The impact of intersymbol interference (ISI) on single carrier frequency domain equalization with multiple input multiple output (MIMO-SCFDE) systems is severe. Most existing channel equalization methods fail to solve it completely. In this paper, given the disadvantages of the error propagation and the gap from matched filter bound (MFB), we creatively introduce a decision feedback equalizer with frequency-domain bidirectional noise prediction (DFE-FDBiNP) to tackle intersymbol interference (ISI) in MIMO-SCFDE systems. The equalizer has two-part equalizer, that is the normal mode and the time-reversal mode decision feedback equalization with noise prediction (DFE-NP). Equal-gain combining is used to realize a greatly simplified and low complexity diversity combining. Analysis and simulation results validate the improved performance of the proposed method in quasi-static frequency-selective fading MIMO channel for a typical urban environment.

This paper proposes novel nonlinear precoding for XOR-physical layer network coding (XOR-PNC) to improve the performance of bi-directional MIMO relay systems. The proposed precoder comprises a pre-equalizer and a nonlinear filter, which we also propose in the paper. We theoretically analyze the performance of the XOR-PNC with the proposed nonlinear precoding. As a result, it is shown that the proposed pre-equalizer improves the distribution of the received signals at relays, while the nonlinear precoder not only improves the transmission power efficiency but also simplifies the receiver at the relays. The performance is confirmed by computer simulation. The XOR-PNC with the proposed precoding achieves almost the lower bound in BER performance, which is much better than the amplify-and-forward physical layer network coding (AF-PNC).

The end-to-end packet error rate (PER) performance of a multi-hop cooperative relaying system is discussed in this paper. In this system, the end-to-end PER performance improves with the number of hops under certain conditions. The PER performance of multi-hop cooperative networks is analyzed with the state transition technique. The theoretical analysis reveals that the PER performance can be kept almost constant, or even improved, as the number of hops is increased. Computer simulation results agree closely with the analysis results. Moreover, to confirm this performance characteristic in an actual setup, an in-lab experiment using a fading emulator was conducted. The experimental results confirm the theoretical end-to-end PER performance of this system.

Doppler lidar (LIght Detection And Ranging) can provide accurate wind velocity vector estimates by processing the time delay and Doppler spectrum of received signals. This system is essential for real-time wind monitoring to assist aircraft taking off and landing. Considering the difficulty of calibration and cost, a single Doppler lidar model is more attractive and practical than a multiple lidar model. In general, it is impossible to estimate two or three dimensional wind vectors from a single lidar model without any prior information, because lidar directly observes only a 1-dimensional (radial direction) velocity component of wind. Although the conventional VAD (Velocity Azimuth Display) and VVP (Velocity Volume Processing) methods have been developed for single lidar model, both of them are inaccurate in the presence of local air turbulence. This paper proposes an accurate wind velocity estimation method based on a parametric approach using typical turbulence models such as tornado, micro-burst and gust front. The results from numerical simulation demonstrate that the proposed method remarkably enhances the accuracy for wind velocity estimation in the assumed modeled turbulence cases, compared with that obtained by the VAD or other conventional method.

This paper addresses the attribute recognition problem, a field of research that is dominated by studies in the visible spectrum. Only a few works are available in the thermal spectrum, which is fundamentally different from the visible one. This research performs recognition specifically on wearable attributes, such as glasses and masks. Usually these attributes are relatively small in size when compared with the human body, on top of a large intra-class variation of the human body itself, therefore recognizing them is not an easy task. Our method utilizes a decomposition framework based on Robust Principal Component Analysis (RPCA) to extract the attribute information for recognition. However, because it is difficult to separate the body and the attributes without any prior knowledge, noise is also extracted along with attributes, hampering the recognition capability. We made use of prior knowledge; namely the location where the attribute is likely to be present. The knowledge is referred to as the Probability Map, incorporated as a weight in the decomposition by RPCA. Using the Probability Map, we achieve an attribute-wise decomposition. The results show a significant improvement with this approach compared to the baseline, and the proposed method achieved the highest performance in average with a 0.83 F-score.

