High Efficiency Video Coding (HEVC) has a better coding efficiency comparing with H.264/AVC. However, performance enhancement results in increased computational complexity which is mainly brought by the quadtree based coding tree unit (CTU). In this paper, an early termination algorithm based on AdaBoost classifier for coding unit (CU) is proposed to accelerate the process of searching the best partition for CTU. Experiment results indicate that our method can save 39% computational complexity on average at the cost of increasing Bjontegaard-Delta rate (BD-rate) by 0.18.

This paper investigates the usefulness of a new priority list for two-processor scheduling problem of program nets. Firstly, we discuss the weakness of a previously proposed priority list and then introduce a new priority list. Through simulation experiment we show that the new priority list is better than the previous one and can generate the same length of schedules as GA scheduling, which implies the new priority list can generate approximately optimal schedules.

This paper proposed a novel platform for sensor nodes to resolve the energy and latency challenges. It consists of a processor, an adaptive compressing module and several compression accelerators. We completed the proposed chip in a 0.18µm HJTC CMOS technology. Compared to the software-based solution, the hardware-assisted compression reduces over 98% energy and 212% latency. Besides, we balanced the energy and latency metric using an adaptive module. According to the scheduling algorithm, the module tunes the state of the compression accelerator, as well as the sampling frequency of the online sensor. For example, given a 9µs constraint for a 1-byte operation, it reduces 34% latency while the energy overheads are less than 5%.

This paper presents a quadrature injection locked frequency divider (ILFD) employing tunable active inductors (TAIs), which are used is to extend the locking range and to reduce die area. The CMOS ILFD is based on a new quadrature voltage-controlled oscillator (VCO) with cross-coupled switching pairs and TAI-C tanks, and was fabricated in the 0.18-µm 1P6M CMOS technology. The divide-by-2 LC-tank ILFD is performed by adding injection MOSFETs between the differential outputs of the VCO. Measurement results show that at the supply voltage of 1.8 V, the divider free-running frequency is tunable from 1.34 GHz to 3.07 GHz, and at the incident power of 0 dBm the locking range is about 6 GHz (137%), from the incident frequency 1.37 GHz to 7.38 GHz. The core power consumption is 22.8 mW. The die area is 0.630.55 mm2.

Reconfigurable intelligent surface (RIS) has the capability of boosting system performance by manipulating the wireless propagation environment. This paper investigates a downlink RIS-aided non-orthogonal multiple access (NOMA) system, where a RIS is deployed to enhance physical-layer security (PLS) in the presence of an eavesdropper. In order to improve the main link's security, the RIS is deployed between the source and the users, in which a reflecting element separation scheme is developed to aid data transmission of both the cell-center and the cell-edge users. Additionally, the closed-form expressions of secrecy outage probability (SOP) are derived for the proposed RIS-aided NOMA scheme. To obtain more deep insights on the derived results, the asymptotic performance of the derived SOP is analyzed. Moreover, the secrecy diversity order is derived according to the asymptotic approximation in the high signal-to-noise ratio (SNR) and main-to-eavesdropper ratio (MER) regime. Furthermore, based on the derived results, the power allocation coefficient and number of elements are optimized to minimize the system SOP. Simulations demonstrate that the theoretical results match well with the simulation results and the SOP of the proposed scheme is clearly less than that of the conventional orthogonal multiple access (OMA) scheme obviously.

Cooperative wireless communication is a communication mechanism to attain diversity through virtual antenna array that is formed by sharing resources among different users. Different strategies of resource utilization such as amplify-and-forward (AF) and decode-and-forward (DF) already exist in cooperative networks. Although the implementation of these strategies is simple, their utilization of the channel state information (CSI) is generally poor. As a result, the outage and bit error rate (BER) performances need much more improvement in order to satisfy the upcoming high data rate demands. For that to happen the spectral efficiency supported by a wireless system at a very low outage probability should be increased. In this paper a new approach, based on the previously existing ones, called CSI directed estimate and forward (CDEF) with a reduced estimation domain is proposed. A closed form solution for the optimal signal estimation at the relay using minimum mean square error (MMSE) as well as a possible set reduction of the estimation domain is given. It will be shown that this new strategy attains better symbol error rate (SER) and outage performance than AF or DF when the source relay link is comparatively better than the relay destination link. Simulation results also show that it has got better spectral efficiency at low outage probability for a given signal to noise ratio (SNR) as well as for a fixed outage probability in any operating SNR range.

