Compressed sensing is an effective compression algorithm. It is widely used to measure signals in distributed sensor networks (DSNs). Considering the limited resources of DSNs, the measurement matrices used in DSNs must be simple. In this paper, we construct a deterministic measurement matrix based on Gordon-Mills-Welch (GMW) sequence. The column vectors of the proposed measurement matrix are generated by cyclically shifting a GMW sequence. Compared with some state-of-the-art measurement matrices, the proposed measurement matrix has relative lower computational complexity and needs less storage space. It is suitable for resource-constrained DSNs. Moreover, because the proposed measurement matrix can be realized by using simple shift register, it is more practical. The simulation result shows that, in terms of recovery quality, the proposed measurement matrix performs better than some state-of-the-art measurement matrices.

This paper reviews access system standardization activities and related technologies from the viewpoints of optical-based PON access, mobile access systems including LPWAN, and access network virtualization. Future study issues for the next access systems are also presented.

By incorporating cloud computing capabilities to provide radio access functionalities, Cloud Radio Access Networks (CRANs) are considered to be a key enabling technology of future 5G and beyond communication systems. In CRANs, centralized radio resource allocation optimization is performed over a large number of small cells served by simple access points, the Remote Radio Heads (RRHs). However, the fronthaul links connecting each RRH to the cloud introduce delays and entail imperfect Channel State Information (CSI) knowledge at the cloud processors. In order to satisfy the stringent latency requirements envisioned for 5G applications, the concept of Fog Radio Access Networks (FogRANs) has recently emerged for providing cloud computing at the edge of the network. Although FogRAN may alleviate the latency and CSI quality issues of CRAN, its distributed nature degrades network interference mitigation and global system performance. Therefore, we investigate the design of tailored user pre-scheduling and beamforming for FogRANs. In particular, we propose a hybrid algorithm that exploits both the centralized feature of the cloud for globally-optimized pre-scheduling using imperfect global CSIs, and the distributed nature of FogRAN for accurate beamforming with high quality local CSIs. The centralized phase enables the interference patterns over the global network to be considered, while the distributed phase allows for latency reduction, in line with the requirements of FogRAN applications. Simulation results show that our proposed algorithm outperforms the baseline algorithm under imperfect CSIs, jointly in terms of throughput, energy efficiency, as well as delay.

We numerically demonstrate a possibility on-off keying (OOK) type of modulation over tens gigabits per second for sub-terahertz radiation in our proposed wireless transmitter device structure towards radio over fiber (RoF) technology. The integrated device consists of an InP-based compound semiconductor resonant tunneling diode (RTD) adjacent to an InP-based photo diode (PD), a self-complementary type of bow-tie antenna (BTA), external microstrip lines. These integration structures are carefully designed to obtain robust relaxation oscillation (RO) due to the negative differential conductance (NDC) characteristic of the RTD and the nonlinearity of the NDC. Moreover, the device is designed to exhibit OOK modulation of RO due to photo current from the PD inject into the RTD. Electromagnetic simulations and nonlinear equivalent circuit model of the whole device structure are established to perform large signal analysis numerically with considerations of previously measured characteristics of the triple-barrier RTD.

In this paper, we have investigated the etching selectivity of HfN encapsulating layer for high quality PtHf-alloy silicide (PtHfSi) formation with low contact resistivity on Si(100). The HfN(10 nm)/PtHf(20 nm)/p-Si(100) stacked layer was in-situ deposited by RF-magnetron sputtering at room temperature. Then, silicidation was carried out at 500°C/20 min in N2/4.9%H2 ambient. Next, the HfN encapsulating layer was etched for 1-10 min by buffered-HF (BHF) followed by the unreacted PtHf metal etching. We have found that the etching duration of the 10-nm-thick HfN encapsulating layer should be shorter than 6 min to maintain the PtHfSi crystallinity. This is probably because the PtHf-alloy silicide was gradually etched by BHF especially for the Hf atoms after the HfN was completely removed. The optimized etching process realized the ultra-low contact resistivity of PtHfSi to p+/n-Si(100) and n+/p-Si(100) such as 9.4×10-9Ωcm2 and 4.8×10-9Ωcm2, respectively, utilizing the dopant segregation process. The control of etching duration of HfN encapsulating layer is important to realize the high quality PtHfSi formation with low contact resistivity.

