We consider Downlink (DL) scheduling for a multi-user cooperative cellular system with fixed relays. The conventional scheduling trend is to avoid interference by allocating orthogonal radio resources to each user, although simultaneous allocation of users on the same resource has been proven to be superior in, e.g., the broadcast channel. Therefore, we design a scheduler where in each frame, two selected relayed users are supported simultaneously through the Superposition Coding (SC) based scheme proposed in this paper. In this scheme, the messages destined to the two users are superposed in the modulation domain into three SC layers, allowing them to benefit from their high quality relayed links, thereby increasing the sum-rate. We derive the optimal power allocation over these three layers that maximizes the sum-rate under an equal rates' constraint. By integrating this scheme into the proposed scheduler, the simulation results show that our proposed SC scheduler provides high throughput and rate outage probability performance, indicating a significant fairness improvement. This validates the approach of simultaneous allocation versus orthogonal allocation in the cooperative cellular system.

Inter-satellite link (ISL) is an important part of the next generation global navigation satellite system (GNSS). In this paper, key technologies of GNSS ISL ranging and time synchronization are researched. Considering that Ka frequency band is used for ISL, a fixed topology is designed and a new time division duplex (TDD) mode is proposed after analyzing the characteristics of GNSS constellations. A novel method called Non-coherent Dual One-way Measuring (NC-DOWM) is applied to this TDD mode. In addition, relevant mathematical formulas, error models and error compensation are discussed in detail. It is found that the proposed NC-DOWM method for GNSS ISL ranging and time synchronization outperforms the current method for GPS in terms of channel utilization efficiency and measuring precision. Furthermore, the presented method has excellent anti-interference capability and engineering feasibility, which can provide a strong technical support for the ISL of the next generation GNSS.

Finite difference time domain (FDTD) method has been accelerated on the Cell Broadband Engine (Cell B.E.). However the problem has arisen that speedup is limited by the bandwidth of the main memory on large-scale analysis. As described in this paper, we propose a novel algorithm and implement FDTD using it. We compared the novel algorithm with results obtained using region segmentation, thereby demonstrating that the proposed algorithm has shorter calculation time than that provided by region segmentation.

WSNs (Wireless Sensor Networks) are becoming more widely used in various fields, and localization is a crucial and essential issue for sensor network applications. In this letter, we propose a low-complexity localization mechanism for WSNs that operate in 3D (three-dimensional) space. The basic idea is to use aerial vehicles that are deliberately equipped with anchor nodes. These anchors periodically broadcast beacon signals containing their current locations, and unknown nodes receive these signals as soon as the anchors enter their communication range. We estimate the locations of the unknown nodes based on the proposed scheme that transforms the 3D problem into 2D computations to reduce the complexity of 3D localization. Simulated results show that our approach is an effective scheme for 3D self-positioning in WSNs.

Network testbeds have been used for network measurement and experiments. In such testbeds, resources, such as CPU, memory, and I/O interfaces, are shared and virtualized to maximize node utility for many users. A few studies have investigated the impact of virtualization on precise network measurement and understood Internet traffic characteristics on virtualized testbeds. Although scheduling latency and heavy loads are reportedly affected in precise network measurement, no clear conditions or criteria have been established. Moreover, empirical-statistical criteria and methods that pick out anomalous cases for precise network experiments are required on userland because virtualization technology used in the provided testbeds is hardly replaceable. In this paper, we show that ‘oversize packet spacing’, which can be caused by CPU scheduling latency, is a major cause of throughput instability on a virtualized network testbed even when no significant changes occur in well-known network metrics. These are unusual anomalies on virtualized network environment. Empirical-statistical analysis results accord with results at previous work. If network throughput is decreased by the anomalies, we should carefully review measurement results. Our empirical approach enables anomalous cases to be identified. We present CPU availability as an important criterion for estimating the anomalies.

In the underlay decode-and-forward (DaF) cooperative cognitive radio (CR) network, an optimal relay can be selected by the conventional max-min selection on the condition of not violating the interference temperature (IT) constraint. However, the max-min selection may cause some extra amount of interference to the primary system (PS) such that the so-called transfer ratio (TR) may be lower. Note that TR is newly defined as the ratio of the secondary system's (SS's) capacity gain to the PS's capacity loss due to the activities of SS. In order to improve the TR value, we are motivated by the pricing function in game theory to propose a novel low-interference relay selection by taking the impacts of the interference from SS to PS into consideration. Using the low-interference selection, however, it will not always allow the optimal relay to be picked. To clarify this phenomenon, the still optimal probability is defined as the probability of selecting the optimal relay by the proposed scheme. In addition, the impacts of the low-interference selection on the SS's capacity and outage probability are also analyzed. The simulation results prove that compared with the max-min selection, the proposed scheme can achieve higher TR values as well as the total capacity which also indicates that a higher spectrum efficiency can be achieved. It is believed that the results of this paper can provide an alternative viewpoint of evaluating the spectrum efficiency and inspire more interesting and important research topics in the future.

