Protection of the licensed user (LU) and utilization of the spectrum are the most important goals in cognitive radio networks. To achieve the first goal, a cognitive user (CU) is required to sense for a longer time period, but this adversely affects the second goal, i.e., throughput or utilization of the network, because of the reduced time left for transmission in a time slot. This tradeoff can be controlled by simultaneous sensing and data transmission for the whole frame duration. However, increasing the sensing time to the frame duration consumes more energy. We propose a new frame structure in this paper, in which transmission is done for the whole frame duration whereas sensing is performed only until the required detection probability is satisfied. This means the CU is not required to perform sensing for the whole frame duration, and thus, conserves some energy by sensing for a smaller duration. With the proposed frame structure, throughput of all the CUs is estimated for the frame and, based on the estimated throughput and consumed energy in sensing and transmission, the energy efficient pair of CUs (transmitter and receiver) that maximizes system throughput by consuming less energy, is selected for a time slot. The selected CUs transmits data for the whole time slot, whereas sensing is performed only for certain duration. The performance improvement of the proposed scheme is demonstrated through simulations by comparing it with existing schemes.

Building detection from high resolution remote sensing images is challenging due to the high intraclass variability and the difficulty in describing buildings. To address the above difficulties, a novel approach is proposed based on the combination of shape-specific feature extraction and discriminative feature classification. Shape-specific feature can capture complex shapes and structures of buildings. Discriminative feature classification is effective in reflecting similarities among buildings and differences between buildings and backgrounds. Experiments demonstrate the effectiveness of the proposed approach.

This paper presents the set of procedures to blend GNSS and V2V communication to improve the performance of the stand-alone on-board GNSS receiver and to assure mutual positioning with a bounded error. Particle filter algorithm is applied to enhance mutual positioning of vehicles, and it fuses the information provided by the GNSS receiver, wireless measurements in vehicular environments, odometer, and digital road map data including reachability and zone probabilities. Measurement-based statistical model of relative distance as a function of Time-of-Arrival is experimentally obtained. The number of collaborative vehicles to the mutual positioning procedure is investigated in terms of positioning accuracy and network performance through realistic simulation studies, and the proposed mutual positioning procedure is experimentally evaluated by a fleet of five IEEE 802.11p radio modem equipped vehicles. Collaboration in a VANET improves availability of position measurement and its accuracy up to 40% in comparison with respect to the stand-alone GNSS receiver.

A miniaturized and bandwidth-enhanced implantable antenna is designed for wireless biotelemetry in the medical implantable communications service (MICS) frequency band of 402-405MHz. To reduce the antenna size and enhance the available bandwidth with regard to the reflection coefficients, a meandered planar inverted-F antenna (PIFA) structure is adopted on a dielectric/ferrite substrate which is an artificial magneto-dielectric material. The potential of the proposed antenna for the intended applications is verified through prototype fabrication and measurement with a 2/3 human muscle phantom. Good agreement is observed between the simulation and measurement in terms of resonant characteristics and gain radiation patterns; the bandwidth is enhanced in comparison with that of the ferrite-removed antenna, and antenna gain of -27.7dB is obtained in the measurement. Allowances are made for probable fabrication inaccuracies and practical operating environments. An analysis of 1-g SAR distribution is conducted to confirm compliance with the specific absorption rate limitation (1.6W/kg) of the American National Standards Institute (ANSI).

An interference-aware dynamic channel assignment scheme is proposed with consideration of co-tier interference for the downlink of an OFDMA/FDD based dense small-cell network. The proposed scheme adaptively assigns subchannels to the small-cell user equipment (SUE) according to the given traffic load and interference effect from neighbor small-cell access points. The simulation results show that the proposed scheme outperforms the other schemes based on the graph coloring algorithm in terms of the mean SUE capacity.

