Worst-case Design Research Articles

Probabilistic-constrained robust secure transmission for energy harvesting over MISO channels

In this paper, we consider a system supporting simultaneous wireless information and power transfer (SWIPT),where the transmitter delivers private message to a destination receiver (DR) and powers to multipleenergy receivers (ERs) with multiple single-antenna external eavesdroppers (Eves). We study secure robust beamformer and powersplitting (PS) design under imperfect channel state information (CSI).The artificial noise (AN) scheme is further utilized at the transmitter to provide strong wireless security.We aim at maximizing the energy harvested by ERs subject to the transmission power constraint, a range of outageconstraints concerning the signal-to-interference-plus-noise ratio (SINR) recorded at the DR and the Eves, as well as concerningthe energy harvested at the DR. The energy harvesting maximization (EHM) problem is challenging to directly solve,we resort to Bernstein-type inequality restriction technique to reformulatethe original problem as a tractable approximated version. Numerical results show that our robust beamforming schemeoutperforms the beamforming scheme relying on the worst-case design philosophy.

Revisited Perturbation Frequency Design Guideline for Direct Fixed-Step Maximum Power Point Tracking Algorithms

In order to optimize the performance of direct (or perturbative) fixed-step maximum power point tracking algorithms (e.g., perturb and observe and incremental conductance), two design parameters—perturbation frequency and step size—must be selected. The main requirement for perturbation frequency design is ensuring the period between two successive perturbations is longer than settling time of photovoltaic generator power transient. According to existing design guidelines, perturbation frequency should be selected at maximum power point, corresponding to standard test conditions. However, due to finite resolution of digital controllers, maximum power region rather than single maximum power point exists in practice. Therefore, operating point can arbitrarily reside within this region, belonging either to constant-current or constant-voltage I–V curve parts. It is shown that the photovoltaic generator power transient settling process is significantly slower in constant current than maximum power region due to increased value of dynamic resistance. Consequently, perturbation frequency design should be carried out in constant-current region rather than at maximum power point. Short-circuit condition should be selected as worst-case design operation point, where photovoltaic generator dynamic resistance obtains highest value. Then, perturbation frequency design becomes photovoltaic generator independent, influenced only by interfacing converter component values. Experimental results validate presented findings successfully.

Increasing the energy efficiency of microcontroller platforms with low-design margin co-processors

Reducing the energy consumption in low cost, performance-constrained microcontroller units (MCU’s) cannot be achieved with complex energy minimization techniques (i.e. fine-grained DVFS, Thermal Management, etc), due to their high overheads. To this end, we propose an energy-efficient, multi-core architecture combining two homogeneous cores with different design margins. One is a performance-guaranteed core, also called Heavy Core (HC), fabricated with a worst-case design margin. The other is a low-power core, called Light Core (LC), which has only a typical-corner design margin. Post-silicon measurements show that the Light core has a 30% lower power density compared to the Heavy core, with only a small loss in reliability. Furthermore, we derive the energy-optimal workload distribution and propose a runtime environment for Heavy/Light MCU platforms. The runtime decreases the overall energy by exploiting available parallelism to minimize the platform’s active time. Results show that, depending on the core to peripherals power-ratio and the Light core’s operating frequency, the expected energy savings range from 10 to 20%.

Topology optimization under uncertainty via non-intrusive polynomial chaos expansion

This paper presents a systematic approach for topology optimization under uncertainty that integrates non-intrusive polynomial chaos expansion with design sensitivity analysis for reliability-based and robust topology optimization. Uncertainty is introduced in loading and in geometry to address the manufacturing variability. The manufacturing variability is modeled via a thresholding technique in which the threshold field is represented by a reduced dimensional random field. Response metrics such as compliance and volume are characterized as polynomial chaos expansions of the underlying uncertain parameters thus allowing accurate and efficient estimation of statistical moments, failure probabilities and their sensitivities. The number of simulations is reduced for linear structures under loading uncertainty by means of superposition. Efficiency of the non-intrusive polynomial chaos approach is highlighted by comparison with the Monte Carlo method in terms of the number of simulations. To demonstrate the effect of uncertainty, optimized designs that consider uncertainty are compared to those that do not. Comparisons of polynomial chaos expansion to existing analytical methods on a benchmark numerical example are also provided for reliability-based and worst case designs.