With the progress of process technology in recent years, low voltage power supplies have become quite predominant. With this, the voltage margin has decreased and therefore the on-chip decoupling capacitance optimization that satisfies the voltage drop constraint becomes more important. In addition, the reduction of the on-chip decoupling capacitance area will reduce the chip area and, therefore, manufacturing costs. Hence, we propose an algorithm that satisfies the voltage drop constraint and at the same time, minimizes the total on-chip decoupling capacitance area. The proposed algorithm uses the idea of the network algorithm where the path which has the most influence on voltage drop is found. Voltage drop is improved by adding the on-chip capacitance to the node on the path. The proposed algorithm is efficient and effectively adds the on-chip capacitance to the greatest influence on the voltage drop. Experimental results demonstrate that, with the proposed algorithm, real size power/ground network could be optimized in just a few minutes which are quite practical. Compared with the conventional algorithm, we confirmed that the total on-chip decoupling capacitance area of the power/ground network was reducible by about 4050%.

We describe an efficient algorithm that extracts a connected component of an isosurface, or a contour, from a 3D rectilinear volume data. The efficiency of the algorithm is achieved by three factors: (i) directly working with rectilinear grids, (ii) parallel utilization of a multi-core CPU for extracting active cells, the cells containing the contour, and (iii) parallel utilization of a many-core GPU for computing the geometries of a contour surface in each active cell using CUDA. Experimental results show that our hybrid parallel implementation achieved up to 20x speedup over existing methods on an ordinary PC. Our work coupled with the Contour Tree framework is useful for quickly segmenting, displaying, and analyzing a feature of interest in 3D rectilinear volume data without being distracted by other features.

In this letter, we study cooperative transmission in wireless multicast networks. An opportunistic cooperative multicast scheme based on coded cooperation (OCM-CC) is proposed and its closed-form expression of outage performance is obtained. Through numeric evaluation, we analyze its outage probability with different numbers of relays and different cooperative ratios.

In this paper, we propose a quantitative metric of measuring the degree of the visual fatigue in a stereoscopy. To the best of our knowledge, this is the first simplified relative quantitative approach describing visual fatigue value of a stereoscopy. Our experimental result shows that the correlation index of more than 98% is obtained between our Simplified Relative Visual Fatigue (SRVF) model and Mean Opinion Score (MOS).

A signal model and weighted-average based estimation techniques are proposed to estimate the angle-of-arrival (AOA) parameters of multiple clusters for a low data rate ultrawide band (LR-UWB) based wireless positioning system. The optimal AOA estimation techniques for the LR-UWB wireless positioning system according to the cluster condition are introduced and it is shown that the proposed techniques are superior to the conventional technique from the standpoint of performance.

The increase in the advanced location based services such as traffic coordination and management necessitates the need for advanced models tracking the positions of Moving Objects (MOs) like vehicles. Due to computer processing limitations, it is impossible for MOs to continuously update their locations. This results in the uncertainty nature of a MO's location between any two reported positions. Efficiently managing and quantifying the uncertainty regions of MOs are needed in order to support different types of queries and to improve query response time. This challenging problem of modeling uncertainty regions associated with MO was recently addressed by researchers and resulted in models that ranged from linear which require few properties of MOs as input to the models, to non-linear that are able to more accurately represent uncertainty regions by considering higher degree input. This paper summarizes and discusses approaches in modeling uncertainty regions associated with MOs. It further illustrates the need for appropriate approximations especially in the case of non-linear models as the uncertainty regions become rather irregularly shaped and difficult to manage. Finally, we demonstrate through several experimental sets the advantage of non-linear models over linear models when the uncertainty regions of MOs are approximated by two different approximations; the Minimum Bounding Box (MBB) and the Tilted Minimum Bounding Box (TMBB).

