A non-linear extension of generalized hyperplane approximation (GHA) method is introduced in this letter. Although GHA achieved a high-confidence result in motion parameter estimation by utilizing the supervised learning scheme in histogram of oriented gradient (HOG) feature space, it still has unstable convergence range because it approximates the non-linear function of regression from the feature space to the motion parameter space as a linear plane. To extend GHA into a non-linear regression for larger convergence range, we derive theoretical equations and verify this extension's effectiveness and efficiency over GHA by experimental results.

Radio frequency over fiber (RoF) advanced technology is already integrated into current 3G and 4G radio access networks in which the digital unit and remote radio head equipped with nonlinear high power amplifiers (HPAs) are connected through the RoF-based fronthaul links. In this study, we investigated the degradation in the adjacent channel leakage ratio (ACLR) of equipment with the adaptive linearizer RF HPA when both the direct and feedback paths of the transmitting system include RoF links. We show that an ACLR exceeding -57dBc @ 5-MHz offset, which completely satisfies the requirements of the 3GPP technical specifications, can be achieved for a 20-W-class Doherty power amplifier linearized through commercial RoF links. Experiments showed that the achieved ACLR strongly depends on the RoF-link noise figure and that most of the nonlinear distortions caused by RoF can be completely suppressed with the proposed joint linearization approach for simultaneous linearization of RoF and HPA nonlinearities with a single common “joint” linearizer. Experimental results confirm significant ACLR performance enhancements as a result of RoF noise floor reduction, which is achieved under RoF driving conditions optimized together with joint RoF and HPA linearization. Our joint linearization approach via RoF links is confirmed to be applicable for next-generation mobile fronthaul architectures.

Recovery of low-rank matrices has seen significant activity in many areas of science and engineering, motivated by theoretical results for exact reconstruction guarantees and interesting practical applications. Recently, numerous methods incorporated the nuclear norm to pursue the convexity of the optimization. However, this greatly restricts its capability and flexibility in dealing with many practical problems, where the singular values have clear physical meanings. This paper studies a generalized non-convex low-rank approximation, where the singular values are in lp-heuristic. Then specific results are derived for image restoration, including denoising and deblurring. Extensive experimental results on natural images demonstrate the improvement of the proposed method over the recent image restoration methods.

The recently proposed distributed adaptive direct position determination (D-ADPD) algorithm provides an efficient way to locating a radio emitter using a sensor network. However, this algorithm may be suboptimal in the situation of colored emitted signals. We propose an enhanced distributed adaptive direct position determination (EDA-DPD) algorithm. Simulations validate that the proposed EDA-DPD outperforms the D-ADPD in colored emitted signals scenarios and has the similar performance with the D-ADPD in white emitted signal scenarios.

Let R=Z4 be the integer ring mod 4 and C be a linear code over R. The code C is called a triple cyclic code of length (r, s, t) over R if the set of its coordinates can be partitioned into three parts so that any cyclic shift of the coordinates of the three parts leaves the code invariant. These codes can be viewed as R[x]-submodules of R[x]/×R[x]/×R[x]/. In this paper, we determine the generator polynomials and the minimum generating sets of this kind of codes.

A negative capacitor is fabricated using poly(vinylidene fluoride-trifluoroethylene) copolymer and connected in series to an a-IZO TFT. It is experimentally demonstrated that the negative capacitance of the negative capacitor can create steep switching in the a-IZO TFT (e.g., a subthreshold slope change from 342mV/decade to 102mV/decade at room-temperature).

In this paper, a self optimization beamforming null control (SOBNC) scheme is proposed. There is a need of maintaining signal to interference plus noise ratio (SINR) threshold to control modulation and coding schemes (MCS) in recent technologies like Wi-Fi, Long Term Evolution (LTE) and Long Term Evolution Advanced (LTE-A). Selection of MCS depends on the SINR threshold that allows maintaining key performance index (KPI) like block error rate (BLER), bit error rate (BER) and throughput at certain level. The SOBNC is used to control the antenna pattern for SINR estimation and improve the SINR performance of the wireless communication systems. The nulling comes with a price; if wider nulls are introduced, i.e. more number of nulls are used, the 3dB beam-width and peak side lobe level (SLL) in antenna pattern changes critically. This paper proposes a method which automatically controls the number of nulls in the antenna pattern as per the changing environment based on adaptive-network based fuzzy interference system (ANFIS) to maintain output SINR level higher or equal to the required threshold. Finally, simulation results show a performance superiority of the proposed SOBNC compared with minimum mean square error (MMSE) based adaptive nulling control algorithm and conventional fixed null scheme.