In this paper, we introduce a self-constructive Normalized Gaussian Network (NGnet) for online learning tasks. In online tasks, data samples are received sequentially, and domain knowledge is often limited. Then, we need to employ learning methods to the NGnet that possess robust performance and dynamically select an accurate model size. We revise a previously proposed localized forgetting approach for the NGnet and adapt some unit manipulation mechanisms to it for dynamic model selection. The mechanisms are improved for more robustness in negative interference prone environments, and a new merge manipulation is considered to deal with model redundancies. The effectiveness of the proposed method is compared with the previous localized forgetting approach and an established learning method for the NGnet. Several experiments are conducted for a function approximation and chaotic time series forecasting task. The proposed approach possesses robust and favorable performance in different learning situations over all testbeds.

Recent research has shown that the class of rotation symmetric Boolean functions is beneficial to cryptographics. In this paper, for an odd prime p, two sufficient conditions for p-variable rotation symmetric Boolean functions to be 1-resilient are obtained, and then several concrete constructions satisfying the conditions are presented. This is the first time that resilient rotation symmetric Boolean functions have been systematically constructed. In particular, we construct a class of 2-resilient rotation symmetric Boolean functions when p=2m+1 for m ≥ 4. Moreover, several classes of 1-order correlation immune rotation symmetric Boolean functions are also got.

An all-digital fully-synthesizable PVT-tolerant clock data recovery (CDR) architecture for wireline chip-to-chip interconnects is presented. The proposed architecture enables the co-synthesis of the CDR with the digital core. By eliminating the resource hungry manual layout and interfacing steps, which are necessary for conventional CDR topologies, the design process and the time-to-market can be drastically improved. Besides, the proposed CDR architecture enables the re-usability of majority of the sub-systems which enables easy migration to different process nodes. The proposed CDR is also equipped with a self-calibration scheme for ensuring tolerence over PVT. The proposed fully-syntehsizable CDR was implemented in 28nm FDSOI. The system achieves a maximum data rate of 10.06Gbps while consuming a power of 16.1mW from a 1V power supply.

Permutation polynomials over Zpn are useful in the design of cryptographic algorithms. In this paper, we obtain an equivalent condition for polynomial functions over Zpn to be permutations, and this equivalent condition can help us to analysis the randomness of such functions. Our results provide a method to distinguish permutation polynomials from random functions. We also introduce how to improve the randomness of permutation polynomials over Zpn.

In this paper, we study the problem of noise with regard to the perfect reconstruction of non-bandlimited signals, the class of signals having a finite number of degrees of freedom per unit time. The finite rate of innovation (FRI) method provides a means of recovering a non-bandlimited signal through using of appropriate kernels. In the presence of noise, however, the reconstruction function of this scheme may become ill-conditioned. Further, the reduced sampling rates afforded by this scheme can be accompanied by increased error sensitivity. In this paper, to obtain improved noise robustness, we propose the matrix pencil (MP) method for sample signal reconstruction, which is based on principal component analysis (PCA). Through the selection of an adaptive eigenvalue, a non-bandlimited signal can be perfectly reconstructed via a stable solution of the Yule-Walker equation. The proposed method can obtain a high signal-to-noise-ratio (SNR) for the reconstruction results. Herein, the method is applied to certain non-bandlimited signals, such as a stream of Diracs and nonuniform splines. The simulation results demonstrate that the MP and PCA are more effective than the FRI method in suppressing noise. The FRI method can be used in many applications, including those related to bioimaging, radar, and ultrasound imaging.

Through-silicon via (TSV) assignment problem is one of the key design challenges of 3-D IC which is crucial to the wire length and signal delay. In this work we formulate the 3-D IC TSV assignment as an Integer Minimum Cost Multi Commodity (IMCMC) problem on a IMCMC network, and propose a multi-level algorithm. It coarsens the IMCMC network level by level, applies a rough flow assignment on each level of coarsened graph, and generates only promising edges to reduce the IMCMC network size. Benefiting from the multi-level structure, we propose a mixed single and multi commodity flow method improve the TSV assignment solution quality. Moreover, given a TSV assignment, we propose an extended layer by layer algorithm to further optimize the TSV assignment. The experimental results demonstrate that our multi-level with mixed single and multi commodity flow algorithm achieves not only smaller wire length but also shorter runtime compared to other existing works.

