Cross-layer Energy-Efficiency Optimization of Packet Based Wireless MIMO Communication Systems

Energy in today's short-range wireless communication is mostly spent on the analog- and digital hardware rather than on radiated power. Hence,purely information-theoretic considerations fail to achieve the lowest energy per information bit and the optimization process must carefully consider the overall transceiver. In this paper, we propose to perform cross-layer optimization, based on an energy-aware rate adaptation scheme combined with a physical layer that is able to properly adjust its processing effort to the data rate and the channel conditions to minimize the energy consumption per information bit. This energy proportional behavior is enabled by extending the classical system modes with additional configuration parameters at the various layers. Fine grained models of the power consumption of the hardware are developed to provide awareness of the physical layer capabilities to the medium access control layer. The joint application of the proposed energy-aware rate adaptation and modifications to the physical layer of an IEEE802.11n system, improves energy-efficiency (averaged over many noise and channel realizations) in all considered scenarios by up to 44%.

Energy efficiency optimization in hardware-constrained large-scale MIMO systems

Large-scale multiple-input multiple-output (MIMO) communication systems can bring substantial improvement in spectral efficiency and/or energy efficiency, due to the excessive degrees-of-freedom and huge array gain. However, large-scale MIMO is expected to deploy lower-cost radio frequency (RF) components, which are particularly prone to hardware impairments. Unfortunately, compensation schemes are not able to remove the impact of hardware impairments completely, such that a certain amount of residual impairments always exists. In this paper, we investigate the impact of residual transmit RF impairments (RTRI) on the spectral and energy efficiency of training-based point-to-point large-scale MIMO systems, and seek to determine the optimal training length and number of antennas which maximize the energy efficiency. We derive deterministic equivalents of the signal-to-noise-and-interference ratio (SINR) with zero-forcing (ZF) receivers, as well as the corresponding spectral and energy efficiency, which are shown to be accurate even for small number of antennas. Through an iterative sequential optimization, we find that the optimal training length of systems with RTRI can be smaller compared to ideal hardware systems in the moderate SNR regime, while larger in the high SNR regime. Moreover, it is observed that RTRI can significantly decrease the optimal number of transmit and receive antennas.

Joint Optimization of Area Spectral Efficiency and Delay over PPP Interfered Ad-Hoc Networks

To evaluate the performance of the co-channel transmission based communication, we propose a new metric for area spectral efficiency (ASE) of interference limited ad-hoc network by assuming that the nodes are randomly distributed according to a Poisson point processes (PPP). We introduce a utility function, U = ASE/delay and derive the optimal ALOHA transmission probability p and the SIR threshold τ that jointly maximize the ASE and minimize the local delay. Finally, numerical results have been conducted to confirm that the joint optimization based on the U metric achieves a significant performance gain compared to conventional systems.

Laser-Driven Proton Beams: Acceleration Mechanism, Beam Optimization, and Radiographic Applications

This paper reviews recent experimental activity in the area of optimization, control, and application of laser accelerated proton beams, carried out at the Rutherford Appleton Laboratory and the Laboratoire pour l’Utilisation des Lasers Intenses 100 TW facility in France. In particular, experiments have investigated the role of the scale length at the rear of the plasma in reducing target-normal-sheath-acceleration acceleration efficiency. Results match with recent theoretical predictions and provide information in view of the feasibility of proton fast-ignition applications. Experiments aiming to control the divergence of the proton beams have investigated the use of a laser-triggered microlens, which employs laser-driven transient electric fields in cylindrical geometry, enabling to focus the emitted
protons and select monochromatic beam lets out of the broad spectrum beam. This approach could be advantageous in view
of a variety of applications. The use of laser-driven protons as a particle probe for transient field detection has been developed and
applied to a number of experimental conditions. Recent work in this area has focused on the detection of large-scale self-generated magnetic fields in laser-produced plasmas and the investigation of fields associated to the propagation of relativistic electron both on the surface and in the bulk of targets irradiated by high-power laser pulses.

