Self-Assembled Chiral Photonic Crystals From Colloidal Helices Racemate

Chiral crystals consisting of micro-helices have many optical properties while presently available fabrication processes limit their large-scale applications in photonic devices. Here, by using a simplified simulation method, we investigate a bottom-up self-assembly route to build up helical crystals from the smectic monolayer of colloidal helices racemate. With increasing the density, the system undergoes an entropy-driven co-crystallization by forming crystals of various symmetries with different helical shapes. In particular, we identify two crystals of helices arranged in the binary honeycomb and square lattices, which are essentially composed by two sets of opposite-handed chiral crystal. Photonic calculations show that these chiral structures can have large complete photonic bandgaps. In addition, in the self-assembled chiral square crystal, we also find dual polarization bandgaps that selectively forbid the propagation of circularly polarized lights of a specific handedness along the helical axis direction. The self-assembly process in our proposed system is robust, suggesting possibilities of using chiral colloids to assemble photonic metamaterials.Comment: Accepted in ACS Nan

Effective Capacity Maximization With Statistical Delay and Effective Energy Efficiency Requirements

This paper presents the three-fold energy, rate and delay tradeoff in mobile multimedia fading channels. In particular, we propose a rate-efficient power allocation strategy for delay-outage limited applications with constraints on energy-per-bit consumption of the system. For this purpose, at a target delay-outage probability, the link-layer energy efficiency, referred to as effective-EE, is measured by the ratio of effective capacity (EC) and the total expenditure power, including the transmission power and the circuit power. At first, the maximum effective-EE of the channel at a target delay-outage probability is found. Then, the optimal power allocation strategy is obtained to maximize EC subject to an effective-EE constraint with the limit set at a certain ratio of the maximum achievable effective-EE of the channel. We then investigate the effect of the circuit power level on the maximum EC. Further, to set a guideline on how to choose the effective-EE limit, we obtain the transmit power level at which the rate of increasing EC (as a function of transmit power) matches a scaled rate of losing effective-EE. Analytical results show that a considerable EC-gain can be achieved with a small sacrifice in effective-EE from its maximum value. This gain increases considerably as the delay constraint becomes tight

The Decay Lifetime of Polarized Fermions in Flight

Based on the parity violation in Standard model, we study the dependence of lifetime on the helicity of an initial-state fermion in weak interactions. It is pointed out that if the initial fermions in the decays are longitudinally polarized, then the decay lifetime of left-handed polarized fermions is different from that of right-handed polarized fermions in flight with a same velocity in a same inertial system.Comment: 7 pages, Late

Driving with Sharks: Rethinking Connected Vehicles with Vehicle Cyber Security

In a public service announcement on March 17, 2016, the Federal Bureau of Investigation (FBI) jointly with the Department of Transportation and the National Highway Traffic Safety Administration, released a warning over the increasing vulnerability of motor vehicles to remote exploits . Engine shutdown, disable brakes and door locks are few examples of the possible vehicle cyber security attacks. Modern cars grow into a new target for cyberattacks as they become increasingly connected. While driving on the road, sharks (i.e., hackers) only need to be within communication range of your vehicle to attack it. However, in some cases, they can hack into it while they are miles away. In this article, we aim to illuminate the latest vehicle cyber security threats including malware attacks, On-Board Diagnostic (OBD) vulnerabilities, and auto mobile apps threats. We illustrate the In-Vehicle network architecture and demonstrate the latest defending mechanisms that are designed to mitigate such threats

Distributed Resource Allocation Assisted by Intercell Interference Mitigation in Downlink Multicell MC DS-CDMA Systems

This paper investigates the allocation of resources, including subcarriers and spreading codes, as well as intercell interference (ICI) mitigation for multicell downlink multicarrier direct-sequence code division multiple-access systems, which aim to maximize the system's spectral efficiency (SE). The analytical benchmark scheme for resource allocation and ICI mitigation is derived by solving or closely solving a series of mixed integer non-convex optimization problems. Based on the optimization objectives the same as the benchmark scheme, we propose a novel distributed resource allocation assisted by ICI mitigation scheme referred to as resource allocation assisted by ICI mitigation (RAIM), which requires very low implementation complexity and demands little backhaul resource. Our RAIM algorithm is a fully distributed algorithm, which consists of the subcarrier allocation (SA) algorithm named RAIM-SA, spreading code allocation (CA) algorithm called RAIM-CA and the ICI mitigation algorithm termed RAIM-IM. The advantages of the RAIM are that its CA only requires limited binary ICI information of intracell channels, and it is able to make mitigation decisions without any knowledge of ICI information. Our simulation results show that the proposed RAIM scheme, with very low complexity required, achieves significantly better SE performance than other existing schemes, and its performance is very close to that obtained by the benchmark scheme

Tradeoff Analysis and Joint Optimization of Link-Layer Energy Efficiency and Effective Capacity Toward Green Communications

A joint optimization problem of link-layer energy efficiency (EE) and effective capacity (EC) in a Nakagami-m fading channel under a delay-outage probability constraint and an average transmit power constraint is considered and investigated in this paper. First, a normalized multi-objective optimization problem (MOP) is formulated and transformed into a single-objective optimization problem (SOP), by applying the weighted sum method. The formulated SOP is then proved to be continuously differentiable and strictly quasiconvex in the optimum average input power, which turns out to be a cup shape curve. Furthermore, the weighted quasiconvex tradeoff problem is solved by first using Charnes-Cooper transformation and then applying Karush-Kuhn-Tucker (KKT) conditions. The proposed optimal power allocation, which includes the optimal strategy for the link-layer EE-maximization problem and the EC-maximization problem as extreme cases, is proved to be sufficient for the Pareto optimal set of the original EE-EC MOP. Moreover, we prove that the optimum average power level monotonically decreases with the importance weight, but strictly increases with the normalization factor, the circuit power and the power amplifier efficiency. Simulation results confirm the analytical derivations and further show the effects of fading severeness and transmission power limit on the tradeoff performance