Uncertainties Associated with Tunnel Design Fire Scenarios

Computer fire modelling and design fire scenarios are traditionally used in the tunnel design process to challenge tunnel systems, e.g. smoke ventilation, evacuation routes and strategy, and the exposure of structural members. In general, any such fire scenario should be reasonably severe, however, not unrealistically, which may lead to unnecessary over-designing and cost increase. This approach is commonly referred to as the worst-case design fire approach. The objective of the paper is to analyze the impact of uncertainties associated with input data and design fire selection on the representativeness of the design fire scenario. Firstly, the design fire scenario specifications are mapped and uncertainties relating to input data identified and quantified. Subsequently, a risk-based design fire selection approach is introduced taking into account the objective of the analysis: life safety or property protection. The paper is concluded with recommendations regarding the significance of selected input parameters, given analysis objectives, and the possibilities of their uncertainty treatment.

Probabilistic Robust Secure Beamforming in MISO Channels With Imperfect LCSI and Statistical ECSI

In this paper, we investigate the robust secure transmit beamformming design for multiple-input single-output wiretap channels overheard by multiple non-collaborating single-antenna eavesdroppers. Assuming that at the transmitter, the instantaneous legitimate receiver’s channel state information (CSI) is imperfect and only the statistical eavesdroppers’ CSI is known, we seek to maximize the target secrecy rate $R$ with the total transmit power constraint and the secrecy outage probability constraint. The resulting outage-constrained secrecy rate maximization (O-SRM) is non-convex and difficult to solve. Thus, we develop an efficient algorithm to solve it and determine the robust secure beamforming design. Specifically speaking, we first prove that the original O-SRM problem can be solved by an equivalent outage-constrained power minimization problem (O-PMP), which is easy to perform semi-definite relaxation (SDR) and can be solved by semi-definite program (SDP) consequently. Second, we transform the non-convex secrecy rate outage constraints into deterministic ones by resorting to Bernstein-type inequality II. Finally, by solving the convex approximation of the O-PMP with different $R\text{s}$ and bisection search over $R$ , we convert the original O-SRM problem into a sequence of solvable SDPs. Simulation results are provided to verify the secrecy-rate performance improvement of the proposed robust beamforming compared with the existing worst-case design proposed by Li and Ma and the simple non-robust maximum-ratio transmission.

PSO-Based Voltage Control Strategy for Loadability Enhancement in Smart Power Grids

This paper proposes a new voltage control methodology using the particle swarm optimization (PSO) technique for smart grid loadability enhancement. The goal of this paper is to achieve reliable and efficient voltage profile/stability regulation in power grids. This methodology is based on the decouple power flow equations and the worst-case design technique. Specifically, the secondary voltage control (SVC) problem is formulated as an L-infinity norm minimization problem which considers overall load voltage deviations in electrical power systems as an objective model, and the PSO technique is employed to determine a robust control action which aims to improve voltage profile and to enlarge transmission grid loadability by optimal coordinated control of VAR sources. The methodology was successfully tested on several IEEE benchmark systems.

Kriging based robust optimisation algorithm for minimax problems in electromagnetics

Abstract The paper discusses some of the recent advances in kriging based worst-case design optimisation and proposes a new two-stage approach to solve practical problems. The efficiency of the infill points allocation is improved significantly by adding an extra layer of optimisation enhanced by a validation process.

