Partition Information and its Transmission over Boolean Multi-Access Channels

In this paper, we propose a novel partition reservation system to study the partition information and its transmission over a noise-free Boolean multi-access channel. The objective of transmission is not message restoration, but to partition active users into distinct groups so that they can, subsequently, transmit their messages without collision. We first calculate (by mutual information) the amount of information needed for the partitioning without channel effects, and then propose two different coding schemes to obtain achievable transmission rates over the channel. The first one is the brute force method, where the codebook design is based on centralized source coding; the second method uses random coding where the codebook is generated randomly and optimal Bayesian decoding is employed to reconstruct the partition. Both methods shed light on the internal structure of the partition problem. A novel hypergraph formulation is proposed for the random coding scheme, which intuitively describes the information in terms of a strong coloring of a hypergraph induced by a sequence of channel operations and interactions between active users. An extended Fibonacci structure is found for a simple, but non-trivial, case with two active users. A comparison between these methods and group testing is conducted to demonstrate the uniqueness of our problem.Comment: Submitted to IEEE Transactions on Information Theory, major revisio

Adaptive Beam-Frequency Allocation Algorithm with Position Uncertainty for Millimeter-Wave MIMO Systems

Envisioned for fifth generation (5G) systems, millimeter-wave (mmWave) communications are under very active research worldwide. Although pencil beams with accurate beamtracking may boost the throughput of mmWave systems, this poses great challenges in the design of radio resource allocation for highly mobile users. In this paper, we propose a joint adaptive beam-frequency allocation algorithm that takes into account the position uncertainty inherent to high mobility and/or unstable users as, e.g., Unmanned Aerial Vehicles (UAV), for whom this is a major problem. Our proposed method provides an optimized beamwidth selection under quality of service (QoS) requirements for maximizing system proportional fairness, under user position uncertainty. The rationale of our scheme is to adapt the beamwidth such that the best trade-off among system performance (narrower beam) and robustness to uncertainty (wider beam) is achieved. Simulation results show that the proposed method largely enhances the system performance compared to reference algorithms, by an appropriate adaptation of the mmWave beamwidths, even under severe uncertainties and imperfect channel state information (CSIs).Comment: 5 pages, 6 figures, 1 table, 1 algorith

Simultaneous Active and Passive Information Transfer for RIS-Aided MIMO Systems: Iterative Decoding and Evolution Analysis

This paper investigates the potential of reconfigurable intelligent surface (RIS) for passive information transfer in a RIS-aided multiple-input multiple-output (MIMO) system. We propose a novel simultaneous active and passive information transfer (SAPIT) scheme. In SAPIT, the transmitter (Tx) and the RIS deliver information simultaneously, where the RIS information is carried through the RIS phase shifts embedded in reflected signals. We introduce the coded modulation technique at the Tx and the RIS. The main challenge of the SAPIT scheme is to simultaneously detect the Tx signals and the RIS phase coefficients at the receiver. To address this challenge, we introduce appropriate auxiliary variables to convert the original signal model into two linear models with respect to the Tx signals and one entry-by-entry bilinear model with respect to the RIS phase coefficients. With this auxiliary signal model, we develop a message-passing-based receiver algorithm. Furthermore, we analyze the fundamental performance limit of the proposed SAPIT-MIMO transceiver. Notably, we establish the state evolution to predict the receiver performance in a large-size system. We further analyze the achievable rates of the Tx and the RIS, which provides insight into the code design for sum-rate maximization. Numerical results validate our analysis and show that the SAPIT scheme outperforms the passive beamforming counterpart in achievable sum rate of the Tx and the RIS.Comment: 15 pages, 7 figure

Design and Validation of a Distributed Observer-Based Estimation Scheme for Power Grids

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record.This paper presents a novel estimation scheme for power grids based on distributed observers. Assuming only the generator voltage phase angles are measured and the electrical load active power demands are specified, we design an observer for each bus of the power grid, exploiting only knowledge of local information about the power system. In particular, we propose a super-twisting-like sliding mode observer to estimate the frequency deviation for each generator bus, and a so-called algebraic observer to estimate the load voltage phase angle for each load bus based on distributed iterative algorithms. The observer-based estimation scheme is validated by considering the IEEE 39 bus SimPowerSystems model

Analysis of an attenuator artifact in an experimental attack by Gunn-Allison-Abbott against the Kirchhoff-law-Johnson-noise (KLJN) secure key exchange system

