In this letter, a novel adaptive detector that combines DFE and QRD-M is proposed for MIMO-OFDM system. QR decomposition (QRD) is commonly used in many MIMO detection algorithms. In particular, sorted QR decomposition (SQRD) is an advanced algorithm that improves MIMO detection performance. The proposed detector uses SQRD to achieve better performance. To reduce the computational complexity, the received layers of each subcarrier are ordered by using the post SNR and are detected by DFE and QRD-M detector based on the order. Therefore, the proposed detector structure is varied according to the channel state. In other words, the proposed detector achieves a good tradeoff between complexity and performance. A simulation confirms the substantial performance improvements of the proposed adaptive detector with only slightly greater complexity than the conventional detector.

This paper examines two-pass authenticated key exchange (AKE) protocols that are secure without the NAXOS technique under the gap Diffie-Hellman assumption in the random oracle model: FHMQV [18], KFU1 [21], SMEN- [13], and UP [17]. We introduce two protocol, biclique DH protocol and multiplied biclique DH protocol, to analyze the subject protocols, and show that the subject protocols use the multiplied biclique DH protocol as internal protocols. The biclique DH protocol is secure, however, the multiplied biclique DH protocol is insecure. We show the relations between the subject protocols from the viewpoint of how they overcome the insecurity of the multiplied biclique DH protocol: FHMQV virtually executes two multiplied biclique DH protocols in sequence with the same ephemeral key on two randomized static keys. KFU1 executes two multiplied biclique DH protocols in parallel with the same ephemeral key. UP is a version of KFU1 in which one of the static public keys is generated with a random oracle. SMEN- can be thought of as a combined execution of two multiplied biclique DH protocols. In addition, this paper provides ways to characterize the AKE protocols and defines two parameters: one consists of the number of static keys, the number of ephemeral keys, and the number of shared secrets, and the other is defined as the total sum of these numbers. When an AKE protocol is constructed based on some group, these two parameters indicate the number of elements in the group, i.e., they are related to the sizes of the storage and communication data.

H.264 video codec system requires big capacity and high bandwidth of Frame Store (FS) for buffering reference frames. The up-to-date three dimensional (3D) stacked Phase change Random Access Memory (PRAM) is the promising approach for on-chip caching the reference signals, as 3D stacking offers high memory bandwidth, while PRAM possesses the advantages in terms of high density and low leakage power. However, the write endurance problem, that is a PRAM cell can only tolerant limited number of write operations, becomes the main barrier in practical applications. This paper studies the wear reduction techniques of PRAM based FS in H.264 codec system. On the basis of rate-distortion theory, the content oriented selective writing mechanisms are proposed to reduce bit updates in the reference frame buffers. With the proposed control parameter a, our methods make the quantitative trade off between the quality degradation and the PRAM lifetime prolongation. Specifically, taking a in the range of [0.2,2], experimental results demonstrate that, our methods averagely save 29.9–35.5% bit-wise write operations and reduce 52–57% power, at the cost of 12.95–20.57% BDBR bit-rate increase accordingly.

A wireless emergency communication network with a fixed allocation of spectrum resources cannot meet the tremendous demand for spectrum access when a crisis occurs. It is necessary to develop an effective spectrum access scheme to improve the performance of emergency communication systems. In this paper, we study a new emergency communication system combines cognitive radio technology and an emergency communication network. Emergency users can utility resources in a general network when traffic becomes congested in an emergency network. Non-reciprocal spectrum access scheme (NRA) and reciprocal spectrum access scheme (RA) for two heterogeneous cognitive networks, namely emergency network and general network are proposed to compare with traditional spectrum access scheme (TA). User behavior with each scheme is modeled by continuous-time Markov chains. Moreover, the blocking and dropping probabilities of users in two heterogeneous cognitive networks are derived as the performance metrics. In addition, the throughput and the spectrum utilization rate of the system are evaluated. Finally, we compare the performance of three dynamic spectrum access schemes. The simulation results show that the RA scheme is an effective scheme to enhance the performance of emergency systems.