Robust secure switching transmission in multi‐antenna relaying systems: cooperative jamming or decode‐and‐forward beamforming

In this study, the authors investigate the physical layer security for safeguarding secure transmission in multi-antenna relaying networks with imperfect channel state information (CSI). Different from traditional strategies in multi-antenna relaying systems, which would terminate the communication if the relay could not decode the signals successfully, the authors propose robust secure transmission strategy which switches between cooperative jamming (CJ) and decode-and-forward (DF) beamforming. Specifically, if the received signal-to-noise ratio at the relay is lower than a predefined threshold, it will impose CJ signals on potential eavesdropper, otherwise the relay would operate DF beamforming. The authors’ objective is to maximise secrecy rate and minimise secrecy outage probability in different practical communication scenarios with relaxed or strict time-delay constraint. Thus, given the unavailability of the perfect eavesdropping CSI, the authors propose a worst-case robust design and a statistical-approach robust design based on secrecy rate and secrecy outage criterion, respectively. In addition, a traditional DF robust scheme and a non-robust scheme are also considered as benchmarks. Simulation results verify that the proposed scheme significantly outperforms the traditional DF robust scheme and the non-robust scheme.

Resource Efficiency: A New Beamforming Design for Multicell Multiuser Systems

Apart from spectral efficiency (SE), energy efficiency (EE) has become an important metric for future wireless communication systems. However, how to achieve balance between SE and EE for a multicell multiuser coordinated beamforming system remains an open problem. In this paper, we propose a new paradigm for EE–SE balancing, namely, using a new metric called resource efficiency (RE) as the objective function to achieve a reasonable tradeoff between SE and EE. The considered optimization problem is more complex than traditional problems and, in general, is NP-hard for finding the globally optimal solution. To obtain insight into the problem, we first equivalently transform the original problem into a parameterized subtractive form optimization problem with some auxiliary variables by using the fraction programming theory. Then, a successive convex approximation method and the classical second-order cone programming method are jointly used to solve the equivalent problem. Finally, an effective algorithm with proven convergence is proposed to obtain the solution to the considered RE optimization. In addition, the algorithm is further extended to consider imperfect channel state information (CSI) using the worst-case design. Extensive numerical simulations are given to validate the effectiveness of our algorithm.

Combine Flash-Based FPGA TID and Long-Term Retention Reliabilities Through ${{\rm V}_{\rm T}}$ Shift

Reliability test results of data retention and total ionizing dose (TID) in 65 nm Flash-based field programmable gate array (FPGA) are presented. Long-chain inverter design is recommended for reliability evaluation because it is the worst case design for both effects. Based on preliminary test data, both issues are unified and modeled by one natural decay equation. The relative contributions of TID induced threshold-voltage shift and retention mechanisms are evaluated by analyzing test data.

Thermally Adaptive Cache Access Mechanisms for 3D Many-Core Architectures

A compelling confluence of technology and application trends in which the cost, execution time, and energy of applications are being dominated by the memory system is driving the industry to 3D packages for future microarchitectures. However, these packages result in high heat fluxes and increased thermal coupling challenging current thermal solutions. Conventional design approaches utilize design margins that correspond to worst case temperatures and process corners leading to a significant impact on system level performance. This paper advocates a design approach based on microarchitecture adaptation to device-level temperature-dependent delay variations to realize average case performance that is superior to which can be achieved by using worst case design margins. We demonstrate this approach with adaptation principles for the last level cache (LLC) in a 3D many-core architecture. We propose and evaluate two adaptation mechanisms. In the first case, the access time to the LLC from the L1 tracks the LLC’s temperature-delay variations. In the second case, the processor DVFS state tracks the LLC temperature as a negative feedback. Compared to a worst case design baseline, the full system simulation results show that both approaches increase the IPC by over 20 percent, and improve the energy efficiency by up to 3 percent.