Investigating the efficiency of fitting Coxian phase-type distributions to health care data

Coxian phase-type distributions are becoming a popular means of representing survival times within a health care environment. They are favoured as they show a distribution as a system of phases and can allow for an easy visual representation of the rate of flow of patients through a system. Difficulties arise, however, in determining the parameter estimates of the Coxian phase-type distribution. This paper examines ways of making the fitting of the Coxian phase-type distribution less cumbersome by outlining different software packages and algorithms available to perform the fit and assessing their capabilities through a number of performance measures. The performance measures rate each of the methods and help in identifying the more efficient. Conclusions drawn from these performance measures suggest SAS to be the most robust package. It has a high rate of convergence in each of the four example model fits considered, short computational times, detailed output, convergence criteria options, along with a succinct ability to switch between different algorithms.

Multi-Fidelity Multidisciplinary Whole Engine Thermo-Mechanical Design Optimization

Traditionally, the optimization of a turbomachinery engine casing for tip clearance has involved either twodimensional transient thermomechanical simulations or three-dimensional mechanical simulations. This paper illustrates that three-dimensional transient whole-engine thermomechanical simulations can be used within tip clearance optimizations and that the efficiency of such optimizations can be improved when a multifidelity surrogate modeling approach is employed. These simulations are employed in conjunction with a rotor suboptimization using surrogate models of rotor-dynamics performance, stress, mass and transient displacements, and an engine parameterization.

On The Energy-Efficiency of Byte-Addressable Non-Volatile Memory

Non-Volatile Memory (NVM) technology holds promise to replace SRAM and DRAM at various levels of the memory hierarchy. The interest in NVM is motivated by the difficulty faced in scaling DRAM beyond 22 nm and, long-term, lower cost per bit. While offering higher density and negligible static power (leakage and refresh), NVM suffers increased latency and energy per memory access. This paper develops energy and performance models of memory systems and applies them to understand the energy-efficiency of replacing or complementing DRAM with NVM. Our analysis focusses on the application of NVM in main memory. We demonstrate that NVM such as STT-RAM and RRAM is energy-efficient for memory sizes commonly employed in servers and high-end workstations, but PCM is not. Furthermore, the model is well suited to quickly evaluate the impact of changes to the model parameters, which may be achieved through optimization of the memory architecture, and to determine the key parameters that impact system-level energy and performance.

Experimental design and batch experiments for optimization of Cr(VI) removal from aqueous solutions by hydrous cerium oxide nanoparticles

Hydrous cerium oxide (HCO) was synthesized by intercalation of solutions of cerium(III) nitrate and sodium hydroxide and evaluated as an adsorbent for the removal of hexavalent chromium from aqueous solutions. Simple batch experiments and a 2⁵ factorial experimental design were employed to screen the variables affecting Cr(VI) removal efficiency. The effects of the process variables; solution pH, initial Cr(VI) concentration, temperature, adsorbent dose and ionic strength were examined. Using the experimental results, a linear mathematical model representing the influence of the different variables and their interactions was obtained. Analysis of variance (ANOVA) demonstrated that Cr(VI) adsorption significantly increases with decreased solution pH, initial concentration and amount of adsorbent used (dose), but slightly decreased with an increase in temperature and ionic strength. The optimization study indicates 99% as the maximum removal at pH 2, 20 °C, 1.923 mM of metal concentration and a sorbent dose of 4 g/dm³. At these optimal conditions, Langmuir, Freundlich and Redlich–Peterson isotherm models were obtained. The maximum adsorption capacity of Cr(VI) adsorbed by HCO was 0.828 mmol/g, calculated by the Langmuir isotherm model. Desorption of chromium indicated that the HCO adsorbent can be regenerated using NaOH solution 0.1 M (up to 85%). The adsorption interactions between the surface sites of HCO and the Cr(VI) ions were found to be a combined effect of both anion exchange and surface complexation with the formation of an inner-sphere complex.