In this paper, the authors propose an integer linear programming (ILP) model for static multi-car elevator operation problems. Here, “static” means that all information which make the behavior of the elevator system indeterministic is known before scheduling. The proposed model is based on the trip-based ILP model for static single-car elevator operation problems. A trip of an elevator is a one-directional movement of that elevator, which is labaled upward or downward. In the trip-based ILP model, an elevator trajectory is scheduled according to decision variables which determine allocations of trips to users of an elevator system. That model has such an advantage that the difficulty in solving ILP formulations resulted by that model does not depend on the length of the planning horizon nor the height of the considered building, thus is effective when elevator trajectories are simple. Moreover, that model has many variables relevant to elevators' positions. The proposed model is resulted by adding 3 constraints which are basically based on those variables and make it possible to prevent elevators in a same shaft from interfering. The first constraint simply imposes the first and last floors of an upper trip to be above those of its lower trip. The second constraint imagines the crossing point between upper and lower trips and imposes it ahead of or behind the lower trip according to their directions. The last constraint estimates future positions of elevators and imposes the upper trip to be above floors of passengers on the lower trip. The basic validity of the proposed model is displayed by solving 90 problem instances and examining elevator trajectories generated from them, then comparing objective function values of elevator trajectories on a multi-car elevator system with those on single-car elevator systems.

Limited satellite visibility, multipath and non-line-of-sight signals reduce the performance of the stand-alone Global Navigation Satellite System (GNSS) receiver in urban environments. Embedding 3D model of urban structures in the condition of restricted visibility of the GNSS satellites due to urban canyons may improve position measurement accuracy significantly. State-of-the-art methods use raytracing or rasterization techniques applied on a 3D map to detect satellite visibility. But these techniques are computationally expensive and limit their widespread benefits for mobile and automotive applications. In this paper, a texture-based satellite visibility detection (TBSVD) methodology suitable for mobile and automotive grade Graphical Processing Units is presented. This methodology applies ray marching algorithm on a 2D height map texture of urban structures, and it is proposed as a more efficient alternative to 3D raytracing or rasterization methodology. Real road test in the business district of the metropolitan city is conducted in order to evaluate its performance. TBSVD is implemented in conventional ranging-based GNSS solution and the results illustrate the effectiveness of the proposed approach.

Frequencies around 300GHz offer extremely broad atmospheric transmission window with relatively low losses of up to 10dB/km and can be regarded as the ultimate platform for ultrahigh-speed wireless communications with near-fiber-optic data rates. This paper reviews technical challenges and recent advances in integrated circuits targeted at communications using these and nearby “terahertz (THz)” frequencies. Possible new applications of THz wireless links that are hard to realize by other means are also discussed.

Power line noise is one of critical problems in bio-sensing. Various approaches utilizing both analog and digital techniques has been proposed. However, these approaches need active circuits with a wide dynamic range. N-path notch filters which implementable using passive components can be a promising solution to this problem. However, the notch depth of a conventional N-path notch filter is limited by the number of path. A new N-path notch filter with additional S/H circuit is proposed. Simulation results show that the proposed topology improves the notch depth by 43dB.

In this paper, we propose two secure multiuser multiple-input multiple-output (MIMO) transmission approaches based on interference alignment (IA) in the presence of an eavesdropper. To deal with the information leakage to the eavesdropper as well as the interference signals from undesired transmitters (Txs) at desired receivers (Rxs), our approaches aim to design the transmit precoding and receive subspace matrices to minimize both the total inter-main-link interference and the wiretapped signals (WSs). The first proposed IA scheme focuses on aligning the WSs into proper subspaces while the second one imposes a new structure on the precoding matrices to force the WSs to zero. In each proposed IA scheme, the precoding matrices and the receive subspaces at the legitimate users are alternatively selected to minimize the cost function of a convex optimization problem for every iteration. We provide the feasible conditions and the proofs of convergence for both IA approaches. The simulation results indicate that our two IA approaches outperform the conventional IA algorithm in terms of the average secrecy sum rate.