On-the-fly adaptivity for process networks over shared-memory platforms

Modern MPSoC architectures incorporate tens of processing elements on a single die. This trend poses the need of expressing the parallelism of the applications in order to effectively exploit the available resources. Several models of computation have been proposed, that specify an application as a network of independent computational elements. Such models represent a suitable solution for systematic mapping of parallel applications onto multiprocessor architectures. However, the workload of a given application can abruptly vary, as well as the amount of computing resources available, depending on the overall workload of the system and on the input data dependency. Traditional worst-case designs may overestimate workloads, leading to resource wasting and unnecessary power consumption. To overcome such limitation, in this work we devise a fast, run-time and automatic approach able to quickly re-configure the core-to-task mapping and the degree of parallelism of the application when the available resources or the application workload change, targeting shared-memory platforms. Experiments, carried out using an FPGA implementation, demonstrate the effectiveness of the proposed approach, in terms of achievable speed-up, power saving and introduced overhead.

Opportunistic relaying and jamming with robust design in hybrid full/half-duplex relay system

Full duplex (FD) protocol has been widely used in wireless communications, which could transmit and receive signals at the meantime. In this paper, considering the worst-case channel uncertainty, opportunistic relaying and jamming strategy in decode-and-forward (DF) hybrid full/half-duplex (HD) relay system is proposed to enhance security. Specifically, the relay works in FD protocol to receive the confidential signals and transmit jamming signals at the first time slot. Then, the relay switches to HD protocol to transmit the decoded signals. Meanwhile, jammers emit cooperative jamming (CJ) signals to interfere the eavesdropper at two transmission slots. Suppose that imperfect eavesdropper channel condition is considered, we propose a worst-case robust design to obtain distributed jamming weights, which is solved through semi-definite program (SDP). Furthermore, we analyze secrecy rate and secrecy outage performance of the proposed scheme. As a benchmark, a traditional relay selection strategy with HD protocol in distributed relay system is listed for comparison. Simulation results demonstrate that our hybrid scheme with robust design outperforms the traditional relay selection scheme, because the traditional scheme does not consider hybrid FD/HD protocols and robust design based on imperfect channel conditions.

Robust Monotonic Convergent Iterative Learning Control

This technical note presents an approach to deal with model uncertainty in iterative learning control (ILC). Model uncertainty generally degrades the performance of conventional learning algorithms. To deal with this problem, a robust worst-case norm-optimal ILC design is introduced. The design problem is reformulated as a convex optimization problem, which can be solved efficiently. The technical note also shows that the proposed robust ILC is equivalent to conventional norm-optimal ILC with trial-varying parameters; accordingly, the design tradeoff between robustness and convergence speed is analyzed.

Robust Beamforming Design for Max–Min SINR in MIMO Interference Channels

This letter considers the max-min signal-to-interference-plus-noise ratio (SINR) problem for single stream multi-input multi-output (MIMO) interference channels with imperfect channel state information (CSI). Assuming bounded CSI error, we recast this problem as a worst-case fairness problem with linear matrix inequalities (LMI) constraints. Due to its nonconvexity, we propose an iterative algorithm in which the transmit and the receive beamformers are obtained alternately to solve the worst-case max-min fairness beamforming design problem. The beamformers generated by the proposed algorithm monotonically improve the min-SINR utility and guarantee to converge to a local optimal solution. Simulation results demonstrate the convergence behavior and the robustness of the proposed algorithm.

Simplified fragility-based risk analysis for impulse governed blast loading scenarios

