Many selected mapping (SLM) schemes have been proposed to reduce the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signal sequences. In this paper, an efficient selection (ES) method of the OFDM signal sequence with minimum PAPR among many alternative OFDM signal sequences is proposed; it supports various SLM schemes. Utilizing the fact that OFDM signal components can be sequentially generated in many SLM schemes, the generation and PAPR observation of the OFDM signal sequence are processed concurrently. While the u-th alternative OFDM signal components are being generated, by applying the proposed ES method, the generation of that alternative OFDM signal components can be interrupted (or stopped) according to the selection criteria of the best OFDM signal sequence in the considered SLM scheme. Such interruption substantially reduces the average computational complexity of SLM schemes without degradation of PAPR reduction performance, which is confirmed by analytical and numerical results. Note that the proposed method is not an isolated SLM scheme but a subsidiary method which can be easily adopted in many SLM schemes in order to further reduce the computational complexity of considered SLM schemes.

The traffic of the future aggregation network will dynamically change not only in volume but also destination to support the application of virtualization technology to network edge equipment to achieve cost-effectiveness. Therefore, future aggregation network will have to accommodate this traffic cost-effectively, despite dynamic changes in both volume and destination. To correspond to this trend, in this paper, we propose an optical layer 2 switch network based on bufferless optical time division multiplexing (TDM) and dynamic bandwidth allocation to achieve a future aggregation network cost-effectively. We show here that our proposed network architecture effectively reduced the number of wavelengths and optical interfaces by application of bufferless optical TDM technology and dynamic bandwidth allocation to the aggregation network.

The Euler number is an important topological property in a binary image, and it can be computed by counting certain bit-quads in the binary image. This paper proposes a further improved bit-quad-based algorithm for computing the Euler number. By scanning image rows two by two and utilizing the information obtained while processing the previous pixels, the number of pixels to be checked for processing a bit-quad can be decreased from 2 to 1.5. Experimental results demonstrated that our proposed algorithm significantly outperforms conventional Euler number computing algorithms.

It is known that in the selected mapping (SLM) scheme for orthogonal frequency division multiplexing (OFDM), correlation (CORR) metric outperforms the peak-to-average power ratio (PAPR) metric in terms of bit error rate (BER) performance. It is also well known that four times oversampling is used for estimating the PAPR performance of continuous OFDM signal. In this paper, the oversampling effect of OFDM signal is analyzed when CORR metric is used for the SLM scheme in the presence of nonlinear high power amplifier. An analysis based on the correlation coefficients of the oversampled OFDM signals shows that CORR metric of two times oversampling in the SLM scheme is good enough to achieve the same BER performance as four times and 16 times oversampling cases. Simulation results confirm that for the SLM scheme using CORR metric, the BER performance for two times oversampling case is almost the same as that for four and 16 times oversampling cases.

Recent small cube satellites use higher frequency bands such as Ku-band for higher throughput communications. This requires high-frequency link in an earth radio station as well. As one of the solutions, we propose usage of bidirectional radio-on-fiber link employing a wavelength multiplexing scheme. It was numerically shown that the response linearity of the electro-absorption modulator integrated laser (EML) is sufficient and that the spurious emissions are lower enough or can be reduced by the radio-frequency filters. From the frequency response and the single-sideband phase noise measurements, the EML was proved to be used in a radio-on-fiber system of the cube satellite earth station.

This paper presents an Adapting Block-Propagative Background Subtraction (ABPBGS) designed for Ultra High Definition Television (UHDTV) foreground detection. The main idea is to detect block after block along the objects in order to skip all areas of the image in which there is no moving object. This is particularly interesting for UHDTV when the objects of interest could represent not even 0.1% of the total area. From a seed block which is determined in a previous iteration, the detection will spread along an object as long as it detects a part of that object. A block history map guaranties that each block is processed only once. Moreover, only small blocks are loaded and processed, thus saving computational time and memory usage. The process of each block is independent enough to be easily parallelized. Compared to 9 state-of-the-art works, the ABPBGS achieved the best results with an average global quality score of 0.57 (1 being the maximum) on a dataset of 4K and 8K UHDTV sequences developed for this work. None of the state-of-the-art methods could process 4K videos in reasonable time while the ABPBGS has shown an average speed of 5.18fps. In comparison, 5 of the 9 state-of-the-art methods performed slower on 270p down-scale version of the same videos. The experiments have also shown that for the process an 8K UHDTV video the ABPBGS can divide the memory required by about 24 for a total of 450MB.

