To improve the data rate in OFDMA-based wireless networks, Carrier Aggregation (CA) technology has been included in the LTE-Advanced standard. Different Carrier Component (CC) capacities of users under the same eNodeB (eNB, i.e. Base Station) make it challenging to allocate resources with CA. In this paper, we jointly consider CC and Resource Block (RB) assignments, and power allocation to achieve proportional fairness in the long term. The goal of the problem is to maximize the overall throughput with fairness consideration. We consider a more general CC assignment framework that each User Equipment (UE) (i.e. Mobile Station) can support any number of CCs. Furthermore, we have proved the problem is NP-hard, even if power is equally allocated to RBs. Thus, first an optimal RB assignment and power allocation algorithm is proposed and then a carrier aggregation enabled joint resource allocation algorithm called CARA is proposed. By jointly considering CC and RB assignments, and power allocation, the proposed approach can achieve better performance. Simulation results show the proposed algorithm can significantly improve performance, e.g., total throughput compared with the existing algorithm.

This paper describes low-power dynamic multiple-input and multiple-output (MIMO) detection for a 4×4 MIMO-orthogonal frequency-division multiplexing (MIMO-OFDM) receiver. MIMO-OFDM systems achieve high-speed and large capacity communications. However, they impose high computational cost in MIMO detection when separating spatially multiplexed signals and they consume vast amounts of power. We propose low-power dynamic MIMO detection that controls detection speed according to wireless environments. The power consumption is reduced by dynamic voltage and frequency scaling (DVFS) that controls the operating voltage and clock frequency in the MIMO detector. We implemented dynamic MIMO detection in a pipelined minimum mean square error (MMSE) MIMO detector that we developed in our previous work. A power saving of 92% was achieved under lowest clock frequency mode conditions.

This paper deals with an integral equation method for analyzing the diffraction of a transverse magnetic (TM) plane wave by a perfectly conductive periodic surface. In the region below the periodic surface, the extinction theorem holds, and the total field vanishes if the field solution is determined exactly. For an approximate solution, the extinction theorem does not hold but an extinction error field appears. By use of an image Green's function, new formulae are given for the extinction error field and the mean square extinction error (MSEE), which may be useful as a validity criterion. Numerical examples are given to demonstrate that the formulae work practically even at a critical angle of incidence.

In the shadow theory, a new description and a physical mean at a low grazing limit of incidence on gratings in the two dimensional scattering problem have been discussed. In this paper, by applying the shadow theory to the three dimensional problem of multilayered dielectric periodic gratings, we formulate the oblique primary excitation and introduce the scattering factors through our analytical method, by use of the matrix eigenvalues. In terms of the scattering factors, the diffraction efficiencies are defined for propagating and evanescent waves with linearly and circularly polarized incident waves. Numerical examples show that when an incident angle becomes low grazing, only specular reflection occurs with the reflection coefficient -1, regardless of the incident polarization. It is newly found that in a circularly polarized incidence case, the same circularly polarized wave as the incident wave is specularly reflected at a low grazing limit.

We analyzed polarization characteristics of gammadion-shaped planar chiral nano-gratings (PCNGs), using Jones matrix and FDTD simulation. Optical activity (OA) was found to take place at wavelengths where long-lifetime modes appeared in the chiral layer. Among two kinds of resonance phenomena that concern the extension of the lifetime, guided-mode resonance and Fabry-Perot resonance, the latter was found to be a key to generate practically-important, broad peaks in the OA spectrum. Through the calculation of dispersion relations of Bloch modes in the chiral layer, we showed that the interference of multiple modes with group velocity dispersion played a critical role in the generation of such long-lifetime modes.

In this paper, the authors present a CAM-based Information Detection Hardware System for fast, exact and approximate image matching on 2-D data, using FPGA. The proposed system can be potentially applied to fast image matching with various required search patterns, without using search principles. In designing the system, we take advantage of Content Addressable Memory (CAM) which has parallel multi-match mode capability and has been designed, using dual-port RAM blocks. The system has a simple structure, and does not employ any Central Processor Unit (CPU) or complicated computations.

We implemented a scalar multiplication method over elliptic curves using division polynomials. We adapt an algorithm for computing elliptic nets proposed by Stange. According to our experimental results, the scalar multiplication method using division polynomials is faster than the binary method in an affine coordinate system.

In this letter, an estimation technique for multiple CFOs is proposed that uses the properties of the Zadoff-Chu (ZC) sequence. After initial estimation of multiple CFOs by using the properties of the ZC sequence, accurate estimates are obtained in the proposed technique by an iterative procedure. The proposed technique can be applied to LTE-based CoMP systems where ZC sequences are used to generate synchronization signals in downlink and random access preambles in uplink.

