In this article, we propose a method to reduce the impact of primary traffic on spectrum sensing performance. In practice, the sensing performance is degraded by noise-only sample in the spectrum sensing time. Therefore, we employ a time of primary user (PU) signal arrival detector in order to remove the noise-only portion. Then, we employ equal-weight-based energy detection (EWED) to provide the detection decision. The analysis and simulation results show that there exists an optimal early time of arrival (ToA) false alarm which provides better performance compared to the use of a single EWED scheme.

In Long-Term Evolution (LTE)-Advanced, heterogeneous networks are important to further improve the system throughput per unit area. In heterogeneous network deployment, low power nodes such as picocells are overlaid onto macrocells. In the downlink, the combined usage of inter-cell interference coordination (ICIC), which is a technique that reduces the severe interference from macrocells by reducing the transmission power or stopping the transmission from the macrocells, and cell range expansion (CRE), which is a technique that expands the cell radius of picocells by biasing the received signal power, is very effective in improving the system and cell-edge user throughput. In this paper, we consider two types of ICIC. The first one reduces the transmission power from the macrocells (referred to as reduced power ICIC) and the second one stops the transmission from the macrocells (referred to as zero power ICIC). This paper investigates the impact of the reduction in the transmission power when using reduced power ICIC and the restriction on the modulation scheme caused by the reduction in the transmission power when using reduced power ICIC on the user throughput performance with the CRE offset value as a parameter. In addition, the throughput performance when applying reduced power ICIC is compared to that when applying zero power ICIC. Simulation results show that the user throughput with reduced power ICIC is not sensitive to the protected subframe ratio compared to that with zero power ICIC even if the modulation scheme is restricted to only QPSK in the protected subframes. This indicates that reduced power ICIC is more robust than zero power ICIC for non-optimum protected subframe ratios.

The interference rejection combining (IRC) receiver effectively improves the cell-edge user throughput by suppressing interference from the surrounding cells. The work item (WI) for the specification of the IRC receiver is now ongoing for Release 11 Long-Term Evolution (LTE)-Advanced. Furthermore, heterogeneous networks where low power nodes such as picocells are overlaid onto macrocells are important to further improve the system throughput per unit area. In heterogeneous networks, to achieve an offloading gain from macrocells to picocells, cell range expansion (CRE) is applied. Additionally, inter-cell interference coordination (ICIC) is applied to reduce the severe inter-cell interference imposed from the macrocells onto the sets of user equipment (UEs) connected to picocells. In such cases, the interference statistics are completely different from traditional well-planned macrocell deployments, which have been investigated for the IRC receiver. This paper clarifies the effect of the IRC receiver in a heterogeneous network employing CRE and ICIC. Simulation results show that when both CRE and ICIC are applied, the effect of the IRC receiver becomes small due to a reduction in the severe inter-cell interference from ICIC. However, we clarify that the user throughput gain at the cumulative distribution function of 5% from the IRC receiver exceeding 10% is achieved compared to the conventional minimum mean square error (MMSE) receiver in a heterogeneous network regardless of the usage of ICIC. Furthermore, in heterogeneous networks employing CRE and ICIC, we clarify that an average user throughput gain exceeding 5% is achieved from the IRC receiver and the improvement in the average user throughput is high especially for the UEs connected to picocells compared to UEs connected to macrocells.

In this paper, a novel feature named bidirectional local template patterns (B-LTP) is proposed for use in pedestrian detection in still images. B-LTP is a combination and modification of two features, histogram of templates (HOT) and center-symmetric local binary patterns (CS-LBP). For each pixel, B-LTP defines four templates, each of which contains the pixel itself and two neighboring center-symmetric pixels. For each template, it then calculates information from the relationships among these three pixels and from the two directional transitions across these pixels. Moreover, because the feature length of B-LTP is small, it consumes less memory and computational power. Experimental results on an INRIA dataset show that the speed and detection rate of our proposed B-LTP feature outperform those of other features such as histogram of orientated gradient (HOG), HOT, and covariance matrix (COV).