This paper proposes an improved closed-form method for moving source localization using time difference of arrival (TDOA), frequency difference of arrival (FDOA) and differential Doppler rate measurements. After linearizing the measurement equations by introducing three additional parameters, a rough estimate is obtained by using the weighted least-square (WLS) estimator. To further refine the estimate, the relationship between additional parameters and source location is utilized. The proposed method gives a final closed-form solution without iteration or the extra mathematics operations used in existing methods by employing the basic idea of WLS processing. Numerical examples show that the proposed method exhibits better robustness and performance compared with several existing methods.

Network virtualization is viewed as a promising approach to facilitate the sharing of physical infrastructure among different kinds of users and applications. In this letter, we propose a topological consistency-based virtual network embedding (TC-VNE) over elastic optical networks (EONs). Based on the concept of topological consistency, we propose a new node ranking approach, named Sum-N-Rank, which contributes to the reduction of optical path length between preferred substrate nodes. In the simulation results, we found our work contributes to improve spectral efficiency and balance link load simultaneously without deteriorating blocking probability.

For the three-user X channel, its degree of freedom (DoF) 9/5 has been shown achievable theoretically through asymptotic model with infinite resources, which is impractical. In this article, we explore the propagation delay (PD) feature among different links to maximize the achievable DoF with the minimum cost. Since perfect interference alignment (IA) is impossible for 9 messages within 5 time-slots, at least one extra time-slot should be utilized. By the cyclic polynomial approach, we propose a scheme with the maximum achievable DoF of 5/3 for 10 messages within 6 time-slots. Feasibility conditions in the Euclidean space are also deduced, which demonstrates a quite wide range of node arrangements.

With the existing of coverage holes, the Quality of Service (such as event response, package delay, and the life time et al.) of a Wireless Sensor Network (WSN) may become weaker. In order to recover the holes, one can locate them by identifying the boundary nodes on their edges. Little effort has been made to distinguish the boundary nodes in a model where wireless sensors are randomly deployed on a three-dimensional surface. In this paper, we propose a distributed method which contains three steps in succession. It first projects the 1-hop neighborhood of a sensor to the plane. Then, it sorts the projected nodes according to their angles and finds out if there exists any ring formed by them. At last, the algorithm validates a circle to confirm that it is a ring surrounding the node. Our solution simulates the behavior of rotating a semicircle plate around a sensor under the guidance of its neighbors. Different from the existing results, our method transforms a three-dimensional problem into a two-dimensional one and maintaining its original topology, and it does not rely on any complex Hamiltonian Cycle finding to test the existence of a circle in the neighborhood of a sensor. Simulation results show our method outperforms others at the correctness and effectiveness in identifying the nodes on the edges of a three-dimensional WSN.

Data-driven untying of a recursive autoencoder (RAE) is proposed for utterance intent classification for spoken dialogue systems. Although an RAE expresses a nonlinear operation on two neighboring child nodes in a parse tree in the application of spoken language understanding (SLU) of spoken dialogue systems, the nonlinear operation is considered to be intrinsically different depending on the types of child nodes. To reduce the gap between the single nonlinear operation of an RAE and intrinsically different operations depending on the node types, a data-driven untying of autoencoders using part-of-speech (PoS) tags at leaf nodes is proposed. When using the proposed method, the experimental results on two corpora: ATIS English data set and Japanese data set of a smartphone-based spoken dialogue system showed improved accuracies compared to when using the tied RAE, as well as a reasonable difference in untying between two languages.