The calculation of cross-correlation between a sequence with good autocorrelation and its decimated sequence is an interesting problem in the field of sequence design. In this letter, we consider a class of ternary sequences with perfect autocorrelation, proposed by Shedd and Sarwate (IEEE Trans. Inf. Theory, 1979, DOI: 10.1109/TIT.1979.1055998), which is generated based on the cross-correlation between m-sequence and its d-decimation sequence. We calculate the cross-correlation distribution between a certain pair of such ternary perfect sequences and show that the cross-correlation takes three different values.

Utilization data (a kind of incomplete data) is defined as the fraction of a fixed period in which the system is busy. In computer systems, utilization data is very common and easily observable, such as CPU utilization. Unlike inter-arrival times and waiting times, it is more significant to consider the parameter estimation of transaction-based systems with utilization data. In our previous work [7], a novel parameter estimation method using utilization data for an Mt/M/1/K queueing system was presented to estimate the parameters of a non-homogeneous Poisson process (NHPP). Since NHPP is classified as a simple counting process, it may not fit actual arrival streams very well. As a generalization of NHPP, Markovian arrival process (MAP) takes account of the dependency between consecutive arrivals and is often used to model complex, bursty, and correlated traffic streams. In this paper, we concentrate on the parameter estimation of an MAP/M/1/K queueing system using utilization data. In particular, the parameters are estimated by using maximum likelihood estimation (MLE) method. Numerical experiments on real utilization data validate the proposed approach and evaluate the effective traffic intensity of the arrival stream of MAP/M/1/K queueing system. Besides, three kinds of utilization datasets are created from a simulation to assess the effects of observed time intervals on both estimation accuracy and computational cost. The numerical results show that MAP-based approach outperforms the exiting method in terms of both the estimation accuracy and computational cost.

A dual band 0.18 µm CMOS LC-tank injection locked frequency divider (ILFD) is proposed. The ILFD circuit is realized with a cross-coupled pMOS LC-tank oscillator with an inductor switch for frequency band selection. The self-oscillating VCO is injection-locked by nth-harmonic input to obtain the division factor of n. The division ratio of 1, 2, and 3 has been found for the proposed ILFD. Measurement results show that at the supply voltage of 1.1 V, the free-running frequency is from 2.28(3.09) GHz to 2.78(3.72) GHz for the low- (high-) frequency band. The power consumption of the ILFD core is 3.7 mW (6.2 mW) at low (high) band. The total area including the output buffer and the pads is 0.8410.764 mm2.

The ordered successive interference cancellation (OSIC) detector based on the minimum mean square error (MMSE) criterion has been proved to be a low-complexity detector with efficient bit error rate (BER) performance. As the well-known MMSE-Based OSIC detector, the MMSE-Based vertical Bell Laboratories Layered Space-Time (VBLAST) detector, whose computational complexity is cubic, can not attain the minimum BER performance. Some approaches to reducing the BER of the MMSE-Based VBLAST detector have been contributed, however these improvements have large computational complexity. In this paper, a low complexity MMSE-Based OSIC detector called MMSE-OBEP (ordering based on error probability) is proposed to improve the BER performance of the previous MMSE-Based OSIC detectors, and it has cubic complexity. The proposed detector derives the near-exact error probability of the symbols in the MMSE-Based OSIC detector, thus giving priority to detect the symbol with the smallest error probability can minimize the error propagation in the MMSE-Based OSIC detector and enhance the BER performance. We show that, although the computational complexity of the proposed detector is cubic, it can provide better BER performance than the previous MMSE-Based OSIC detector.