We developed a novel movement-imagery-based brain-computer interface (BCI) for untrained subjects without employing machine learning techniques. The development of BCI consisted of several steps. First, spline Laplacian analysis was performed. Next, time-frequency analysis was applied to determine the optimal frequency range and latencies of the electroencephalograms (EEGs). Finally, trials were classified as right or left based on β-band event-related synchronization using the cumulative distribution function of pretrigger EEG noise. To test the performance of the BCI, EEGs during the execution and imagination of right/left wrist-bending movements were measured from 63 locations over the entire scalp using eight healthy subjects. The highest classification accuracies were 84.4% and 77.8% for real movements and their imageries, respectively. The accuracy is significantly higher than that of previously reported machine-learning-based BCIs in the movement imagery task (paired t-test, p < 0.05). It has also been demonstrated that the highest accuracy was achieved even though subjects had never participated in movement imageries.

Wireless sensor networks are comprised of several sensor nodes that communicate via wireless technology. Locating the sensor nodes is a fundamental problem in developing applications for wireless sensor networks. In this paper, we introduce a distributed localization scheme, called the Rectangle Overlapping Approach (ROA), using a mobile beacon with GPS and a directional antenna. The node locations are computed by performing simple operations that rely on the rotation angle and position of the mobile beacon. Simulation results show that the proposed scheme is very efficient and that the node positions can be determined accurately when the beacon follows a random waypoint movement model.

For the control of multiple servomotors in a humanoid robots, a communication system is proposed. In the system, DC electric power, command/response signals and a common clock signal for precise synchronous movement of the servomotors are transmitted via the same wiring with a multi-drop bus. Because of the bandwidth limitation, the common clock signal and the command/response signals overlap each other. It is confirmed that the coexistence of both signals is possible by using interference cancellation at the reception of command/response signals.

In this letter, we propose a novel speech enhancement algorithm based on data-driven residual gain estimation. The entire system consists of two stages. At the first stage, a conventional speech enhancement algorithm enhances the input signal while estimating several signal-to-noise ratio (SNR)-related parameters. The residual gain, which is estimated by a data-driven method, is applied to further enhance the signal at the second stage. A number of experimental results show that the proposed speech enhancement algorithm outperforms the conventional speech enhancement technique based on soft decision and the data-driven approach using SNR grid look-up table.

The cooperative relay network exploits the space diversity gain by allowing cooperation among users to improve transmission quality. It is an important issue to identify the cluster-head (or relay node) and its members who are to cooperate. The cluster-head consumes more battery power than an ordinary node since it has extra responsibilities, i.e., ensuring the cooperation of its members' transmissions; thereby the cluster-head has a lower throughput than the average. Since users are joining or departing the clusters from time to time, the network topology is changing and the network may not be stable. How to balance the fairness among users and the network stability is a very interesting topic. This paper proposes an adaptive weighted clustering algorithm (AWCA), in which the weight factors are introduced to adaptively control both the stability and fairness according to the number of arrival users. It is shown that when the number of arrival users is large, AWCA has the life time longer than FWCA and similar to SWCA and that when the number of arrival users is small, AWCA provides fairness higher than SWCA and close to FWCA.

This paper proposes a high-accuracy sub-pixel registration framework based on phase correlation for noisy images. First we introduce a denoising module, where the edge-preserving filter is adopted. This strategy not only filters off the noise but also preserves most of the original image signal. A confidence-weighted optimization module is then proposed to fit the linear phase plane discriminately and to achieve sub-pixel shifts. Experiments demonstrate the effectiveness of the combination of our modules and improvements of the accuracy and robustness against noise compared to other sub-pixel phase correlation methods in the Fourier domain.

Iterative synthesis methods for making aware of wire congestion are proposed for a multi-context dynamically reconfigurable processor (DRP) with a large number of processing elements (PEs) and programmable-wire connections. Although complex data-paths can be synthesized using the programmable-wire, its delay is long especially when wire connections are congested. We propose two iterative synthesis techniques between a high-level synthesizer (HLS) and the place & route tool to shorten the prolonged wire delay. First, we feed back wire delays for each context to a scheduler in the HLS. The experimental results showed that a critical-path delay was shorten by 21% on average for applications with timing closure problems. Second, we skip the routing and estimate wire delays based on the congestion. The synthesis time was shorten to 1/3 causing delay improvement rate degradation at two points on average.

This paper presents a verification and analysis tool set for embedded systems. Recently, the development scale of embedded systems has been increasing since they are used for mobile systems, automobile platforms, and various consumer systems with rich functionality. This has increased the amount of time and cost needed to develop them. Consequently, it is very important to develop tools to reduce development time and cost. This paper describes a tool set consisting of three tools to enhance the efficiency of embedded system design. The first tool is an integrated tool platform. The second is a remote debugging system. The third is a clock-accurate verification system based on a field-programmable gate array (FPGA) for custom embedded systems. This tool set promises to significantly reduce the time and cost needed to develop embedded systems.