The newest video coding standard called H.264 provides considerable performance improvement over a wide range of bit rates and video resolutions compared to previous standards. However, these features result in an extraordinary increase in encoder complexity, mainly regarding to mode decision and multiple reference frame motion estimation (ME). This letter presents two algorithms to reduce the computational complexity caused by motion estimation. The adaptive search range decision method determines the search range size according to the motion vector predictor dynamically and the early termination scheme defines a criterion to early terminate the search processing for multiple reference frames. Experimental results show that the proposed algorithms provide significant improvement of coding speed with negligible objective quality degradation compared to the fast motion estimation algorithms adopted by reference software.

We give a tutorial on high-level synthesis of VLSI. The evolution of digital system synthesis techniques and the need for higher level design automation tools are first discussed. We then point out essential issues to the successful development and acceptance by the designers of a high-level synthesis system. Techniques that have been proposed for various subtasks of high-level synthesis are surveyed. Possible applications of the high level synthesis in area other than chip design are forecast. Finally, we point out several directions for possible future research.

We have proposed integrated waveguide structure suitable for mid- and near- infrared light propagation using Si and CaF2 heterostructures on Si substrate. Using a fabrication process based on etching, lithography and crystal growth techniques, we have formed a slab-waveguide structure with a current injection mechanism on a SOI substrate, which would be a key component for Si/CaF2 quantum cascade lasers and other optical integrated systems. The propagation of light at a wavelength of 1.55 µm through a Si/CaF2 waveguide structure have been demonstrated for the first time using a structure with a Si/CaF2 multilayered core with 610-nm-thick, waveguide width of 970 nm, which satisfies single-mode condition in the horizontal direction within a tolerance of fabrication accuracy. The waveguide loss for transverse magnetic (TM) mode has been evaluated to be 51.4 cm-1. The cause of the loss was discussed by estimating the edge roughness scattering and free carrier absorption, which suggests further reduction of the loss would be possible.

The construction of frequency hopping sequences with good Hamming correlation is the foundation of research in frequency hopping communication. In this letter, classes of optimal low hit zone frequency hopping sequence set are constructed based on the interleaving technology. The results of the study show that the sequence set with large family size is optimal for the Peng-Fan-Lee bound. And all the sequences in the set are inequivalent.

In cloud radio access networks (C-RANs) architecture, the Hybrid Automatic Repeat Request (HARQ) protocol imposes a strict limit on the latency between the baseband unit (BBU) pool and the remote radio head (RRH), which is a key challenge in the adoption of C-RANs. In this letter, we propose a joint edge caching and network coding strategy (ENC) in the C-RANs with multicast fronthaul to improve the performance of HARQ and thus achieve ultra-low latency in 5G cellular systems. We formulate the edge caching design as an optimization problem for maximizing caching utility so as to obtain the optimal caching time. Then, for real-time data flows with different latency constraints, we propose a scheduling policy based on network coding group (NCG) to maximize coding opportunities and thus improve the overall latency performance of multicast fronthaul transmission. We evaluate the performance of ENC by conducting simulation experiments based on NS-3. Numerical results show that ENC can efficiently reduce the delivery delay.

A novel mobile assignment method based on transmit power and cell load is proposed for WCDMA base station location planning. Experimental results show that, compared with the currently widely used mobile assignment method based on link attenuation, the proposed mobile assignment method is more reasonable and unnecessary base stations are reduced in the planning results.

This paper presents a fully digital modulation calibration technique for channel mismatch of TIADC at any frequency. By pre-inputting a test signal in TIADC, the mismatch errors are estimated and stored, and the stored values will be extracted for compensation when the input signal is at special frequency which can be detected by a threshold judgement module, thus solving the problem that the traditional modulation calibration algorithm cannot calibrate the signal at special frequency. Then, by adjusting the operation order among the error estimation coefficient, modulation function and input signal in the calibration loop, further, the order of correlation and modulation in the error estimation module, the complexity of the proposed calibration algorithm is greatly reduced and it will not increase with the number of channels of TIADC. What's more, the hardware consumption of filters in calibration algorithm is greatly reduced by introducing a CSD (Canonical Signed Digit) coding technique based on Horner's rule and sub-expression sharing. Applied to a four-channel 14bit 560MHz TIADC system, with input signal at 75.6MHz, the FPGA verification results show that, after calibration, the spurious-free dynamic range (SFDR) improves from 33.47dB to 99.81dB and signal-to-noise distortion ratio (SNDR) increases from 30.15dB to 81.89dB.