This paper presents a joint linear processing scheme for two-hop and half-duplex distributed amplify-and-forward (AF) relaying networks with one source, one destination and multiple relays, each having multiple antennas. By using the minimum mean-square error (MMSE) criterion and the Wiener filter principle, the joint relay and destination design with perfect channel state information (CSI) is first formulated as an optimization problem with respect to the relay precoding matrix under the constraint of a total relay transmit power. The constrained optimization with an objective to design the relay block-diagonal matrix is then simplified to an equivalent problem with scalar optimization variables. Next, it is revealed that the scalar-version optimization is convex when the total relay power or the second-hop SNR (signal to noise ratio) is above a certain threshold. The underlying optimization problem, which is non-convex in general, is solved by complementary geometric programming (CGP). The proposed joint relay and destination design with perfect CSI is also extended for practical systems where only the channel mean and covariance matrix are available, leading to a robust processing scheme. Finally, Monte Carlo simulations are undertaken to demonstrate the superior MSE (mean-square error) and SER (symbol error rate) performances of the proposed scheme over the existing relaying method in the case of relatively large second-hop SNR.

This paper proposes a method to incorporate the concept of time for the inclusion of dynamics of signaling pathway in a Petri net model, i.e., to use timed Petri nets. Incorporation of delay times into a Petri net model makes it possible to conduct quantitative evaluation on a target signaling pathway. However, experimental data describing detailed reactions are not available in most cases. An algorithm given in this paper determines delay times of a timed Petri net only from the structural information of it. The suitability of this algorithm has been confirmed by the results of an application to the IL-1 signaling pathway.

In this study, we propose a method to estimate body composition-related health indicators (e.g., ratio of body fat, body water, and muscle, etc.) using video-based gait analysis. This method is more efficient than individual measurement using a conventional body composition meter. Specifically, we designed a deep-learning framework with a convolutional neural network (CNN), where the input is a gait energy image (GEI) and the output consists of the health indicators. Although a vast amount of training data is typically required to train network parameters, it is unfeasible to collect sufficient ground-truth data, i.e., pairs consisting of the gait video and the health indicators measured using a body composition meter for each subject. We therefore use a two-step approach to exploit an auxiliary gait dataset that contains a large number of subjects but lacks the ground-truth health indicators. At the first step, we pre-train a backbone network using the auxiliary dataset to output gait primitives such as arm swing, stride, the degree of stoop, and the body width — considered to be relevant to the health indicators. At the second step, we add some layers to the backbone network and fine-tune the entire network to output the health indicators even with a limited number of ground-truth data points of the health indicators. Experimental results show that the proposed method outperforms the other methods when training from scratch as well as when using an auto-encoder-based pre-training and fine-tuning approach; it achieves relatively high estimation accuracy for the body composition-related health indicators except for body fat-relevant ones.

This paper proposes a region-of-interest (ROI) based H.264 encoder and the VLSI architecture of the ROI detection algorithm. In ROI based video coding system, pre-processing unit to detect ROI should only introduce low computational complexity overhead due to the low power requirement. The Macroblocks (MBs) in ROIs are detected sequentially in the same order of H.264 encoding to satisfy the MB level pipelining of ROI detector and H.264 encoder. ROI detection is performed in a novel estimation-and-verification process with an ROI contour template. Proposed architecture can be configured to detect either single ROI or multiple ROIs in each frame and the throughput of single detection mode is 5.5 times of multiple detection mode. 98.01% and 97.89% of MBs in ROIs can be detected in single and multiple detection modes respectively. Hardware cost of proposed architecture is only 4.68 k gates. Detection speed is 753 fps for CIF format video at the operation frequency of 200 MHz in multiple detection mode with power consumption of 0.47 mW. Compared with previous fast ROI detection algorithms for video coding application, the proposed architecture obtains more accurate and smaller ROI. Therefore, more efficient ROI based computation complexity and compression efficiency optimization can be implemented in H.264 encoder.