Among the five carrier aggregation (CA) deployment scenarios, the most preferred scenario is Scenario 1, which maximizes CA gain by fully overlapping a primary cell (PCell) and one or more secondary cells (SCells). It is possible since the same frequency band is used between component carriers (CCs) so nearly the same coverage is expected. However, Scenario 1 cannot guarantee high throughput in multi-radio access technology carrier aggregation (multi-RAT CA) which is actively being researched. Different carrier frequency characteristics in multi-RAT CA makes it hard to accurately match different frequency ranges. If the ranges of PCell and SCell differ, high throughput may not be obtained despite the CA operation. We found a coverage mismatch of approximately 37% between the PCell and SCell in the deployed network and realized a reduced CA gain in those areas. In this paper, we propose a novel PCell change approach named “PCell frequency switching (PFS)” to guarantee high throughput against cell coverage mismatch in multi-RAT CA deployment scenario 1. The experiment results show that the throughput increased by 9.7% on average and especially by 80.9% around the cell edge area when PFS is applied instead of the legacy CA handover operation.

In this paper, a reduction of the number of components included in direct simulation type active complex filter is proposed. The proposed method is achieved by sharing NIC's (Negative Impedance Converters) which satisfy some conditions. Compared with the conventional method, the proposed one has wide generality. As an example, a third-order complex elliptic filter is designed. The validity of the proposed method is confirmed through experiment.

Salient region detection is a fundamental problem in computer vision and image processing. Deep learning models perform better than traditional approaches but suffer from their huge parameters and slow speeds. To handle these problems, in this paper we propose the multi-feature fusion network (MFFN) - a efficient salient region detection architecture based on Convolution Neural Network (CNN). A novel feature extraction structure is designed to obtain feature maps from CNN. A fusion dense block is used to fuse all low-level and high-level feature maps to derive salient region results. MFFN is an end-to-end architecture which does not need any post-processing procedures. Experiments on the benchmark datasets demonstrate that MFFN achieves the state-of-the-art performance on salient region detection and requires much less parameters and computation time. Ablation experiments demonstrate the effectiveness of each module in MFFN.

Signed networks are ubiquitous in the real world. It is of great significance to study the problem of community detection in signed networks. In general, the behaviors of nodes in a signed network are rational, which coincide with the players in the theory of game that can be used to model the process of the community formation. Unlike unsigned networks, signed networks include both positive and negative edges, representing the relationship of friends and foes respectively. In the process of community formation, nodes usually choose to be in the same community with friends and between different communities with enemies. Based on this idea, we proposed a game theory model to address the problem of community detection in signed networks. Taking nodes as players, we build a gain function based on the numbers of positive edges and negative edges inside and outside a community, and prove the existence of Nash equilibrium point. In this way, when the game reaches the Nash equilibrium state, the optimal strategy space for all nodes is the result of the final community division. To systematically investigate the performance of our method, elaborated experiments on both synthetic networks and real-world networks are conducted. Experimental results demonstrate that our method is not only more accurate than other existing algorithms, but also more robust to noise.

The large computational complexity makes stereo matching a big challenge in real-time application scenario. The problem of stereo matching in a video sequence is slightly different with that in a still image because there exists temporal correlation among video frames. However, no existing method considered temporal consistency of disparity for algorithm acceleration. In this work, we proposed a scheme called the dynamic disparity range (DDR) to optimize matching cost calculation and cost aggregation steps by narrowing disparity searching range, and a scheme called temporal cost aggregation path to optimize the cost aggregation step. Based on the schemes, we proposed the DDR-SGM and the DDR-MCCNN algorithms for the stereo matching in video sequences. Evaluation results showed that the proposed algorithms significantly reduced the computational complexity with only very slight loss of accuracy. We proved that the proposed optimizations for the stereo matching are effective and the temporal consistency in stereo video is highly useful for either improving accuracy or reducing computational complexity.

This paper presents an analysis of random number generators based on continuous-time chaotic oscillators. Two different methods for random number generation have been studied: 1) Regular sampling of a chaotic waveform, and 2) Chaotic sampling of a regular waveform. Kernel density estimation is used to analytically describe the distribution of chaotic state variables and the probability density function corresponding to the output bit stream. Random bit sequences are generated using analytical equations and results from numerical simulations. Applying the concepts of autocorrelation and approximate entropy, randomness quality of the generated bit sequences are assessed to analyze relationships between the frequencies of the regular and chaotic waveforms used in both random number generation methods. It is demonstrated that in both methods, there exists certain ratios between the frequencies of regular and chaotic signal at which the randomness of the output bit stream changes abruptly. Furthermore, both random number generation methods have been compared against their immunity to interference from external signals. Analysis shows that chaotic sampling of regular waveform method provides more robustness against interference compared to regular sampling of chaotic waveform method.