Because accurate position information plays an important role in wireless sensor networks (WSNs), target localization has attracted considerable attention in recent years. In this paper, based on target spatial domain discretion, the target localization problem is formulated as a sparsity-seeking problem that can be solved by the compressed sensing (CS) technique. To satisfy the robust recovery condition called restricted isometry property (RIP) for CS theory requirement, an orthogonalization preprocessing method named LU (lower triangular matrix, unitary matrix) decomposition is utilized to ensure the observation matrix obeys the RIP. In addition, from the viewpoint of the positioning systems, taking advantage of the joint posterior distribution of model parameters that approximate the sparse prior knowledge of target, the sparse Bayesian learning (SBL) approach is utilized to improve the positioning performance. Simulation results illustrate that the proposed algorithm has higher positioning accuracy in multi-target scenarios than existing algorithms.

In this paper, we propose a channel-unaware algorithm to suppress the narrowband interference (NBI) for the time synchronization, where multiple antennas are equipped at the receiver. Based on the fact that the characteristics of synchronization signal are different from those of NBI in both the time and spatial domain, the proposed algorithm suppresses the NBI by utilizing the multiple receive antennas in the eigen domain of NBI, where the eigen domain is obtained from the time domain statistical information of NBI. Because time synchronization involves incoherent detection, the proposed algorithm does not use the desired channel information, which is different from the eigen domain interference rejection combining (E-IRC). Simulation results show, compared with the traditional frequency domain NBI suppression technique, the proposed algorithm has about a 2 dB gain under the same probability of detection.

As dual-polarized multiple-input multiple-output (MIMO) technique has little inter-antenna interference, it provides high data rate and reliability to a user equipment (UE) with the low system complexity. In the joint transmission (JT) technique of the coordinated multi-point (CoMP) transmission system, multiple transmission points (TPs) transmit the same data to the UE so that the UE can get the diversity gain and the high reliability, especially at the cell-edge. However, the system performance of the dual-polarized MIMO in the JT technique of CoMP system is very sensitive on the dual-polarized channel state when the channel is asymmetric. In this letter, an improved dual-polarized MIMO scheme for JT of the downlink CoMP transmission system is proposed. This scheme adaptively applies the transmission power to each dual-polarized MIMO antenna and the modulation order of the transmission data according to the channel state information (CSI). System-level simulation results show that the proposed scheme provides better bit-error-rate (BER) performance in the asymmetric dual-polarized channel state than the conventional scheme.

Single-carrier (SC) transmission with space-time block coded (STBC) transmit diversity can achieve good bit error rate (BER) performance. However, in a high mobility environment, the STBC codeword orthogonality is distorted and as consequence, the BER performance is degraded by the interference caused by the orthogonality distortion of STBC codeword. In this paper, we proposed a novel frequency-domain equalization (FDE) for SC-STBC transmit diversity in doubly selective fading channel. Multiple FDE weight matrices, each associated with a different code block, are jointly optimized based on the minimum mean square error (MMSE) criterion taking into account not only channel frequency variation but also channel time variation over the STBC codeword. Computer simulations confirm that the proposed robust FDE achieves BER performance superior to conventional FDE, which was designed based on the assumption of a quasi-static fading.

The so-called numerical alphabet has been established as one of the various memorization systems. It enables numbers to be transformed into words. In that way memorizing numbers is highly alleviated, since words are to be memorized instead of numbers, which is substantially easier. In order to master the technique of transforming numbers into words (for memorizing them), as well as transforming words back to numbers, a person has to practice. Upon adopting the numerical alphabet, one then has to practice various examples and translate numbers into proper words and words into proper numbers. This paper describes the computer application we have developed that helps in this process. To our knowledge, this is the first complete application of this type ever created. We also show the results of the students' number-memorization tests, performed before and after using the application, which show significant improvements.

This paper proposes a new class of Hilbert pairs of almost symmetric orthogonal wavelet bases. For two wavelet bases to form a Hilbert pair, the corresponding scaling lowpass filters are required to satisfy the half-sample delay condition. In this paper, we design simultaneously two scaling lowpass filters with the arbitrarily specified flat group delay responses at ω=0, which satisfy the half-sample delay condition. In addition to specifying the number of vanishing moments, we apply the Remez exchange algorithm to minimize the difference of frequency responses between two scaling lowpass filters, in order to improve the analyticity of complex wavelets. The equiripple behavior of the error function can be obtained through a few iterations. Therefore, the resulting complex wavelets are orthogonal and almost symmetric, and have the improved analyticity. Finally, some examples are presented to demonstrate the effectiveness of the proposed design method.

Given a set of positive-weighted points and a query rectangle r (specified by a client) of given extents, the goal of a maximizing range sum (MaxRS) query is to find the optimal location of r such that the total weights of all points covered by r is maximized. In this paper, we address the problem of processing MaxRS queries over road network databases and propose two new external memory methods. Through a set of simulations, we evaluate the performance of the proposed methods.