This paper proposes a new family of space-time block codes whose transmission rate is 1 symbol per channel use. The proposed space-time codes can achieve full transmit diversity with larger coding gain for the constellation carved from the scaled complex integer ring κZ[i]. It is confirmed that the performances of the proposed space-time codes are superior to the existing space-time block codes by our simulation results.

High-definition (HD) videos become more and more popular on portable devices these years. Due to the resolution mismatch between the HD video sources and the relative low-resolution screens of portable devices, the HD videos are usually fully decoded and then down-sampled (FDDS) for the displays, which not only increase the cost of both computational power and memory bandwidth, but also lose the details of video contents. In this paper, an encoder-unconstrained partial decoding scheme for H.264/AVC is presented to solve the problem by only decoding the object of interest (OOI) related region, which is defined by users. A simplified compression domain tracking method is utilized to ensure that the OOI locates in the center of the display area. The decoded partial area (DPA) adaptation, the reference block relocation (RBR) and co-located temporal Intra prediction (CTIP) methods are proposed to improve the visual quality for the DPA with low complexity. The simulation results show that the proposed partial decoding scheme provides an average of 50.16% decoding time reduction comparing to the fully decoding process. The displayed region also presents the original HD granularity of OOI. The proposed partial decoding scheme is especially useful for displaying HD video on the devices of which the battery life is a crucial factor.

In this letter, we investigate the secure transmission in radio frequency (RF) powered two-hop untrusted relay networks, where the source node and untrusted relay are both wireless powered by an RF power supplier. Specifically, considering the non-linear energy-harvesting (EH) model, the two-process communication protocol is proposed. The secrecy rate is maximized by jointly designing the beamforming vector at source and beamforming matrix at relay, under the constraints of transmit power at RF power supplier and destination. The secrecy rate maximization (SRM) is non-convex, hence we propose an alternative optimization (AO) based iterative algorithm. Numerical results demonstrate that the proposed scheme can significantly increase the secrecy rate compared to the baseline schemes.

This paper considers the power allocation (PA) problem for three-node decode-and-forward (DF) relay communication systems, where the aggregate transmit power constraint is imposed on the source and the relay and the optimization target is to maximize the system's instantaneous information rate. Since the relay is equipped with multiple antennas, the receiver and transmitter beamforming strategies are generally adopted. In this paper, we start by proposing a closed-form solution for the frequency-flat (FF) fading environment, then give a bisection algorithm with low complexity to obtain an optimal solution for the frequency-selective (FS) fading scenario. Finally, simulations validate the proposed methods.

We propose to use clustered interference alignment for the situation where the backhaul link capacity is limited and the base station is cache-enabled given MIMO interference channels, when the number of Tx-Rx pairs exceeds the feasibility constraint of interference alignment. We optimize clustering with the soft cluster size constraint algorithm by adding a cluster size balancing process. In addition, the CSI overhead is quantified as a system performance indicator along with the average throughput. Simulation results show that cluster size balancing algorithm generates clusters that are more balanced as well as attaining higher long-term throughput than the soft cluster size constraint algorithm. The long-term throughput is further improved under high SNR by reallocating the capacity of the backhaul links based on the clustering results.

Petri nets have recently become widely accepted as a description method for biological pathways by researchers in computer science as well as those in biology. This paper gives an overview of Petri net formalisms to describe biological pathways and discusses their use in modelings and simulations for the systematic understandings of biological pathways. After reviewing the use of various types of Petri nets for the biological pathway modelings, we showed the examples that analyze fundamental properties of biological pathways using T-invariant, P-invariant, siphon, and trap. Applications of hybrid Petri nets for producing new biological hypotheses through simulations are also illustrated.