Dipolar emission in trench metal-insulator-metal waveguides for short-scale plasmonic communications: numerical optimization

Here we consider the numerical optimization of active surface plasmon polariton (SPP) trench waveguides suited for integration with luminescent polymers for use as highly localized SPP source devices in short-scale communication integrated circuits. The numerical analysis of the SPP modes within trench waveguide systems provides detailed information on the mode field components, effective indices, propagation lengths and mode areas. Such trench waveguide systems offer extremely high confinement with propagation on length scales appropriate to local interconnects, along with high efficiency coupling of dipolar emitters to waveguided plasmonic modes which can be close to 80%. The large Purcell factor exhibited in these structures will further lead to faster modulation capabilities along with an increased quantum yield beneficial for the proposed plasmon-emitting diode, a plasmonic analog of the light-emitting diode. The confinement of studied guided modes is on the order of 50 nm and the delay over the shorter 5 μm length scales will be on the order of 0.1 ps for the slowest propagating modes of the system, and significantly less for the faster modes.

DFIG Machine Design for Maximizing Power Output Based on Surrogate Optimization Algorithm

This paper presents a surrogate-model based optimization of a doubly-fed induction generator (DFIG) machine winding design for maximizing power yield. Based on site-specific wind profile data and the machine’s previous operational performance, the DFIG’s stator and rotor windings are optimized to match the maximum efficiency with operating conditions for rewinding purposes. The particle swarm optimization (PSO)-based surrogate optimization techniques are used in conjunction with the finite element method (FEM) to optimize the machine design utilizing the limited available information for the site-specific wind profile and generator operating conditions. A response surface method in the surrogate model is developed to formulate the design objectives and constraints. Besides, the machine tests and efficiency calculations follow IEEE standard 112-B. Numerical and experimental results validate the effectiveness of the proposed technologies.

Energy Saving - Another Perspective for Parameter Optimization of P and PI Controllers

Modern control methods like optimal control and model predictive control (MPC) provide a framework for simultaneous regulation of the tracking performance and limiting the control energy, thus have been widely deployed in industrial applications. Yet, due to its simplicity and robustness, the conventional P (Proportional) and PI (Proportional–Integral) control are still the most common methods used in many engineering systems, such as electric power systems, automotive, and Heating, Ventilation and Air Conditioning (HVAC) for buildings, where energy efficiency and energy saving are the critical issues to be addressed. Yet, little has been done so far to explore the effect of its parameter tuning on both the system performance and control energy consumption, and how these two objectives are correlated within the P and PI control framework. In this paper, the P and PI controllers are designed with a simultaneous consideration of these two aspects. Two case studies are investigated in detail, including the control of Voltage Source Converters (VSCs) for transmitting offshore wind power to onshore AC grid through High Voltage DC links, and the control of HVAC systems. Results reveal that there exists a better trade-off between the tracking performance and the control energy through a proper choice of the P and PI controller parameters.

Building information modeling based building design optimization for sustainability

Environmental problems, especially climate change, have become a serious global issue waiting for people to solve. In the construction industry, the concept of sustainable building is developing to reduce greenhouse gas emissions. In this study, a building information modeling (BIM) based building design optimization method is proposed to facilitate designers to optimize their designs and improve buildings’ sustainability. A revised particle swarm optimization (PSO) algorithm is applied to search for the trade-off between life cycle costs (LCC) and life cycle carbon emissions (LCCE) of building designs. In order tovalidate the effectiveness and efficiency of this method, a case study of an office building is conducted in Hong Kong. The result of the case study shows that this method can enlarge the searching space for optimal design solutions and shorten the processing time for optimal design results, which is really helpful for designers to deliver an economic and environmental friendly design scheme.

Aerodynamic optimization using Adjoint methods and parametric CAD models

This paper describes an implementation of a method capable of integrating parametric, feature based, CAD models based on commercial software (CATIA) with the SU2 software framework. To exploit the adjoint based methods for aerodynamic optimisation within the SU2, a formulation to obtain geometric sensitivities directly from the commercial CAD parameterisation is introduced, enabling the calculation of gradients with respect to CAD based design variables. To assess the accuracy and efficiency of the alternative approach, two aerodynamic optimisation problems are investigated: an inviscid, 3D, problem with multiple constraints, and a 2D high-lift aerofoil, viscous problem without any constraints. Initial results show the new parameterisation obtaining reliable optimums, with similar levels of performance of the software native parameterisations. In the final paper, details of computing CAD sensitivities will be provided, including accuracy as well as linking geometric sensitivities to aerodynamic objective functions and constraints; the impact in the robustness of the overall method will be assessed and alternative parameterisations will be included.