We have designed a near-infrared wavelength Si/CaF2 DFB quantum cascade laser and investigated the possibility of single-mode laser oscillation by analysis of the propagation mode, gain, scattering time of Si quantum well, and threshold current density. As the waveguide and resonator, a slab-type waveguide structure with a Si/CaF2 active layer sandwiched by SiO2 on a Si (111) substrate and a grating structure in an n-Si conducting layer were assumed. From the results of optical propagation mode analysis, by assuming a λ/4-shifted bragg waveguide structure, it was found that the single vertical and horizontal TM mode propagation is possible at the designed wavelength of 1.70µm. In addition, a design of the active layer is proposed and its current injection capability is roughly estimated to be 25.1kA/cm2, which is larger than required threshold current density of 1.4kA/cm2 calculated by combining analysis results of the scattering time, population inversion, gain of quantum cascade lasers, and coupling theory of a Bragg waveguide. The results strongly indicate the possibility of single-mode laser oscillation.

Pedestrian attribute recognition (PAR) aims to recognize a series of a person's semantic attributes, e.g., age, gender, which plays an important role in video surveillance. This paper proposes a multi-correlation graph convolutional network named MCGCN for PAR, which includes a semantic graph, visual graph, and synthesis graph. We construct a semantic graph by using attribute features with semantic constraints. A graph convolution is employed, based on prior knowledge of the dataset, to learn the semantic correlation. 2D features are projected onto visual graph nodes and each node corresponds to the feature region of each attribute group. Graph convolution is then utilized to learn regional correlation. The visual graph nodes are connected to the semantic graph nodes to form a synthesis graph. In the synthesis graph, regional and semantic correlation are embedded into each other through inter-graph edges, to guide each other's learning and to update the visual and semantic graph, thereby constructing semantic and regional correlation. On this basis, we use a better loss weighting strategy, the suit_polyloss, to address the imbalance of pedestrian attribute datasets. Experiments on three benchmark datasets show that the proposed approach achieves superior recognition performance compared to existing technologies, and achieves state-of-the-art performance.

Web Service Business Process Execution Language (BPEL) has become the de facto standard for developing instant service-oriented workflow applications in open environment. The correctness and reliability of BPEL processes have gained increasing concerns. However, the unique features (e.g., dead path elimination (DPE) semantics, parallelism, etc.) of BPEL language have raised enormous problems to it, especially in path feasibility analysis of BPEL processes. Path feasibility analysis of BPEL processes is the basis of BPEL testing, for it relates to the test case generation. Since BPEL processes support both parallelism and DPE semantics, existing techniques can't be directly applied to its path feasibility analysis. To address this problem, we present a novel technique to analyze the path feasibility for BPEL processes. First, to tackle unique features mentioned above, we transform a BPEL process into an intermediary model — BPEL control flow graph, which is proposed to abstract the execution flow of BPEL processes. Second, based on this abstraction, we symbolically encode every path of BPEL processes as some Satisfiability formulas. Finally, we solve these formulas with the help of Satisfiability Modulo Theory (SMT) solvers and the feasible paths of BPEL processes are obtained. We illustrate the applicability and feasibility of our technique through a case study.

In this paper, we investigate the maximum induced matching problem (MaxIM) on C5-free d-regular graphs. The previously known best approximation ratio for MaxIM on C5-free d-regular graphs is $left(rac{3d}{4}-rac{1}{8}+rac{3}{16d-8} ight)$. In this paper, we design a $left(rac{2d}{3}+rac{1}{3} ight)$-approximation algorithm, whose approximation ratio is strictly smaller/better than the previous one when d≥6.

An optimization model with maximum ratio combining (MRC) diversity soft handover is proposed for WCDMA base station location planning with heuristic algorithm, which can calculate the influence of MRC diversity soft handover directly in the process of base station location planning. Experimental results show that the proposed model can get better capacity and coverage performance in the planning results than the traditional optimization model without MRC diversity.

This paper investigates interference coordination for 3-dimension (3D) antenna array systems in multicell multiple-input multiple-output (MIMO) and orthogonal frequency division multiple-access (OFDMA) wireless networks. Cell-center user and cell-edge user specific downtilts are accordingly partitioned through dynamic vertical beamforming in the 3D MIMO-OFDM communication systems. Taking these user specific downtilts into consideration, the objective of our proposed interference coordination scheme is to maximize both the cell-edge users' and cell-center users' throughput, subject to per base-station (BS) power, cell-center user and cell-edge user specific downtilt constraints. Here, two coordination techniques, consisting of the fractional frequency reuse (FFR) scheme and partial joint process (JP) coordinated multiple point (COMP) transmission mode, are introduced in this paper. To solve the interference coordination problem, two resource block (RB) partitioning schemes are proposed for the above-mentioned coordination techniques accordingly. Based on such RB partitioning, JP CoMP-based dual decomposition method (JC-DDM) and FFR-based dual decomposition method (FDDM) are proposed, where RB assignment, power allocation (RAPA) and downtilts adjustment are jointly optimized. To simplify the computation complexity, a suboptimal algorithm (SOA) is presented to decouple the optimization problem into three subproblems by using FFR scheme. Simulation results show that all of our proposed algorithms outperform the interference coordination scheme with fixed downtilts. JC-DDM and FDDM find the local optimal throughput with different transmission techniques, while SOA iteratively optimize the downtilts and RAPA which shows close-to-optimal performance with much lower computation complexity.