The blind multichannel identification is useful in many applications. Although many approaches have been proposed to address this challenging problem, the adaptive filtering-based methods are attractive due to their computational efficiency and good convergence property. The multichannel normalized least mean-square (MCNLMS) algorithm is easy to implement, but it converges very slowly for a correlated input. The multichannel affine projection algorithm (MCAPA) is thus proposed to speed up the convergence. However, the convergence of the MCNLMS and MCAPA is still unsatisfactory in practice. In this paper, we propose a time-domain Kalman filtering approach to the blind multichannel identification problem. Specifically, the proposed adaptive Kalman filter is based on the cross relation method and also uses more past input vectors to explore the decorrelation property. Simulation results indicate that the proposed method outperforms the MCNLMS and MCAPA significantly in terms of the initial convergence and tracking capability.

A high-rate coding scheme that polar codes are concatenated with low density generator matrix (LDGM) codes is proposed in this paper. The scheme, referred to as polar-LDGM (PLG) codes, can boost the convergence speed of polar codes and eliminate the error floor behavior of LDGM codes significantly, while retaining the low encoding and decoding complexity. With a sensibly designed Gaussian approximation (GA), we can accurately predict the theoretical performance of PLG codes. The numerical results show that PLG codes have the potential to approach the capacity limit and avoid error floors effectively. Moreover, the encoding complexity is lower than the existing LDPC coded system. This motives the application of powerful PLG codes to satellite communications in which message transmission must be extremely reliable. Therefore, an adaptive relaying protocol (ARP) based on PLG codes for the relay satellite system is proposed. In ARP, the relay transmission is selectively switched to match the channel conditions, which are determined by an error detector. If no errors are detected, the relay satellite in cooperation with the source satellite only needs to forward a portion of the decoded message to the destination satellite. It is proved that the proposed scheme can remarkably improve the error probability performance. Simulation results illustrate the advantages of the proposed scheme

This paper presents an interference suppression and signal restoration technique that can create the clean signals required by automotive frequency-modulated continuous wave radar systems. When a radar signal from another radar system interferes with own transmitted radar signal, the target detection performance is degraded. This is because the beat frequency corresponding to the target cannot be estimated owing to the increase in the noise floor. In this case, advanced weighted-envelope normalization or wavelet denoising can be used to mitigate the effect of the interference; however, these methods can also lead to the loss of the desired signal containing the range and velocity information of the target. Therefore, we propose a method based on an autoregressive model to restore a signal damaged by mutual interference. The method uses signals that are not influenced by the interference to restore the signal. In experiments conducted using two different automotive radar systems, our proposed method is demonstrated to effectively suppress the interference and restore the desired signal. As a result, the noise floor resulting from the mutual interference was lowered and the beat frequency corresponding to the desired target was accurately estimated.

The electric properties of a field-effect transistor not only depend on gate surface sidewall but also on channel orientation when applying channel stain engineering. The change of the gate surface and channel orientation through the rotated FinFETs provides the capability to compare the orientation dependence of performance and reliability. This study characterized the <100> and <110> channels of FinFETs on the same wafer under tensile and compressive stresses by cutting the wafer into rectangular silicon pieces and evaluated their piezoresistance coefficients. The piezoresistance coefficients of the <100> and <110> silicon under tensile and compressive stresses were first evaluated based on the current setup. Tensile stresses enhance the mobilities of both <100> and <110> channels, whereas compressive stresses degrade them. Electrical characterization revealed that the threshold voltage variation and drive current degradation of the {100} surface were significantly higher than those of {110} for positive bias temperature instability and hot carrier injection with equal gate and drain voltage (VG=VD). By contrast, insignificant difference is noted for the subthreshold slope degradation. These findings imply that a higher ratio of bulk defect trapping is generated by gate voltage on the <100> surface than that on the <110> surface.