The differential fault analysis of SOSEMNAUK was presented in Africacrypt in 2011. In this paper, we improve previous work with algebraic techniques which can result in a considerable reduction not only in the number of fault injections but also in time complexity. First, we propose an enhanced method to determine the fault position with a success rate up to 99% based on the single-word fault model. Then, instead of following the design of SOSEMANUK at word levels, we view SOSEMANUK at bit levels during the fault analysis and calculate most components of SOSEMANUK as bit-oriented. We show how to build algebraic equations for SOSEMANUK and how to represent the injected faults in bit-level. Finally, an SAT solver is exploited to solve the combined equations to recover the secret inner state. The results of simulations on a PC show that the full 384 bits initial inner state of SOSEMANUK can be recovered with only 15 fault injections in 3.97h.

The problem of radar constant-modulus (CM) waveform design for the detection of multiple targets is considered in this paper. The CM constraint is imposed from the perspective of hardware realization and full utilization of the transmitter's power. Two types of CM waveforms — the arbitrary-phase waveform and the quadrature phase shift keying waveform — are obtained by maximizing the minimum of the signal-to-clutter-plus-noise ratios of the various targets. Numerical results show that the designed CM waveforms perform satisfactorily, even when compared with their counterparts without constraints on the peak-to-average ratio.

In this paper, we describe the fabrication of low leakage Superconductor/Insulator/Superconductor (SIS) junctions with a Nb/Al/AlOx/Al/Nb structure. In other words, an extra Al layer was added onto the top of the insulator in a conventional Nb/Al/AlOx/Nb junction. We measured the current and voltage (IV) characteristics of both the Nb/Al/AlOx/Al/Nb and Nb/Al/AlOx/Nb junctions at the temperature of liquid helium, and found that the sub-gap leakage current in the Nb/Al/AlOx/Al/Nb junctions was much lower than that of the Nb/Al/AlOx/Nb junctions. Our analysis of the IV characteristics indicates that the quality of the AlOx insulator used in the Nb/Al/AlOx/Al/Nb junction was close to ideal, while the insulator used in the Nb/Al/AlOx/Nb junction had possible defects. According to the scanning transmission electron microscope (STEM) images and energy-dispersive X-ray spectroscopy (EDX) analyses, it was evident that the Nb atoms diffused into the bottom electrode of the Nb/Al/AlOx/Nb junction, while a smaller number diffused into the bottom electrode of the Nb/Al/AlOx/Al/Nb junction. Therefore, we conclude that the extra Al layer effectively acted as a buffer layer that prevented the Nb atoms from diffusing into the insulator and bottom electrode. The presence of the top Al layer is expected to favorably improve the quality of junctions with a very high current density, and support the extension of the RF and IF bandwidths of SIS mixers.

This paper introduces and uses spider monkey optimization (SMO) for synthesis sparse linear arrays, which are composed of a uniformly spaced core subarray and an extended sparse subarray. The amplitudes of all the elements and the locations of elements in the extended sparse subarray are optimized by the SMO algorithm to reduce the side lobe levels of the whole array, under a set of practical constraints. To show the efficiency of SMO, different examples are presented and solved. Simulation results of the sparse arrays designed by SMO are compared with published results to verify the effectiveness of the SMO method.

An 8-issue superscalar core generally requires a 24-port RAM for the register file. The area and energy consumption of a multiported RAM increase in proportional to the square of the number of ports. A register cache can reduce the area and energy consumption of the register file. However, earlier register cache systems suffer from lower IPC caused by register cache misses. Thus, we proposed the Non-Latency-Oriented Register Cache System (NORCS) to solve the IPC problem with a modified pipeline. We evaluated NORCS mainly from the viewpoint of microarchitecture in the original article, and showed that NORCS maintains almost the same IPC as conventional register files. Researchers in NVIDIA adopted the same idea for their GPUs. However, the evaluation was not sufficient from the viewpoint of LSI design. In the original article, we used CACTI to evaluate the area and energy consumption. CACTI is a design space exploration tool for cache design, and adopts some rough approximations. Therefore, this paper shows design of NORCS with FreePDK45, an open source process design kit for 45nm technology. We performed manual layout of the memory cells and arrays of NORCS, and executed SPICE simulation with RC parasitics extracted from the layout. The results show that, from a full-port register file, an 8-entry NORCS achieves a 75.2% and 48.2% reduction in area and energy consumption, respectively. The results also include the latency which we did not present in our original article. The latencies of critical path is 307ps and 318ps for an 8-entry NORCS and a conventional multiported register file, respectively, when the same two cycles are allocated to register file read.