This paper summarizes recent progress on modified uni-traveling carrier photodiodes that have achieved RF output power levels of 1.8 Watt and 4.4 Watt in continuous wave and pulsed operation, respectively. Flip-chip bonded discrete photodiodes, narrowband photodiodes, and photodiodes integrated with antennas are described.

In 2002, Hwang and Yeh showed that Peyravian-Zunic's password authentication schemes are not secure and proposed an improvement by using the server public key. Since applying the server public key results in the additional burden, we propose secure password authentication schemes without using the server public key in this paper.

In many real-world problems, a complex task is typically composed of a set of subtasks that follow a certain execution order. Traditional multi-agent reinforcement learning methods perform poorly in such multi-task cases, as they consider the whole problem as one task. For such multi-agent multi-task problems, heterogeneous relationships i.e., subtask-subtask, agent-agent, and subtask-agent, are important characters which should be explored to facilitate the learning performance. This paper proposes a dynamic heterogeneous graph based agent allocation-action learning framework. Specifically, a dynamic heterogeneous graph model is firstly designed to characterize the variation of heterogeneous relationships with the time going on. Then a multi-subgraph partition method is invented to extract features of heterogeneous graphs. Leveraging the extracted features, a hierarchical framework is designed to learn the dynamic allocation of agents among subtasks, as well as cooperative behaviors. Experimental results demonstrate that our framework outperforms recent representative methods on two challenging tasks, i.e., SAVETHECITY and Google Research Football full game.

This paper studies generalized variants of the MAXIMUM INDEPENDENT SET problem, called the MAXIMUM DISTANCE-d INDEPENDENT SET problem (MaxDdIS for short). For an integer d≥2, a distance-d independent set of an unweighted graph G=(V, E) is a subset S⊆V of vertices such that for any pair of vertices u, v∈S, the number of edges in any path between u and v is at least d in G. Given an unweighted graph G, the goal of MaxDdIS is to find a maximum-cardinality distance-d independent set of G. In this paper, we analyze the (in)approximability of the problem on r-regular graphs (r≥3) and planar graphs, as follows: (1) For every fixed integers d≥3 and r≥3, MaxDdIS on r-regular graphs is APX-hard. (2) We design polynomial-time O(rd-1)-approximation and O(rd-2/d)-approximation algorithms for MaxDdIS on r-regular graphs. (3) We sharpen the above O(rd-2/d)-approximation algorithms when restricted to d=r=3, and give a polynomial-time 2-approximation algorithm for MaxD3IS on cubic graphs. (4) Finally, we show that MaxDdIS admits a polynomial-time approximation scheme (PTAS) for planar graphs.

Multi-modal semantic trajectory prediction has become a new challenge due to the rapid growth of multi-modal semantic trajectories with text message. Traditional RNN trajectory prediction methods have the following problems to process multi-modal semantic trajectory. The distribution of multi-modal trajectory samples shifts gradually with training. It leads to difficult convergency and long training time. Moreover, each modal feature shifts in different directions, which produces multiple distributions of dataset. To solve the above problems, MNERM (Mode Normalization Enhanced Recurrent Model) for multi-modal semantic trajectory is proposed. MNERM embeds multiple modal features together and combines the LSTM network to capture long-term dependency of trajectory. In addition, it designs Mode Normalization mechanism to normalize samples with multiple means and variances, and each distribution normalized falls into the action area of the activation function, so as to improve the prediction efficiency while improving greatly the training speed. Experiments on real dataset show that, compared with SERM, MNERM reduces the sensitivity of learning rate, improves the training speed by 9.120 times, increases HR@1 by 0.03, and reduces the ADE by 120 meters.

In spectrum sensing, if the primary user (PU) signal and the channel noise both follow Gaussian distribution and neither of their probability distribution functions (PDFs) are known, the traditional approaches based on entropy or Likelihood Ratio Test (LRT) etc., become infeasible. To address this problem, we propose a spectrum sensing method that exploits the similarity of PDFs of two time-adjacent detected data sets with cross entropy, while accounting for achieving the detection performance of LRT which is Neyman-Pearson optimal in detecting the primary user. We show that the detection performance of the proposed method asymptotically approximates that of LRT in detecting the PU. The simulation results confirm our analysis.

A joint continuous phase frequency shift keying (CPFSK) modulation and physical-layer network coding (PNC), i.e., CPFSK-PNC, is proposed for two-way relay channels (TWRCs). This letter discusses the signal detection of the CPFSK-PNC scheme with emphasis on the maximum-likelihood sequence detection (MLSD) algorithm for the relay receiver. The end-to-end error performance of the proposed CPFSK-PNC scheme is evaluated through simulations.