Blast-loaded structures are presently assessed and designed following a deterministic approach, where only a set of structural analyses under worst-case design scenarios are carried out in order to verify each limit state. As a rational alternative, a conditional probabilistic approach is introduced to offer comprehensive risk assessment and to allow the design with user-defined confidence in meeting performance targets in view of uncertainties. To simplify the probabilistic consideration of the uncertain parameters, the determination of the blast hazard and the structural response are decoupled into the evaluation of blast hazard curves and structural fragilities curves, respectively, by introducing a single conditioning intensity measure. This is chosen to be the impulse density, shown to be sufficient for impulse-governed scenarios, achieving a reduction of the computational effort by several orders of magnitude without introducing bias. Furthermore a problem-specific safety factor formulation is introduced to incorporate the influence of uncertainties in a simple manner, akin to current engineering practice. As a proof-of-concept test, a steel built-up blast resistant door is subjected to an accidental detonation of mortar rounds in a military facility. The equivalent single degree of freedom model is adopted in order to conduct the structural analyses, while detailed finite element analyses are carried out for validation. Finally, the conditional approach risk analysis on the steel door is compared against the results obtained through the comprehensive (probabilistic) unconditional approach, showing the validity of both the proposed intensity measure and safety factor formulation.

Robust time varying sliding sector for uncertain structures control

In this paper, a novel type of control strategy for the active control of uncertain civil structures is introduced. Robust time varying sliding sector for the active control of large, uncertain structures is proposed. The introduced method is chatter free and continuous. Chattering phenomenon is the main drawback in sliding mode controllers. This method is based on defining appropriate sliding sectors with their respective control rules. Sliding sector controller moves system’s states from outside the sector to inside of it with suitable control input. A large structure equipped with active tendons and with mass, stiffness and damping uncertainty is considered. The worst case design is considered where structure’s mass increases and its stiffness and damping coefficients decrease. Furthermore, by applying actuators’ failure, damage-tolerance capacity of the second-order sliding sector is investigated. The structure is subjected to different earth excitations to demonstrate the feasibility of proposed method under various earthquakes with different frequencies. The controlled responses of the structure are compared with LQR method which is a highly robust controller. Comparative results of the numerical simulation are presented to confirm the proposed method robustness and its ability to reduce the structures response under earthquake excitation, effectively.

Joint Optimization of Transceiver Matrices for MIMO-Aided Multiuser AF Relay Networks: Improving the QoS in the Presence of CSI Errors

This paper addresses the problem of amplify-and-forward (AF) relaying for multiple-input-multiple-output (MIMO) multiuser relay networks, where each source transmits multiple data streams to its corresponding destination with the assistance of multiple relays. Assuming realistic imperfect channel state information (CSI) of all the source-relay and relay-destination links, we propose a robust optimization framework for the joint design of the source transmit precoders (TPCs), relay AF matrices and receive filters. Specifically, two well-known CSI error models are considered, namely, the statistical and the norm-bounded error models. We commence by considering the problem of minimizing the maximum per-stream mean square error (MSE) subject to the source and relay power constraints (min-max problem). Then, the statistically robust and worst-case robust versions of this problem, which take into account the statistical and norm-bounded CSI errors, respectively, are formulated. Both of the resultant optimization problems are nonconvex (semi-infinite in the worst-case robust design). Therefore, algorithmic solutions having proven convergence and tractable complexity are proposed by resorting to the iterative block coordinate update approach along with matrix transformation and convex conic optimization techniques. We then consider the problem of minimizing the maximum per-relay power subject to the quality-of-service (QoS) constraints for each stream and the source power constraints (QoS problem). Specifically, an efficient initial feasibility search algorithm is proposed based on the relationship between the feasibility check and the min-max problems. Our simulation results show that the proposed joint transceiver design is capable of achieving improved robustness against different types of CSI errors when compared with nonrobust approaches.

A first order approach for worst-case shape optimization of the compliance for a mixture in the low contrast regime

The purpose of this article is to propose a deterministic method for optimizing a structure considering its worst possible behaviour when a small uncertainty exists over its Lame parameters. The idea is to take advantage of the small parameter to derive an asymptotic expansion of the displacement and of the compliance with respect to the contrast in Lame coefficients. We are then able to compute the worst case design as post-treatment of the computation of the displacement field for the nominal parameters. The domain evolution resulting from the optimization is performed here using the level set method. The computational cost of our method remains of the same order as the cost of the optimization for a homogeneous material.