The technique of partial transmit sequences (PTS) is effective in reducing the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signals. However, the conventional PTS (CPTS) scheme has high computation complexity because it needs several inverse fast Fourier transform (IFFT) units and an optimization process to find the candidate signal with the lowest PAPR. In this paper, we propose a new low-complexity PTS scheme for OFDM systems, in which a hybrid subblock partition method (SPM) is used to reduce the complexity that results from the IFFT computations and the optimization process. Also, the PAPR reduction performance of the proposed PTS scheme is further enhanced by multiplying a selected subblock with a predefined phase rotation vector to form a new subblock. The time-domain signal of the new subblock can be obtained simply by performing a circularly-shift-left operation on the IFFT output of the selected subblock. Computer simulations show that the proposed PTS scheme achieves a PAPR reduction performance close to that of the CPTS scheme with the pseudo-random SPM, but with much lower computation complexity.

In this paper, we consider a distributed power control scheme that can maximize overall capacity of an interference-limited wireless system in which the same radio resource is spatially reused among different transmitter-receiver pairs. This power control scheme employs a gradient-descent method in each transmitter, which adapts its own transmit power to co-channel interference dynamically to maximize the total weighted sum rate (WSR) of the system over a given interval. The key contribution in this paper is to propose a common feedback channel, over which a backward physical signal is accumulated for computing the gradient of the transmit power in each transmitter, thereby significantly reducing signaling overhead for the distributed power control. We show that the proposed power control scheme can achieve almost 95% of its theoretical upper WSR bound, while outperforming the non-power-controlled system by roughly 63% on average.

Wireless sensor networks play an important role in several industries. Ad-hoc networks with multi-hop transmissions are considered suitable for wireless sensor networks because of their high scalability and low construction cost. However, a lack of centralized control makes it difficult to respond to congestion when system capacity is exceeded. Therefore, the analysis of system capacity is a critical issue for system design. In this paper, we propose a novel zone division model to analyze the capacity of multi-hop wireless sensor networks using carrier sense multiple access with collision avoidance protocols. We divide the one-hop area to a gateway (GW) into two zones: an outer zone, where access nodes (ANs) can relay packets from multi-hop ANs, and an inner zone where ANs cannot relay packets. Using this approach, we calculate the packet loss for each zone to estimate the capacity, considering the difference in the communication range of the GW and ANs, as well as the collision with hidden nodes. Comparisons with simulation results and the conventional method show that our model achieves higher estimation accuracy.

The iterative random subdivision of rectangles is used as a generation model of networks in physics, computer science, and urban planning. However, these researches were independent. We consider some relations in them, and derive fundamental properties for the average lifetime depending on birth-time and the balanced distribution of rectangle faces.

A re-configurable wavelength de-multiplexer for wave-length-division-multiplexed (WDM) radio-over-fiber (RoF) systems, which is specially designed for delivering frequency-modulated continuous-wave (FM-CW) signals, is newly developed. The principle and characteristics of the developed de-multiplexer are described in detail. Then the de-multiplexing performances of 4-channel WDM 32-GHz-band, 8-channel WDM 48-GHz-band, and 5-channel WDM 96-GHz-band FM-CW RoF signals are evaluated with the de-multiplexer.

This paper presents a novel peer-to-peer protocol to efficiently distribute virtual machine images in a datacenter. A primary idea of it is to improve the performance of peer-to-peer content delivery by employing deduplication to take advantage of similarity both among and within VM images in cloud datacenters. The efficacy of the proposed scheme is validated through an evaluation that demonstrates substantial performance gains.

In this paper, we propose an analog cancellation scheme for multipath self-interference channels in full-duplex wireless orthogonal frequency-division multiplexing (OFDM) systems. The conventional approaches emulate the radio-frequency (RF) self-interference signals by passing the RF transmit signals through delay lines and programmable attenuators. By contrast, our proposed scheme computes the phase-rotated and weighted versions of the baseband transmit signals in the baseband domain, which are simply upconverted to obtain the emulated RF self-interference signals. Numerical results are presented to verify the suppression performance of the proposed scheme.

In this letter, we present a method for automatic mura detection for display film using the efficient decision of cut-off frequency with DCT and mask filtering with wavelet transform. First, the background image including reflected light is estimated using DCT with adaptive cut-off frequency, and DWT is applied to background-removed images for generating mura mask. Then, a mura mask is generated by separating low-frequency noise in the approximation coefficients. Lastly, mura is detected by applying mura mask filtering to the detail coefficients. According to the comparison by Semu index, the results from the proposed method are superior to those from the existing methods. This indicates that the proposed method is high in reliability.