In this paper, we explore the relationship between Geometric Dilution of Precision (GDOP) and Cramer-Rao Bound (CRB) by tracing back to the original motivations for deriving these two indexes. In addition, the GDOP is served as a sensor-target geometric uncertainty analysis tool whilst the CRB is served as a statistical performance evaluation tool based on the sensor observations originated from target. And CRB is the inverse matrix of Fisher information matrix (FIM). Based on the original derivations for a same positioning application, we interpret their difference in a mathematical view to show that.

Interference alignment (IA) is a promising technology for eliminating interferences while it still achieves the optimal capacity scaling. However, in practical systems, the IA feasibility limit and the heavy signaling overhead obstructs employing IA to large-scale networks. In order to jointly consider these issues, we propose the feedback overhead-aware IA clustering algorithm which comprises two parts: adaptive feedback resource assignment and dynamic IA clustering. Numerical results show that the proposed algorithm offers significant performance gains in comparison with conventional approaches.

An uncorrelated asymmetric ZCZ (UA-ZCZ) sequence set is a special version of an asymmetric ZCZ (A-ZCZ) sequence set, which contains multiple subsets and each subset is a typical ZCZ sequence set. One of the most important properties of UA-ZCZ sequnence set is that two arbitrary sequences from different sequence subsets are uncorrelated sequences, whose cross-correlation function (CCF) is zeros at all shifts. Based on interleaved technique and an uncorrelated sequence set, a new UA-ZCZ sequence set is obtained via interleaving a perfect sequence. The uncorrelated property of the UA-ZCZ sequence sets is expected to be useful for avoiding inter-cell interference of QS-CDMA systems.

Shaped beam reflector antennas are widely used because they can achieve a shaped beam even with a single primary feed. Because coverage shapes depend on service areas, optimum primary radiators and reflector shapes are determined by the service areas. In this paper, we propose a simultaneous optimal design method of the primary radiator and reflector for the shaped beam antenna. Particle swarm optimization and the conjugate gradient method are adopted to optimize the primary radiator and reflector. The design method is applied to Japan coverage to verify its effectiveness.

This paper proposed that a path loss model for outdoor-to-indoor corridor is presented to construct next generation mobile communication systems. The proposed model covers the frequency range of millimeter wave bands up to 40GHz and provides three dimensional incident angle characteristics. Analysis of path loss characteristics is conducted by ray tracing. We clarify that the paths reflected multiple times between the external walls of buildings and then diffracted into one of the buildings are dominant. Moreover, we also clarify how the paths affect the path loss dependence on frequency and three dimensional incident angle. Therefore, by taking these dependencies into consideration, the proposed model decreases the root mean square errors of prediction results to within about 2 to 6dB in bands up to 40GHz.

A huge amount of content exists on the Internet, and contents from mobile devices are also present. Growth of the Internet of Things (IoT) is further accelerating this trend. Content oriented networks have been proposed as a new network architecture that conducts routing using the content's ID instead of an IP address. Content queries are routed on the content name itself instead of a destination address in these content oriented networks. When the content from a mobile device moves somewhere else, all the routing tables are generally re-created with the movement information that the mobile device sends. However, a routing scheme that uses ant colony optimization has attracted attention for supporting this process, but this optimization has a problem in that it cannot cope with moving contents and users sufficiently. In this paper, we propose a scheme that can cope with moving contents sources and users that require contents by using pheromones that are laid by these moving mobile devices. This proposed scheme can be applied to case of not only moving content sources but also the moving request users. Moreover, we conduct simulations to evaluate the performance of the proposed scheme.