Corpus-based concatenative speech synthesis has been widely investigated and deployed in recent years since it provides a highly natural synthesized speech quality. The amount of computation required in the run time, however, can often be quite large. In this paper, we propose early stopping schemes for Viterbi beam search in the unit selection, with which we can stop early in the local Viterbi minimization for each unit as well as in the exploration of candidate units for a given target. It takes advantage of the fact that the space of the acoustic parameters of the database units is fixed and certain lower bounds of the concatenation costs can be precomputed. The proposed method for early stopping is admissible in that it does not change the result of the Viterbi beam search. Experiments using probability-based concatenation costs as well as distance-based costs show that the proposed methods of admissible stopping effectively reduce the amount of computation required in the Viterbi beam search while keeping its result unchanged. Furthermore, the reduction effect of computation turned out to be much larger if the available lower bound for concatenation costs is tighter.

This paper analyzes the conventional unequal erasure protection (UXP) scheme for scalable video transmission, and proposes a dynamic hybrid UXP/ARQ transmission framework to improve the performance of the conventional UXP method for bandwidth-constrained scalable video transmission. This framework applies automatic retransmission request (ARQ) to the conventional UXP scheme for scalable video transmission, and dynamically adjusts the transmission time budget of each group of picture (GOP) according to the feedback about the transmission results of the current and previous GOPs from the receiver. Moreover, the parameter of target video quality is introduced and optimized to adapt to the channel condition in pursuit of more efficient dynamic time allocation. In addition, considering the play-out deadline constraint, the time schedule for the proposed scalable video transmission system is presented. Simulation results show that compared with the conventional UXP scheme and its enhanced method, the average peak signal to noise ratio (PSNR) of the reconstructed video can be improved significantly over a wide range of packet loss rates. Besides, the visual quality fluctuation among the GOPs can be reduced for the video which has much movement change.

This paper presents an efficient algorithm for reporting all intersections among n given segments in the plane using work space of arbitrarily given size. More exactly, given a parameter s which is between Ω(1) and O(n) specifying the size of work space, the algorithm reports all the segment intersections in roughly O(n2/+ K) time using O(s) words of O(log n) bits, where K is the total number of intersecting pairs. The time complexity can be improved to O((n2/s) log s + K) when input segments have only some number of different slopes.

In this paper, we propose a novel camera identification method based on photo-response non-uniformity (PRNU), which performs well even with rotated videos. One of the disadvantages of the PRNU-based camera identification methods is that they are very sensitive to de-synchronization. If a video under investigation is slightly rotated, the identification process without synchronization fails. The proposed method solves this kind of out-of-sync problem, by achieving rotation-tolerance using Optimal Tradeoff Circular Harmonic Function (OTCHF) correlation filter. The experimental results show that the proposed method identifies source device with high accuracy from rotated videos.

We have developed a dedicated onboard “sensor” utilizing wireless communication devices for collision avoidance around road intersections. The “sensor” estimates the positions of transmitters on traffic participants by comparing the strengths of signals received by four ZigBee receivers installed at the four corners of a vehicle. On-board sensors involving cameras cannot detect objects in non line-of-sight (NLOS) area caused by buildings and other vehicles. Although infrastructure sensors for vehicle-to-infrastructure (V2I) cooperative systems can detect such hidden objects, they are substantially more expensive than on-board sensors. The on-board wireless “sensor” developed in this work would function as an alternative tool for collision avoidance around intersections. Herein, we extend our previous work by considering a road surface reflection model to improve the estimation accuracy. By using this model, we succeeded in reducing the error mismatches between the observed data and the calibration data of the estimation algorithm. The proposed system will be realized on the basis of these enhancements.