This work reports a novel power-rail electrostatic discharge (ESD) clamp circuit with parasitic bipolar-junction-transistor (BJT) and channel parallel shunt paths. The parallel shunt paths are formed by delivering a tiny ratio of drain voltage to the gate terminal of the clamp device in ESD events. Under such a mechanism, the proposed circuit achieves enhanced robustness over those of both gate-grounded NMOS (ggNMOS) and the referenced gate-coupled NMOS (gcNMOS). Besides, the proposed circuit also achieves improved fast power-up immunity over that of the referenced gcNMOS. All investigated designs are fabricated in a 65-nm CMOS process. Transmission-line-pulsing (TLP) and human-body-model (HBM) test results have both confirmed the performance enhancements of the proposed circuit. Finally, the validity of the achieved performance enhancements on other trigger circuits is essentially revealed in this work.

The major task in compact modeling for high power devices is to predict the switching waveform accurately because it determines the energy loss of circuits. Device capacitance mainly determines the switching characteristics, which makes accurate capacitance modeling inevitable. This paper presents a newly developed compact model HiSIM-GaN [Hiroshima University STARC IGFET Model for Gallium-Nitride-based High Electron Mobility Transistors (GaN-HEMTs)], where the focus is given on the accurate modeling of the field-plate (FP), which is introduced to delocalize the electric-field peak that occurs at the electrode edge. We demonstrate that the proposed model reproduces capacitance measurements of a GaN-HEMT accurately without fitting parameters. Furthermore, the influence of the field plate on the studied circuit performance is analyzed.

Superconducting Transition edge sensor (TES) coupled with a heavy metal absorber is a promising microcalorimeter for Gamma-ray (γ-ray) spectroscopy with ultra-high energy resolution and high detection efficiency. It is very useful for the non-destructed inspection of the nuclide materials. High resolving power of γ-ray peaks can precisely identify multiple nuclides such as Plutonium (Pu) and Actinides with high efficiency and safety. For this purpose, we have developed the TES coupled with a tin absorber. We suggest the new device structure using the gold bump post which connects a tin absorber to the thermometer of the superconducting Ir/Au bilayer. High thermal conductivity of the gold bump post realized strong thermal coupling between the thermometer and the γ-ray absorber, and it brought the benefit of large pulse height and fast decay time. Our TES achieved the good energy resolution of 84 eV FWHM at 59.5 keV. Using this TES device, we also succeeded to demonstrate the nuclear material measurements. In the measurement of a Pu sample, we detected the sharp γ-ray peaks from 239Pu and 240Pu, and of a Fission Products (FP) sample, we observed fluorescence X-ray peaks emitted by the elements contained in FP. The TES could resolve the fine structures of each fluorescence X-ray line like Kα1 and Kα2. In addition to that, we developed the TES coupled with tantalum absorber, which is expected to have higher absorption efficiency for γ-rays. This device reported the best energy resolution of 465 eV at 662 keV.

We proposed to apply compressed sensing to realize information sharing of link quality for wireless mesh networks (WMNs) with grid topology. In this paper, we extend the link quality sharing method to be applied for WMNs with arbitrary topology. For arbitrary topology WMNs, we introduce a link quality matrix and a matrix formula for compressed sensing. By employing a diffusion wavelets basis, the link quality matrix is converted to its sparse equivalent. Based on the sparse matrix, information sharing is achieved by compressed sensing. In addition, we propose compressed transmission for arbitrary topology WMNs, in which only the compressed link quality information is transmitted. Experiments and simulations clarify that the proposed methods can reduce the amount of data transmitted for information sharing and maintain the quality of the shared information.