RAID has been widely deployed in disk array storage systems to manage both performance and reliability simultaneously. RAID conducts two performance-critical operations during disk failures known as degraded reads/writes and recovery process. Before the recovery process is complete, reads and writes are degraded because data is reconstructed using data redundancy. The performance of degraded reads/writes is critical in order to meet stipulations in customer service level agreements (SLAs), and the recovery process affects the reliability of a storage system considerably. Both operations require fast data reconstruction. Among the erasure codes for fast reconstruction, Local Reconstruction Codes (LRC) are known to offer the best (or optimal) trade-off between storage overhead, fault tolerance, and the number of disks involved in reconstruction. Originally, LRC was designed for fast reconstruction in distributed cloud storage systems, in which network traffic is a major bottleneck during reconstruction. Thus, LRC focuses on reducing the number of disks involved in data reconstruction, which reduces network traffic. However, we observe that when LRC is applied to primary array storage systems, a major bottleneck in reconstruction results from uneven disk utilization. In other words, underutilized disks can no longer receive I/O requests as a result of the bottleneck of overloaded disks. Uneven disk utilization in LRC is due to its dedicated group partitioning policy to achieve the Maximally Recoverable property. In this paper, we present Distributed Reconstruction Codes (DRC) that support fast reconstruction in primary array storage systems. DRC is designed with group shuffling policy to solve the problem of uneven disk utilization. Experiments on real-world workloads show that DRC using global parity rotation (DRC-G) improves degraded performance by as much as 72% compared to RAID-6 and by as much as 35% compared to LRC under the same reliability. In addition, our study shows that DRC-G reduces the recovery process completion time by as much as 52% compared to LRC.

Self-paced e-learning provides much more freedom in time and locale than traditional education as well as diversity of learning contents and learning media and tools. However, its limitations must not be ignored. Lack of information on learners' states is a serious issue that can lead to severe problems, such as low learning efficiency, motivation loss, and even dropping out of e-learning. We have designed a novel e-learning support system that can visually observe learners' non-verbal behaviors and estimate their learning states and that can be easily integrated into practical e-learning environments. Three pairs of internal states closely related to learning performance, concentration-distraction, difficulty-ease, and interest-boredom, were selected as targets of recognition. In addition, we investigated the practical problem of estimating the learning states of a new learner whose characteristics are not known in advance. Experimental results show the potential of our system.

An optical intensity distribution under light irradiation in the organic photovoltaic cell affects the absorbance of the active layer, which determines the photovoltaic performance. In this research, we evaluated the optimum thickness of the organic active layer with poly[4,8-bis(5-(2-ethylhexyl)thiophen-2-yl)benzo[1,2-b;4,5-b']dithiophene-2,6-diyl-alt-(4-(2-ethylhexyl)-3-fluorothieno[3,4-b]thiophene-)-2-carboxylate-2-6-diyl)] and [6,6]-phenyl C71-butyric acid methyl ester. The spectral response of external quantum efficiency was good agreement with the simulated optical intensity distribution within a device stack as a function of the position and the wavelength. As a result, the highest photoconversion efficiency of 10.1% was achieved for the inverted device structure.

Object detection in millimeter-wave Interferometric Synthetic Aperture Radiometer (InSAR) imaging is always a crucial task. Facing unpredictable and numerous objects, traditional object detection models running after the InSAR system accomplishing imaging suffer from disadvantages such as complex clutter backgrounds, weak intensity of objects, Gibbs ringing, which makes a general purpose saliency detection system for InSAR necessary. This letter proposes a spectrum-based saliency detection algorithm to extract the salient regions from unknown backgrounds cooperating with sparse sensing InSAR imaging procedure. Directly using the interferometric value and sparse information of scenes in the basis of the Discrete Cosine Transform (DCT) domain adopted by InSAR imaging procedure, the proposed algorithm isolates the support of saliency region and then inversely transforms it back to calculate the saliency map. Comparing with other detecting algorithms which run after accomplishing imaging, the proposed algorithm will not be affected by information-loss accused by imaging procedure. Experimental results prove that it is effective and adaptable for millimeter-wave InSAR imaging.