The abundance of data leads to new opportunities in the context of energy efficiency in buildings. This paper describes ongoing developments and first results of data-driven grey-box modelling for buildings. A Python toolbox is developed based on a Modelica library wit

Dynamic optimization problems involving differential-algebraic equation (DAE) systems are traditionally solved while retaining the semi-explicit or implicit form of the DAE. We instead consider symbolically transforming the DAE into an ordinary differential equation (ODE) before solving the optimization problem using a collocation method. We present a method for achieving this, which handles DAE-c

The solution of generic dynamic optimization problems described by Modelica, and its extension Optimica, code using direct collocation methods is discussed. We start by providing a description of dynamic optimization problems in general and how to solve them by means of direct collocation. Next, an existing implementation of a collocation algorithm in JModelica.org, using CasADi and IPOPT, is pres

Dynamic optimization problems involving parametric sensitivities, such as optimal experimental design, are typically solved using shooting-based methods, while leveraging numerical integrators with sensitivity computation capabilities. In this paper we present how simultaneous discretization can be employed to solve these problems, by augmenting the dynamic optimization problems with forward sensi

Implementation of open source development practices within commercial settings can bring benefits such as improved source code quality, lower maintenance costs, and increased innovation. However, a widespread in-house implementation of the practices has not been observed. The goal of this research is to understand factors which hinder the implementation. For the purpose, development practices of a

Software engineering considers performance evaluation to be one of the key portions of software quality assurance. Unfortunately, there seems to be a lack of standard methodologies for performance evaluation even in the scope of experimental computer science. Inspired by the concept of “instantiation” in object-oriented programming, we distinguish the generic performance evaluation logic from the

The spot pricing scheme has been considered to be resource-efficient for providers and cost-effective for consumers in the Cloud market. Nevertheless, unlike the static and straightforward strategies of trading on-demand and reserved Cloud services, the market-driven mechanism for trading spot service would be complicated for both implementation and understanding. The largely invisible market acti

Massive MIMO has been shown, both in theory and through experiments, to offer very promising properties. These include the possibility to decrease output power by at least an order of magnitude while still achieving large gains in spectral efficiency, as compared to today’s access schemes. To efficiently design communication algorithms and evaluate massive MIMO schemes, channel models that capture

Outdoor positioning systems are commonly available and typically rely on satellite navigation. The same is not true for indoor positioning systems. Severe multipath, non line-of sight to satellites and moving objects are some of the aspects that make the task of indoor positioning tricky. In this paper, we analyse different tracking methods to estimate and track the delay evolution of a radio chan

The position and orientation estimation problem for mobile robots is approached by fusing measurements from inertial sensors, wheel encoders, and a camera. The sensor fusion approach is based on the standard extended Kalman filter, which is modified to handle measurements from the camera with unknown prior delay. A real-time implementation is done on a four-wheeled omni-directional mobile robot, u

In this paper a synchronized dual input-channel multi-mode Software Defined Radio receiver platform that we built originally is presented. The receiver platform compatible with the GSM, WCDMA, and Wi-Fi standards can detect and identify the surrounding base stations and access points. It features wide frequency range, high adaptive sampling rate and especially dual phase coherent receiving channel