A recent paper by Gunn-Allison-Abbott (GAA) [L.J. Gunn et al., Scientific Reports 4 (2014) 6461] argued that the Kirchhoff-law-Johnson-noise (KLJN) secure key exchange system could experience a severe information leak. Here we refute their results and demonstrate that GAA's arguments ensue from a serious design flaw in their system. Specifically, an attenuator broke the single Kirchhoff-loop into two coupled loops, which is an incorrect operation since the single loop is essential for the security in the KLJN system, and hence GAA's asserted information leak is trivial. Another consequence is that a fully defended KLJN system would not be able to function due to its built-in current-comparison defense against active (invasive) attacks. In this paper we crack GAA's scheme via an elementary current comparison attack which yields negligible error probability for Eve even without averaging over the correlation time of the noise.Comment: Accepted for publication in Fluctuation and Noise Letters, on November 3, 201

Fault Tolerant Control with Additive Compensation for Faults in an Automotive Damper

International audienceAbstract--A novel Fault-Tolerant Controller is proposed for an automotive suspension system based on a Quarter of Vehicle (QoV) model. The design is divided in a robust Linear Parameter-Varying controller used to isolate vibrations from external disturbances and in a compensation mechanism used to accommodate actuator faults. The compensation mechanism is based on a robust fault detection and estimation scheme that reconstructs a fault on the semi-active damper; this information is used to reduce the failure effect into the vertical dynamics to achieve good control performances. Validations have been made over a QoV model in CarSimTM. Results show the effectiveness of the faulttolerant semi-active damper versus an uncontrolled damper; the improvement is 50.4% in comfort and 42.4% in road holding, by avoiding biases in the damper deflection

Multifidelity Learning for the Design of Re-Entry Capsules

The design and optimization of re-entry capsules presents many challenges associated with the variety of physical domains involved and their couplings. Examples are capsules for the transfer of astronauts to the international space station and for future Lunar and Martian exploration missions. For these vehicles, aerodynamics and thermodynamics phenomena are strongly coupled and relate to structural dynamics and vibrations, chemical non equilibrium phenomena that characterize the atmosphere, specifi c re-entry trajectory, and geometrical shape of the body. The design and optimization of these capsules would largely benefi t from accurate analyses of the re-entry flow field through high- fidelity representations of the aerothermodynamic phenomena. However, those high- fidelity representations are usually in the form of computer models for the numerical solutions of PDEs (e.g. Navier-Stokes equations, heat equations, etc.) which require signifi cant computational effort and are commonly excluded from preliminary multidisciplinary design and trade-off analysis. This presentation discusses the use of multi fidelity methods to integrate high- fidelity simulations in order to obtain efficient aerothermodynamic models of the re-entering vehicles. Multi fidelity approaches allow to accelerate the exploration and evaluation of design alternatives through the use of different representations of a physical system/process, each characterized by a different level of fidelity and associated computational expense. By efficiently combining less-expensive information from low- fidelity models with a principled selection of few expensive simulations, multi fidelity methods allow to incorporate high-fidelity costly information for design analysis and optimization. Speci fically, we propose a multifi delity active learning strategy to accelerate the multidisciplinary design optimization (MDO) of a re-entry vehicle. The active learning scheme is formulated to be both data driven and domain-aware, and is implemented for the design of an Orion-like re-entry capsule. The MDO problem comprises trajectory analysis, propulsion system model, aerothermodynamic models, and structural model of the thermal protection systems (TPS). The design objectives are the minimization of the propellant mass burned during the entry maneuver, the structural mass of the TPS and the temperature reached by the TPS structure. The results show that our multifidelity scheme allows to efficiently improve the design solution through a limited number of high- fidelity evaluations

Massive Wireless Energy Transfer without Channel State Information via Imperfect Intelligent Reflecting Surfaces

Intelligent Reflecting Surface (IRS) utilizes low-cost, passive reflecting elements to enhance the passive beam gain, improve Wireless Energy Transfer (WET) efficiency, and enable its deployment for numerous Internet of Things (IoT) devices. However, the increasing number of IRS elements presents considerable channel estimation challenges. This is due to the lack of active Radio Frequency (RF) chains in an IRS, while pilot overhead becomes intolerable. To address this issue, we propose a Channel State Information (CSI)-free scheme that maximizes received energy in a specific direction and covers the entire space through phased beam rotation. Furthermore, we take into account the impact of an imperfect IRS and meticulously design the active precoder and IRS reflecting phase shift to mitigate its effects. Our proposed technique does not alter the existing IRS hardware architecture, allowing for easy implementation in the current system, and enabling access or removal of any Energy Receivers (ERs) without additional cost. Numerical results illustrate the efficacy of our CSI-free scheme in facilitating large-scale IRS without compromising performance due to excessive pilot overhead. Furthermore, our scheme outperforms the CSI-based counterpart in scenarios involving large-scale ERs, making it a promising solution in the era of IoT