In quasi-synchronous frequency-hopping multiple access (QS-FHMA) systems, relative delays are allowed to vary in a domain around the origin. Under such condition, the low hit zone (LHZ) frequency-hopping sequence (FHS) set is more propitious than the conventional FHS set to be applied by the systems. In this paper, a construction based on the interleaving techniques of FHS set with LHZ is proposed. Besides the requirement for this constructed LHZ FHS set to get the optimality or the near optimality with respect to the Peng-Fan-Lee bound is also given. It turns out that the constructed LHZ FHS set has new parameters not covered in the literature, thus it does have great significance in practice.

Novel constructions of inter-group complementary (IGC) sequences are proposed based on Z-periodic complementary (ZPC) sequences and uncorrelated sequence set by taking advantages of interleaved operation. The presented methods can get IGC sequences from interleaving ZPC sequence set. The proposed methods not only can get polyphase IGC sequence set, but also can obtain binary and ternary IGC sequence set. In particular, with the aid of uncorrelated sequence, the number of available groups of IGC sequences from interleaving ZPC sequence set can be chosen with flexibility compared to the existed IGC sequences. The IGC sequences based code division multiple access (CDMA) systems may perform better on bit error rates than conventional sequences based interference-limited CDMA systems. Moreover, the novel IGC sequences may work well in both synchronous and asynchronous operational modes.

This paper considers the beamforming design for energy efficiency transmission over multiple-input and single-output (MISO) channels. The energy efficiency maximization problem is non-convex due to the fractional form in its objective function. In this paper, we propose an efficient method to transform the objective function in fractional form into the difference of two concave functions (DC) form, which can be solved by the successive convex approximation (SCA) algorithm. Then we apply the proposed transformation and pricing mechanism to develop a distributed beamforming optimization for multiuser MISO interference channels, where each user solves its optimization problem independently and only limited information exchange is needed. Numerical results show the effectiveness of our proposed algorithm.

Network virtualization environments (NVEs) are emerging to meet the increasing diversity of demands by Internet users where a virtual network (VN) can be constructed to accommodate each specific application service. In the future Internet, diverse service providers (SPs) will provide application services on their own VNs running across diverse infrastructure providers (InPs) that provide physical resources in an NVE. To realize both efficient resource utilization and good QoS of each individual service in such environments, SPs should perform adaptive control on network and computational resources in dynamic and competitive resource sharing, instead of explicit and sufficient reservation of physical resources for their VNs. On the other hand, two novel concepts, software-defined networking (SDN) and network function virtualization (NFV), have emerged to facilitate the efficient use of network and computational resources, flexible provisioning, network programmability, unified management, etc., which enable us to implement adaptive resource control. In this paper, therefore, we propose an architectural design of network orchestration for enabling SPs to maintain QoS of their applications aggressively by means of resource control on their VNs efficiently, by introducing virtual network provider (VNP) between InPs and SPs as 3-tier model, and by integrating SDN and NFV functionalities into NVE framework. We define new north-bound interfaces (NBIs) for resource requests, resource upgrades, resource programming, and alert notifications while using the standard OpenFlow interfaces for resource control on users' traffic flows. The feasibility of the proposed architecture is demonstrated through network experiments using a prototype implementation and a sample application service on nation-wide testbed networks, the JGN-X and RISE.

In our previous work [12], [13], we introduced generalized feed-forward shift registers (GF2SR, for short) to apply them to secure and testable scan design. In this paper, we introduce another class of generalized shift registers called generalized feedback shift registers (GFSR, for short), and consider the properties of GFSR that are useful for secure scan design. We present how to control/observe GFSR to guarantee scan-in and scan-out operations that can be overlapped in the same way as the conventional scan testing. Testability and security of scan design using GFSR are considered. The cardinality of each class is clarified. We also present how to design strongly secure GFSR as well as GF2SR considered in [13].

Ranking as an important task in information systems has many applications, such as document/webpage retrieval, collaborative filtering and advertising. The last decade has witnessed a growing interest in the study of learning to rank as a means to leverage training information in a system. In this paper, we propose a new learning to rank method, i.e. BLM-Rank, which uses a linear function to score samples and models the pairwise preference of samples relying on their scores under a Bayesian framework. A stochastic gradient approach is adopted to maximize the posterior probability in BLM-Rank. For industrial practice, we have also implemented the proposed algorithm on Graphic Processing Unit (GPU). Experimental results on LETOR have demonstrated that the proposed BLM-Rank method outperforms the state-of-the-art methods, including RankSVM-Struct, RankBoost, AdaRank-NDCG, AdaRank-MAP and ListNet. Moreover, the results have shown that the GPU implementation of the BLM-Rank method is ten-to-eleven times faster than its CPU counterpart in the training phase, and one-to-four times faster in the testing phase.