As the demand for high-throughput communications in wireless LANs (WLAN) increases, the need for expanding channel bandwidth also increases. However, the use of wider band channels results in a decrease in the number of available channels because the total available bandwidth for WLAN is limited. Therefore, if multiple access points (APs) are in proximity and the cells overlap, it is difficult for each AP to use an orthogonal channel and competition increases between APs using the same channel. Coordination of APs is one promising approach; however, it is impractical to control all APs in WLAN systems. To cope with this problem, we proposed to analyze throughput performances of a multibandwidth channel selection by the coordinating APs at Nash equilibria, which can be considered as operating points for independent channel selection by APs. To clarify the effect of coordinating APs, we assume a simple scenario where the cells of three or more APs overlap, and each AP can select multibandwidth channels to maximize their own throughput. Through game-theoretic analysis, we find that the coordinated APs are able to select channels more effectively than if each AP independently selects channels. Consequently, the total throughput of the coordinated APs at Nash equilibria is significantly improved.

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.

In this paper, we present a novel class of long quasi-cyclic low-density parity-check (QC-LDPC) codes. Each of the codes in this class has a structure formed by concatenating single-parity-check codes and QC-LDPC codes of shorter lengths, which allows for efficient, high throughput encoder/decoder implementations. Using a code in this class, we design a forward error correction (FEC) scheme for optical transmission systems and present its high throughput encoder/decoder architecture. In order to demonstrate its feasibility, we implement the architecture on a field programmable gate array (FPGA) platform. We show by both FPGA-based simulations and measurements of an optical transmission system that the FEC scheme can achieve excellent error performance and that there is no significant performance degradation due to the constraint on its structure while getting an efficient, high throughput implementation is feasible.

The gathering problem of anonymous and oblivious mobile robots is one of the fundamental problems in the theoretical mobile robotics. We consider the gathering problem in unoriented and anonymous rings, which requires that all robots eventually keep their positions at a common non-predefined node. Since the gathering problem cannot be solved without any additional capability to robots, all the previous results assume some capability of robots, such as the agreement of local view. In this paper, we focus on the multiplicity detection capability. This paper presents a deterministic gathering algorithm with local-weak multiplicity detection, which provides a robot with information about whether its current node has more than one robot or not. This assumption is strictly weaker than that in previous works. Our algorithm achieves the gathering from an aperiodic and asymmetric configuration with 2 < k < n/2 robots, where n is the number of nodes. We also show that our algorithm is asymptotically time-optimal one, i.e., the time complexity of our algorithm is O(n). Interestingly, despite the weaker assumption, it achieves significant improvement compared to the previous algorithm, which takes O(kn) time for k robots.

This paper presents a 20 GHz push-push VCO realized by a 10 GHz super-harmonic coupled quadrature oscillator for a quadrature 60 GHz frequency synthesizer. The output nodes are peaked by a tunable second harmonic resonator. The proposed VCO is implemented in 65 nm CMOS process. It achieves a tuning range of 3.5 GHz from 16.1 GHz to 19.6 GHz with a phase noise of -106 dBc/Hz at 1 MHz offset. The power consumption of the core oscillators is 10.3 mW and an FoM of -181.3 dBc/Hz is achieved.

Event extraction is vital to social media monitoring and social event prediction. In this paper, we propose a method for social event extraction from web documents by identifying binary relations between named entities. There have been many studies on relation extraction, but their aims were mostly academic. For practical application, we try to identify 130 relation types that comprise 31 predefined event types, which address business and public issues. We use structured Support Vector Machine, the state of the art classifier to capture relations. We apply our method on news, blogs and tweets collected from the Internet and discuss the results.