Many problems can be formulated as maximum clique problems. Hence, it is highly important to develop algorithms that can find a maximum clique very fast in practice. We propose new approximate coloring and other related techniques which markedly improve the run time of the branch-and-bound algorithm MCR (J. Global Optim., 37, pp.95–111, 2007), previously shown to be the fastest maximum-clique-finding algorithm for a large number of graphs. The algorithm obtained by introducing these new techniques in MCR is named MCS. It is shown that MCS is successful in reducing the search space quite efficiently with low overhead. Extensive computational experiments confirm the superiority of MCS over MCR and other existing algorithms. It is faster than the other algorithms by orders of magnitude for several graphs. In particular, it is faster than MCR for difficult graphs of very high density and for very large and sparse graphs, even though MCS is not designed for any particular type of graph. MCS can be faster than MCR by a factor of more than 100,000 for some extremely dense random graphs. This paper demonstrates in detail the effectiveness of each new techniques in MCS, as well as the overall contribution.

Recent attempts to directly combine CMOS pixel readout chips with modern gas detectors open the possibility to fully take advantage of gas detectors. Those conventional readout LSIs designed for hybrid semiconductor detectors show some issues when applied to gas detectors. Several new proposed readout LSIs can improve the time and the charge measurement precision. However, the widely used basic charge sensitive amplifier (CSA) has an almost fixed dynamic range. There is a trade-off between the charge measurement resolution and the detectable input charge range. This paper presents a method to apply the folding integration technique to a basic CSA. As a result, the detectable input charge dynamic range is expanded while maintaining all the key merits of a basic CSA. Although folding integration technique has already been successfully applied in CMOS image sensors, the working conditions and the signal characteristics are quite different for pixel readout LSIs for gas particle detectors. The related issues of the folding CSA for pixel readout LSIs, including the charge error due to finite gain of the preamplifier, the calibration method of charge error, and the dynamic range expanding efficiency, are addressed and analyzed. As a design example, this paper also demonstrates the application of the folding integration technique to a Qpix readout chip. This improves the charge measurement resolution and expands the detectable input dynamic range while maintaining all the key features. Calculations with SPICE simulations show that the dynamic range can be improved by 12 dB while the charge measurement resolution is improved by 10 times. The charge error during the folding operation can be corrected to less than 0.5%, which is sufficient for large input charge measurement.

Super resolution (SR) reconstruction is the process of fusing a sequence of low-resolution images into one high-resolution image. Many researchers have introduced various SR reconstruction methods. However, these traditional methods are limited in the extent to which they allow recovery of high-frequency information. Moreover, due to the self-similarity of face images, most of the facial SR algorithms are machine learning based. In this paper, we introduce a facial SR algorithm that combines learning-based and regularized SR image reconstruction algorithms. Our conception involves two main ideas. First, we employ separated frequency components to reconstruct high-resolution images. In addition, we separate the region of the training face image. These approaches can help to recover high-frequency information. In our experiments, we demonstrate the effectiveness of these ideas.

We have seen a rapid increase in mobile data traffic in cellular networks, especially in densely populated areas called “hotspots.” In order to deal with this trend, heterogeneous networks (HetNet) are attracting much attention as a method of effectively accommodating such traffic increases using the Long Term Evolution (LTE)-Advanced system in the 3rd Generation Partnership Project (3GPP). This paper first presents an overview of HetNet, where various wireless nodes can be deployed over the coverage area formed by macro base stations (BSs). Next, various evaluation results are provided for HetNet, where pico BSs (“Pico-BSs”) are deployed over the coverage area of macro BSs (“Macro-BSs”). Then, this paper presents a comprehensive analysis, not only of the effect of overlaying Pico-BSs but also a detailed analyses of the techniques called “cell range expansion (CRE)” and “enhanced inter-cell interference coordination (eICIC)” for facilitating the offloading of user terminals (UEs) from Macro-BSs to Pico-BSs and mitigating interference, respectively, for both downlink and uplink. Noteworthy outcomes found through the comprehensive study are that CRE provides throughput improvements for uplinks, especially for UE connected to Pico-BSs. In addition, this paper demonstrates that CRE contributes to improving downlink throughput especially for low traffic loads. The outcome regarding eICIC is that eICIC provides improvements in total throughput, in spite of the fact that eICIC causes unfairness between UE connected to the Pico-BSs and those with Macro-BSs.