Coupled with the discrete wavelet transform, SPIHT (set partitioning in hierarchical trees) is a highly efficient image compression technique that allows for progressive transmission. One problem, however, is that its decoding can be extremely sensitive to bit errors in the code sequence. In this paper, we address the issue of transmitting SPIHT-encoded images via noisy channels, wherein errors are inevitable. The communication scenario assumed in this paper is that the transmitter cannot get any acknowledgement from the receiver. In our scheme, the original SPIHT code sequence is first segmented into packets. Each packet is classified as either a CP (critical packet) or an RP (refinement packet). For error control, cyclic redundancy check (CRC) is incorporated into each packet. By checking the CRC check sum, the receiver is able to tell whether a packet is correctly received or not. In this way, the noisy channel can be effectively modeled as an erasure channel. For unequal error protection (UEP), each of those packets are repeatedly transmitted for a few times, as determined by a process called diversity allocation (DA). Two DA algorithms are proposed. The first algorithm produces a nearly optimal decoded image (as measured in the expected signal-to-noise ratio). However, its computation cost is extremely high. The second algorithm works in a progressive fashion and is naturally compatible with progressive transmission. Its computation complexity is extremely low. Nonetheless, its decoded image is nearly as good. Experimental results show that the proposed scheme significantly improves the decoded images. They also show that making distinction between CP and RP results in wiser diversity allocation to packets and thus produces higher quality in the decoded images.

As businesses are increasingly relying on the cloud to host their services, cloud providers are striving to offer guaranteed and highly-available resources. To achieve this goal, recent proposals have advocated to offer both computing and networking resources in the form of Virtual Data Centers (VDCs). Subsequently, several attempts have been made to improve the availability of VDCs through reliability-aware resource allocation schemes and redundancy provisioning techniques. However, the research to date has not considered the heterogeneity of the underlying physical components. Specifically, it does not consider recent findings showing that failure rates and availability of data center equipments can vary significantly depending on various parameters including their types and ages. To address this limitation, in this paper we propose a High-availability Virtual Infrastructure management framework (Hi-VI) that takes into account the heterogeneity of cloud data center equipments to dynamically provision backup resources in order to ensure required VDC availability. Specifically, we propose a technique to compute the availability of a VDC that considers both (1) the heterogeneity of data center networking and computing equipments in terms of failure rates and availability, and (2) the number of redundant virtual nodes and links provisioned as backups. We then leverage this technique to propose an allocation scheme that jointly provisions resources for VDCs and backups of virtual components with the goal of achieving the required VDC availability while minimizing energy costs. Through simulations, we demonstrate the effectiveness of our framework compared to heterogeneity-oblivious solutions.

As one of organic electroluminescent (EL) materials, we developed a method of fabricating an ink using low molecular- weight materials with a long emission lifetime for application to the inkjet method. Although the emission lifetime is usually long for low molecular-weight materials, their high manufacturing cost due to the necessity of vapor deposition is a disadvantage. We utilized the low molecular-weight material, tris-(8-hydroxyquinoline) aluminum (Alq3), and investigated its dispersibility in a solvent in which it has low solubility. In addition, we ascertained whether the material could maintain its photoluminescence characteristic under the irradiation of ultraviolet rays by investigating the emission of photoluminescence. Alq3 was crystallized into nanosize crystals, whose surface was then coated with a primary amine by the gas evaporation method. The fabricated ink contained crystals with an average size of 250nm and high dispersibility in tetradecane, in which Alq3 is insoluble. Thus, we made it possible to carry out an inkjet method with low molecular weight EL materials.

Recently, fuzzy set theory has been widely employed in building portfolio selection models where uncertainty plays a role. In these models, future security returns are generally taken for fuzzy variables and mathematical models are then built to maximize the investment profit according to a given risk level or to minimize a risk level based on a fixed profit level. Based on existing works, this paper proposes a portfolio selection model based on fuzzy birandom variables. Two original contributions are provided by the study: First, the concept of technical analysis is combined with fuzzy set theory to use the security returns as fuzzy birandom variables. Second, the fuzzy birandom Value-at-Risk (VaR) is used to build our model, which is called the fuzzy birandom VaR-based portfolio selection model (FBVaR-PSM). The VaR can directly reflect the largest loss of a selected case at a given confidence level and it is more sensitive than other models and more acceptable for general investors than conventional risk measurements. To solve the FBVaR-PSM, in some special cases when the security returns are taken for trapezoidal, triangular or Gaussian fuzzy birandom variables, several crisp equivalent models of the FBVaR-PSM are derived, which can be handled by any linear programming solver. In general, the fuzzy birandom simulation-based particle swarm optimization algorithm (FBS-PSO) is designed to find the approximate optimal solution. To illustrate the proposed model and the behavior of the FBS-PSO, two numerical examples are introduced based on investors' different risk attitudes. Finally, we analyze the experimental results and provide a discussion of some existing approaches.

