Carrier Frequency Offset Estimation for OFDM Systems using Repetitive Patterns

This paper deals with Carrier Frequency Offset (CFO) estimation for OFDM systems using repetitive patterns in the training symbol. A theoretical comparison based on Cramer Rao Bounds (CRB) for two kinds of CFO estimation methods has been presented in this paper. Through the comparison, it is shown that the performance of CFO estimation can be improved by exploiting the repetition property and the exact training symbol rather than exploiting the repetition property only. The selection of Q (number of repetition patterns) is discussed for both situations as well. Moreover, for exploiting the repetition and the exact training symbol, a new numerical procedure for the Maximum-Likelihood (ML) estimation is designed in this paper to save computational complexity. Analysis and numerical result are also given, demonstrating the conclusions in this paper

Evolutionary L∞ identification and model reduction for robust control

An evolutionary approach for modern robust control oriented system identification and model reduction in the frequency domain is proposed. The technique provides both an optimized nominal model and a 'worst-case' additive or multiplicative uncertainty bounding function which is compatible with robust control design methodologies. In addition, the evolutionary approach is applicable to both continuous- and discrete-time systems without the need for linear parametrization or a confined problem domain for deterministic convex optimization. The proposed method is validated against a laboratory multiple-input multiple-output (MIMO) test rig and benchmark problems, which show a higher fitting accuracy and provides a tighter L�¢���� error bound than existing methods in the literature do

Memory effects in device-dependent and device-independent cryptography

In device-independent cryptography, it is known that reuse of devices across multiple protocol instances can introduce a vulnerability against memory attacks. This is an introductory note to highlight that even if we restrict ourselves to device-dependent QKD and only consider a single protocol instance, memory effects across rounds are enough to cause substantial difficulties in applying many existing non-IID proof techniques, such as de Finetti reductions and complementarity-based arguments (e.g. analysis of phase errors). We present a quick discussion of these issues, including some tailored scenarios where protocols admitting security proofs via those techniques become insecure when memory effects are allowed, and we highlight connections to recently discussed attacks on DIQKD protocols that have public announcements based on the measurement outcomes. This discussion indicates the challenges that would need to be addressed in order to apply those techniques in the presence of memory effects (for either the device-dependent or device-independent case), even for a single protocol instance

Robustness of implemented device-independent protocols against constrained leakage

Device-independent (DI) protocols have experienced significant progress in recent years, with a series of demonstrations of DI randomness generation or expansion, as well as DI quantum key distribution. However, existing security proofs for those demonstrations rely on a typical assumption in DI cryptography, that the devices do not leak any unwanted information to each other or to an adversary. This assumption may be difficult to perfectly enforce in practice. While there exist other DI security proofs that account for a constrained amount of such leakage, the techniques used are somewhat unsuited for analyzing the recent DI protocol demonstrations. In this work, we address this issue by studying a constrained leakage model suited for this purpose, which should also be relevant for future similar experiments. Our proof structure is compatible with recent proof techniques for flexibly analyzing a wide range of DI protocol implementations. With our approach, we compute some estimates of the effects of leakage on the keyrates of those protocols, hence providing a clearer understanding of the amount of leakage that can be allowed while still obtaining positive keyrates.Comment: Changelog: more detailed analysis of conditioning on acceptance events, implemented tighter version of fidelity constraints and replaced SDP formulation with more stable approach, updated figures accordingl