Adverse weather, such as rain or snow, can cause difficulties in the processing of video streams. Because the appearance of raindrops can affect the performance of human tracking and reduce the efficiency of video compression, the detection and removal of rain is a challenging problem in outdoor surveillance systems. In this paper, we propose a new algorithm for rain detection and removal based on both spatial and wavelet domain features. Our system involves fewer frames during detection and removal, and is robust to moving objects in the rain. Experimental results demonstrate that the proposed algorithm outperforms existing approaches in terms of subjective and objective quality.

The self-improvement of static random access memory (SRAM) cell stability by post-fabrication high-voltage stress is experimentally demonstrated and its mechanism is analyzed using 4k device-matrix-array (DMA) SRAM test element group (TEG). It is shown that the stability of unbalance cells is automatically improved by merely applying stress voltage to the VDD terminal of SRAM. It is newly found that | VTH| of the OFF-state pFETs in the SRAM cell is selectively lowered which improves the cell stability and contributes to the self-improvement.

The response of differential pairs against low-frequency substrate voltage variation is captured in a combined transistor and substrate network models. The model generation is regularized for variation of transistor geometries including channel sizes, fingering and folding, and the placements of guard bands. The expansion of the models for full-chip substrate noise analysis is also discussed. The substrate sensitivity of differential pairs is evaluated through on-chip substrate coupling measurements in a 90 nm CMOS technology with more than 64 different geometries and operating conditions. The trends and strengths of substrate sensitivity are shown to be well consistent between simulation and measurements.

This letter proposes an iterative learning control with advanced output data (ADILC) scheme using an estimation of the impulse response for non-minimum phase (NMP) systems, whose model is unknown, except for the relative degree and the number of NMP zeros. Although the ADILC has a simple learning structure that can be applied to both minimum phase and NMP systems, at least a partial model should be known in order to apply ADILC. Considering this fact, in this letter, we propose a new ADILC method based on the estimation of the impulse response for NMP systems whose model is unknown. An estimation method for the learning matrix and an ADILC scheme are presented for NMP systems.

As the successive video compression standard of H.264/AVC, High Efficiency Video Codec (HEVC) will play an important role in video coding area. In the deblocking filter part, HEVC inherits the basic property of H.264/AVC and gives some new features. Based on this variation, this paper introduces a novel dual-mode deblocking filter architecture which could support both of the HEVC and H.264/AVC standards. For HEVC standard, the proposed symmetric unified-cross unit (SUCU) based filtering scheme greatly reduces the design complexity. As a result, processing a 1616 block needs 24 clock cycles. For H.264/AVC standard, it takes 48 clock cycles for a 1616 macro-block (MB). In synthesis result, the proposed architecture occupies 41.6k equivalent gate count at frequency of 200 MHz in SMIC 65 nm library, which could satisfy the throughput requirement of super hi-vision (SHV) on 60 fps. With filter reusing scheme, the universal design for the two standards saves 30% gate counts than the dedicated ones in filter part. In addition, the total power consumption could be reduced by 57.2% with skipping mode when the edges need not be filtered.

This paper describes algorithms for generating low intermodulation-distortion (IMD) two-tone sinewaves, for such as communication application ADC testing, using an arbitrary waveform generator (AWG) or a multi-bit ΣΔ DAC inside an SoC. The nonlinearity of the DAC generates distortion components, and we propose here eight methods to precompensate for the IMD using DSP algorithms and produce low-IMD two-tone signals. Theoretical analysis, simulation, and experimental results all demonstrate the effectiveness of our approach.

The Internet was designed for academic use more than 40 years ago. After having been used commercially, many unpredictable requirements have emerged, including mobility, security and content distribution. In addition, the Internet has become so ossified that fulfilling new requirements is difficult. Instead of developing ad-hoc solutions, re-designing clean-slate Internet architectures has become a key research challenge in networking communities. This survey paper addresses key research issues and then introduces ongoing research projects from Japan, the United States and the European Union.

This paper proposes a low power tone recognition suitable for automatic tonal speech recognizer (ATSR). The tone recognition estimates fundamental frequency (F0) only from vowels by using a new magnitude difference function (MDF), called vowel-MDF. Accordingly, the number of operations is considerably reduced. In order to apply the tone recognition in portable electronic equipment, the tone recognition is designed using parallel and pipeline architecture. Due to the pipeline and parallel computations, the architecture achieves high throughput and consumes low power. In addition, the architecture is able to reduce the number of input frames depending on vowels, making it more adaptable depending on the maximum number of frames. The proposed architecture is evaluated with words selected from voice activation for GPS systems, phone dialing options, and words having the same phoneme but different tones. In comparison with the autocorrelation method, the experimental results show 35.7% reduction in power consumption and 27.1% improvement of tone recognition accuracy (110 words comprising 187 syllables). In comparison with ATSR without the tone recognition, the speech recognition accuracy indicates 25.0% improvement of ATSR with tone recogntion (2,250 training data and 45 testing words).