In this paper we aim to group visual correspondences in order to detect objects or parts of objects commonly appearing in a pair of images. We first extract visual keypoints from images and establish initial point correspondences between two images by comparing their descriptors. Our method is based on two types of graphs, named relational graphs and correspondence graphs. A relational graph of a point is constructed by thresholding geometric and topological distances between the point and its neighboring points. A threshold value of a geometric distance is determined according to the scale of each keypoint, and a topological distance is defined as the shortest path on a Delaunay triangulation built from keypoints. We also construct a correspondence graph whose nodes represent two pairs of matched points or correspondences and edges connect consistent correspondences. Two correspondences are consistent with each other if they meet the local consistency induced by their relational graphs. The consistent neighborhoods should represent an object or a part of an object contained in a pair of images. The enumeration of maximal cliques of a correspondence graph results in groups of keypoint pairs which therefore involve common objects or parts of objects. We apply our method to common visual pattern detection, object detection, and object recognition. Quantitative experimental results demonstrate that our method is comparable to or better than other methods.

Scale-Invariant Feature Transform (SIFT) has lately attracted attention in computer vision as a robust keypoint detection algorithm which is invariant for scale, rotation and illumination changes. However, its computational complexity is too high to apply in practical real-time applications. This paper proposes a low complexity keypoint extraction algorithm based on SIFT descriptor and utilization of the database, and its real-time hardware implementation for Full-HD resolution video. The proposed algorithm computes SIFT descriptor on the keypoint obtained by corner detection and selects a scale from the database. It is possible to parallelize the keypoint detection and descriptor computation modules in the hardware. These modules do not depend on each other in the proposed algorithm in contrast with SIFT that computes a scale. The processing time of descriptor computation in this hardware is independent of the number of keypoints because its descriptor generation is pipelining structure of pixel. Evaluation results show that the proposed algorithm on software is 12 times faster than SIFT. Moreover, the proposed hardware on FPGA is 427 times faster than SIFT and 61 times faster than the proposed algorithm on software. The proposed hardware performs keypoint extraction and matching at 60 fps for Full-HD video.

In this paper we propose a method to use features of an individual object to locate and recognize this object concurrently in a static image with Multi-feature fusion based on multiple objects sample library. This method is proposed based on the observation that lots of previous works focuses on category recognition and takes advantage of common characters of special category to detect the existence of it. However, these algorithms cease to be effective if we search existence of individual objects instead of categories in complex background. To solve this problem, we abandon the concept of category and propose an effective way to use directly features of an individual object as clues to detection and recognition. In our system, we import multi-feature fusion method based on colour histogram and prominent SIFT (p-SIFT) feature to improve detection and recognition accuracy rate. p-SIFT feature is an improved SIFT feature acquired by further feature extraction of correlation information based on Feature Matrix aiming at low computation complexity with good matching rate that is proposed by ourselves. In process of detecting object, we abandon conventional methods and instead take full use of multi-feature to start with a simple but effective way-using colour feature to reduce amounts of patches of interest (POI). Our method is evaluated on several publicly available datasets including Pascal VOC 2005 dataset, Objects101 and datasets provided by Achanta et al.

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.

Scheduling restriction is attracting much attention in LTE-Advanced as a technique to reduce the power consumption and network overheads in interference coordinated heterogeneous networks (HetNets). Such a network with inter-cell interference coordination (ICIC) provides two radio resources with different channel quality statistics. One of the resources is protected (unprotected) from inter-cell interference (hence, called protected (non-protected) resource) and has higher (lower) average channel quality. Without scheduling restriction, the channel quality feedback would be doubled to reflect the quality difference of the two resources. We present a simple scheduling restriction scheme that addresses the problem without significant performance degradation. Users with relatively larger (smaller) average channel quality difference between the two resources are scheduled in the protected (non-protected) resource only, and a boundary user, determined by a proportional fair resource allocation (PFRA) under simplified static channels, is scheduled on one of the two resources or both depending on PFRA. Having most users scheduled in only one of the resources, the power consumption and network overheads that would otherwise be required for the channel quality feedback on the other resource can be avoided. System level simulation of LTE-Advanced downlink shows that the performance degradation due to our scheduling restriction scheme is less than 2%, with the average feedback reduction of 40%.