This paper presents an application of the constained interpolation profile basis set (CIP-BS) method to electromagnetic fields analyses. Electromagnetic fields can be expanded in terms of multi-dimensional CIP basis functions, and the Galerkin method can then be applied to obtain a system of linear equations. In the present study, we focus on a two-dimensional problem with TMz polarization. In order to examine the precision of the CIP-BS method, TE202 resonant mode in a rectangular cavity is analyzed. The numerical results show that CIP-BS method has better performance than the finite-difference time-domain (FDTD) method when the time step is small. Then an absorbing boundary condition based on the perfectly matched layer (PML) is formulated, and the absorption performance is demonstrated. Finally, the propagation in an inhomogeneous medium is computed by using the proposed method, and it is observed that in the CIP-BS method, smooth variation of material constants is effectively formulated without additional computational costs, and that accurate results are obtained in comparison with the FDTD method even if the permittivity is high.

“How to get the original ideas” is the fundamental and critical issue for the researchers in science and technology. In this paper, the author writes his experiences concerning how he could encounter the interesting and original ideas of three research subjects, i.e., the accelerating medium effect, the guided-mode extracted integral equation and the surface plasmon gap waveguide.

Space-time block code (STBC) with complex orthogonal designs achieves full diversity with a simple maximum-likelihood (ML) decoding, however, do not achieve a full transmission rate for more than two antennas. To attain a higher transmission rate, STBC with quasi-orthogonal designs were proposed, whereas there are interference terms caused by relaxing the orthogonality. It has an impact on decoding complexity because a receiver needs to decode two symbols at a time. Moreover, QO-STBC does not achieve full diversity. In this paper, we propose a scheme which makes possible to decode symbols one by one, and two schemes which gain full transmission diversity by upsetting the balance of the transmit power and rotating constellation.

Prediction of cross-talk is an important facet of multicore fiber (MCF) design. Several approaches for estimating cross-talk in MCF have been proposed but none are faultless, especially when applied to MCF with heterogeneous cores. We propose a new calculation approach that attempts to solve this problem. In our approach, cross-talk in multicore fibers is estimated by coupled power theory. The coefficients in the coupled power equation are theoretically calculated by the central limit theorem and by quantum mechanical time-dependent perturbations. The results from our calculations agree with those of Monte Carlo simulations of heterogeneous MCFs.

In multi-static sonar systems, the least square (LS) and maximum likelihood (ML) are the typical estimation criteria for target location estimation. The LS localizaiton has the advantage of low computational complexity. On the other hand, the performance of LS can be degraded severely when the target lies on or around the straight line between the source and receiver. We examine mathematically the reason for the performance degradation of LS. Then, we propose a location adaptive — least square (LA-LS) localization that removes the weakness of the LS localizaiton. LA-LS decides the receivers that produce abnormally large measurement errors with a proposed probabilistic measure. LA-LS achieves improved performance of the LS localization by ignoring the information from the selected receivers.

Cooperative wireless communication is a communication mechanism to attain diversity through virtual antenna array that is formed by sharing resources among different users. Different strategies of resource utilization such as amplify-and-forward (AF) and decode-and-forward (DF) already exist in cooperative networks. Although the implementation of these strategies is simple, their utilization of the channel state information (CSI) is generally poor. As a result, the outage and bit error rate (BER) performances need much more improvement in order to satisfy the upcoming high data rate demands. For that to happen the spectral efficiency supported by a wireless system at a very low outage probability should be increased. In this paper a new approach, based on the previously existing ones, called CSI directed estimate and forward (CDEF) with a reduced estimation domain is proposed. A closed form solution for the optimal signal estimation at the relay using minimum mean square error (MMSE) as well as a possible set reduction of the estimation domain is given. It will be shown that this new strategy attains better symbol error rate (SER) and outage performance than AF or DF when the source relay link is comparatively better than the relay destination link. Simulation results also show that it has got better spectral efficiency at low outage probability for a given signal to noise ratio (SNR) as well as for a fixed outage probability in any operating SNR range.

In this paper, a simple yet efficient texture representation is proposed for texture classification by exploring the joint statistics of local quantized patterns (jsLQP). In order to combine information of different domains, the Gaussian derivative filters are first employed to obtain the multi-scale gradient responses. Then, three feature maps are generated by encoding the local quantized binary and ternary patterns in the image space and the gradient space. Finally, these feature maps are hybridly encoded, and their joint histogram is used as the final texture representation. Extensive experiments demonstrate that the proposed method outperforms state-of-the-art LBP based and even learning based methods for texture classification.

In cognitive radio networks, the dynamic traffic of the primary user can lead to not only the spectrum sensing performance degradation, but also co-channel interference between primary user and secondary user, and, furthermore, the secondary system throughput can be decreased. Taking into account the impact of the dynamic primary-user traffic on spectrum sensing performance and the secondary throughput, we study the optimization problem of maximizing the secondary throughput under the constraints of probability of detection, average interference and transmit power budget, and derive its optimal solution. The optimal power allocation scheme and the algorithm that can find the optimal sensing time are also proposed. The proposed algorithm is of great practical significance in the scenario where primary-user traffic varies very quickly, for example, in public safety spectrum band.