This paper describes the design of an interpolated pipeline analog-to-digital converter (ADC). By introducing the interpolation technique into the conventional pipeline topology, it becomes possible to realize a more than 10-bits resolution and several hundred MS/s ADC using low-gain open-loop amplifiers without any multiplying digital-to-analog converter (MDAC) calibration. In this paper, linearity requirement of the amplifier is analyzed with the relation of reference range and stage resolution first. Noise characteristic is also discussed with amplifier's noise bandwidth and load capacitance. After that, sampling speed and SNR characteristic are examined with various amplifier currents. Next, the resolution optimization of the pipeline stage is discussed based on the power consumption. Through the analysis, reasonable parameters for the amplifier can be defined, such as transconductance, source degeneration resistance and load capacitance. Also, optimized operating speed and stage resolution for interpolated pipelined ADC is shown. The analysis in this paper is valuable to both the design of interpolated pipeline ADCs and other circuits which incorporate interpolation and amplifiers.

Diffusion-weighted (DW)-functional magnetic resonance imaging (fMRI) is a recently reported technique for measuring neural activities by using diffusion-weighted imaging (DWI). DW-fMRI is based on the property that cortical cells swell when the brain is activated. This approach can be used to observe changes in water diffusion around cortical cells. The spatial and temporal resolutions of DW-fMRI are superior to those of blood-oxygenation-level-dependent (BOLD)-fMRI. To investigate how the DWI signal intensities change in DW-fMRI measurement, we carried out Monte Carlo simulations to evaluate the intensities before and after cell swelling. In the simulations, we modeled cortical cells as two compartments by considering differences between the intracellular and the extracellular regions. Simulation results suggested that DWI signal intensities increase after cell swelling because of an increase in the intracellular volume ratio. The simulation model with two compartments, which respectively represent the intracellular and the extracellular regions, shows that the differences in the DWI signal intensities depend on the ratio of the intracellular and the extracellular volumes. We also investigated the MPG parameters, b-value, and separation time dependences on the percent signal changes in DW-fMRI and obtained useful results for DW-fMRI measurements.

In this paper, we propose a pedestrian detection algorithm based on both appearance and motion features to achieve high detection accuracy when applied to complex scenes. Here, a pedestrian's appearance is described by a histogram of oriented spatial gradients, and his/her motion is represented by another histogram of temporal gradients computed from successive frames. Since pedestrians typically exhibit not only their human shapes but also unique human movements generated by their arms and legs, the proposed algorithm is particularly powerful in discriminating a pedestrian from a cluttered situation, where some background regions may appear to have human shapes, but their motion differs from human movement. Unlike the algorithm based on a co-occurrence feature descriptor where significant generalization errors may arise owing to the lack of extensive training samples to cover feature variations, the proposed algorithm describes the shape and motion as unique features. These features enable us to train a pedestrian detector in the form of a spatio-temporal histogram of oriented gradients using the AdaBoost algorithm with a relatively small training dataset, while still achieving excellent detection performance. We have confirmed the effectiveness of the proposed algorithm through experiments on several public datasets.

This paper presents a digitally error-corrected pipeline analog-to-digital converter (ADC) using linearization of incomplete settling errors. A pre-charging technique is used for residue amplifiers in order to reduce the incomplete settling error itself and linearize the input signal dependency of the incomplete settling error. A technique with charge redistribution of divided capacitors is proposed for pre-charging capacitors without any additional reference sources. This linearized settling error is corrected by a first-order error approximation in digital domain with feasible complexity and cost. Simulation results show that the ADC achieves SNDR of 70 dB, SFDR of 79 dB at nyquist input frequency in a 65 nm CMOS process under 1.2 V power supply voltage for 1.2 Vp-p input signal swing. The estimated power consumption of the 12b 200 MS/s pipeline ADC using the proposed digital error correction of incomplete settling errors is 7.6 mW with a small FOM of 22 fJ/conv-step.