This paper proposes a graph-theory-based Euler number computing algorithm. According to the graph theory and the analysis of a mask's configuration, the Euler number of a binary image in our algorithm is calculated by counting four patterns of the mask. Unlike most conventional Euler number computing algorithms, we do not need to do any processing of the background pixels. Experimental results demonstrated that our algorithm is much more efficient than conventional Euler number computing algorithms.

Robust yet efficient techniques for detecting and tracking targets in infrared (IR) images are a significant component of automatic target recognition (ATR) systems. In our previous works, we have proposed infrared target detection and tracking systems based on sparse representation method. The proposed infrared target detection and tracking algorithms are based on sparse representation and Bayesian probabilistic techniques, respectively. In this paper, we adopt Naïve Bayes Nearest Neighbor (NBNN) that is an extremely simple, efficient algorithm that requires no training phase. State-of-the-art image classification techniques need a comprehensive learning and training step (e.g., using Boosting, SVM, etc.) In contrast, non-parametric Nearest Neighbor based image classifiers need no training time and they also have other more advantageous properties. Results of tracking in infrared sequences demonstrated that our algorithm is robust to illumination changes, and the tracking algorithm is found to be suitable for real-time tracking of a moving target in infrared sequences and its performance was quite good.

The dynamic routing and wavelength assignment (RWA) problem in wavelength division multiplexing (WDM) optical networks with sparse wavelength conversion has been a hot research topic in recent years. An optimized algorithm based on a multiple-layered interconnected graphic model (MIG) for the dynamic RWA is presented in this paper. The MIG is constructed to reflect the actual WDM network topology. Based on the MIG, the link cost is given by the conditions of available lightpath to calculate an initial solution set of optimal paths, and by combination with path length, the optimized solution using objective function is determined. This approach simultaneously solves the route selection and wavelength assignment problem. Simulation results demonstrate the proposed MIG-based algorithm is effective in reducing blocking probability and boosting wavelength resource utilization compared with other RWA methods.

Industrial applications such as automotive ones require a cheap communication mechanism to send out communication messages from node to node by their deadline time. This paper presents a design paradigm in which we optimize both assignment of a network node to a bus and slot multiplexing of a FlexRay network system under hard real-time constraints so that we can minimize the cost of wire harness for the FlexRay network system. We present a cost minimization problem as a non-linear model. We developed a network synthesis tool which was based on simulated annealing. Our experimental results show that our design paradigm achieved a 50.0% less cost than a previously proposed approach for a virtual cost model.

Although multi-user multiple-input multiple-output (MI-MO) systems provide high data rate transmission, they may suffer from interference. Block diagonalization and eigenbeam-space division multiplexing (E-SDM) can suppress interference. The transmitter needs to determine beamforming weights from channel state information (CSI) to use these techniques. However, MIMO channels change in time-varying environments during the time intervals between when transmission parameters are determined and actual MIMO transmission occurs. The outdated CSI causes interference and seriously degrades the quality of transmission. Channel prediction schemes have been developed to mitigate the effects of outdated CSI. We evaluated the accuracy of prediction of autoregressive (AR)-model-based prediction and Lagrange extrapolation in the presence of channel estimation error. We found that Lagrange extrapolation was easy to implement and that it provided performance comparable to that obtained with the AR-model-based technique.

Tenant network provisioning in multi-tenancy data centers is time-consuming and error-prone due to the need to configure network devices with hundreds of parameter values (e.g., VLAN ID, IP address) determined according to complicated operational rules. Past works have aimed to automate such operational rule-based provisioning processes by implementing data center-specific provisioning programs, but a crucial problem is the high cost of adapting the programs to suit multiple data centers. In this paper, we aim to solve this problem by enabling to describe the provisioning processing, which has been hard-coded programs in conventional approaches, in easy-to-edit “provisioning template” files. The key component of the provisioning template is the parameter decision rule, which is a declarative abstract representation of parameter dependency and parameter assignment. We design the provisioning template so that it can handle various configuration items while preserving its editability for tenant provisioning. We design and implement the provisioning platform, and the evaluation based on a production data center shows that the provisioning platform can adopt multiple data centers with a single program, leading to less development cost compared to past approaches (i.e., program development for each data center).