The design and performance evaluation is presented of a partially adaptive array that suppresses clutter from low elevation angles in atmospheric radar observations. The norm-constrained and directionally constrained minimization of power (NC-DCMP) algorithm has been widely used to suppress clutter in atmospheric radars, because it can limit the signal-to-noise ratio (SNR) loss to a designated amount, which is the most important design factor for atmospheric radars. To suppress clutter from low elevation angles, adding supplemental antennas that have high response to the incoming directions of clutter has been considered to be more efficient than to divide uniformly the high-gain main array. However, the proper handling of the gain differences of main and sub-arrays has not been well studied. We performed numerical simulations to show that using the proper gain weighting, the sub-array configuration has better clutter suppression capability per unit SNR loss than the uniformly divided arrays of the same size. The method developed is also applied to an actual observation dataset from the MU radar at Shigaraki, Japan. The properly gain-weighted NC-DCMP algorithm suppresses the ground clutter sufficiently with an average SNR loss of about 1 dB less than that of the uniform-gain configuration.

To resist algebraic and fast algebraic attacks, Boolean functions used in stream ciphers should have optimal algebraic immunity and good fast algebraic immunity. One challenge of cryptographic Boolean functions is to determine their ability to resist fast algebraic attacks, which can be measured by their fast algebraic immunities. In this letter, we determine the exact values of fast algebraic immunity of the majority function of 2m and 2m+1 variables. This is the first time that the exact values of the fast algebraic immunity of an infinite class of symmetric Boolean functions with optimal algebraic immunity are determined.

Rain attenuation can drastically impact the service availability of satellite communication, especially in the higher frequency bands above 20 GHz, such as the Ka-band. Several countermeasures, including site and time diversity, have been proposed to maintain satellite link service. In this paper, we evaluate the performance of a power boost beam method, which is an adaptive satellite power control technology based on using rain radar data obtained throughout Japan to forecast the power margin. Boost beam analysis is considered for different beam sizes (50, 100, 150, and 200km) and beam numbers (1-4 beams) for a total of 16 cases. Moreover, we used a constant boost power corresponding to the rainfall rate of 20mm/h. The obtained results show that in comparison to the case with no boost, the effective rain intensity in each boost case was reduced.

How to manage the video streaming in future networks is becoming a more and more challenging issue. Recent studies on vehicular networks depict a new picture of the next generation Intelligent Transport System (ITS), with high level road safety and more comfortable driving experience. To cope with the heterogeneous network development for the next generation cellular network, centralized medium control is promising to be employed upon Road Side Unit (RSU). To accommodate the QoS constraints posed by video services in vehicular networks, the scalable video coding (SVC) scheme in H.264/AVC standard family offers spatial and temporal scalabilities in the video dissemination. In this paper, we target the resource allocation and layer selection problem for the multi-user video streaming over highway scenario, by employing SVC coding scheme for the video contents. We propose a Resource Allocation and Layer Selection (RALS) algorithm, which explicitly takes account of the utility value of each Group Of Picture (GOP) among all the vehicular users. Simulation results show that our proposed RALS algorithm outperforms the comparison schemes in typical scenarios.

In this paper, we present the channel estimation (CE) problem in the orthogonal frequency division multiplexing system with offset quadrature amplitude modulation (OFDM/OQAM). Most CE methods rely on the assumption of a low frequency selective channel to tackle the problem in a way similar to OFDM. However, these methods would result in a severe performance degradation of the channel estimation when the assumption is not quite inaccurate. Instead, we focus on estimating the channel impulse response (CIR) itself which makes no assumption on the degree of frequency selectivity of the channels. After describing the main idea of this technique, we present an iterative CE method that does not require zero-value guard symbols in the preamble and consequently improves the spectral efficiency. This is done by the iterative estimation of the unknown transmitted data adjacent to the preamble. Analysis and simulation results validate the efficacy of the proposed method in multipath fading channels.

Estimating the cardinality of flows over sliding windows on high-speed links is still a challenging work under time and space constrains. To solve this problem, we present a novel data structure maintaining a summary of data and propose a constant-time update algorithm for fast evicting expired information. Moreover, a further memory-reducing schema is given at a cost of very little loss of accuracy.

Audio-Visual Speech Recognition (AVSR) is one of techniques to enhance robustness of speech recognizer in noisy or real environments. On the other hand, Deep Neural Networks (DNNs) have recently attracted a lot of attentions of researchers in the speech recognition field, because we can drastically improve recognition performance by using DNNs. There are two ways to employ DNN techniques for speech recognition: a hybrid approach and a tandem approach; in the hybrid approach an emission probability on each Hidden Markov Model (HMM) state is computed using a DNN, while in the tandem approach a DNN is composed into a feature extraction scheme. In this paper, we investigate and compare several DNN-based AVSR methods to mainly clarify how we should incorporate audio and visual modalities using DNNs. We carried out recognition experiments using a corpus CENSREC-1-AV, and we discuss the results to find out the best DNN-based AVSR modeling. Then it turns out that a tandem-based method using audio Deep Bottle-Neck Features (DBNFs) and visual ones with multi-stream HMMs is the most suitable, followed by a hybrid approach and another tandem scheme using audio-visual DBNFs.

In this paper, an infinite-horizon team-optimal incentive Stackelberg strategy is investigated for a class of stochastic linear systems with many non-cooperative leaders and one follower. An incentive structure is adopted which allows for the leader's team-optimal Nash solution. It is shown that the incentive strategy set can be obtained by solving the cross-coupled stochastic algebraic Riccati equations (CCSAREs). In order to demonstrate the effectiveness of the proposed strategy, a numerical example is solved.

We investigate a phased array-fed dual reflector antenna applying one-dimensional beam-scanning of the center-fed type, using an elliptical aperture to provide wide area observation. The distinguishing feature of this antenna is its elliptical aperture shape, in which the aperture diameter differs between the forward satellite direction and the cross-section orthogonal to it. The shape in the plane of the forward satellite direction, which does not have a beam-scanning function, is a ring-focus Cassegrain antenna, and the shape in the plane orthogonal to that, which does have a beam-scanning function, is an imaging reflector antenna. This paper describes issues which arose during design of the elliptical aperture shape and how they were solved, and presents design results using elliptical aperture dimensions of 1600 mm × 600 mm, in which the beam width differs by more than two times in the orthogonal cross-section. The effectiveness of the antenna was verified by fabricating a prototype antenna based on the design results. Measurement results confirmed that an aperture efficiency of 50% or more could be achieved, and that a different beam width was obtained in the orthogonal plane in accordance with design values.

In this paper, the integration of dynamic plant-wide optimization and distributed generalized predictive control (DGPC) is presented for serially connected processes. On the top layer, chance-constrained programming (CCP) is employed in the plant-wide optimization with economic and model uncertainties, in which the constraints containing stochastic parameters are guaranteed to be satisfied at a high level of probability. The deterministic equivalents are derived for linear and nonlinear individual chance constraints, and an algorithm is developed to search for the solution to the joint probability constrained problem. On the lower layer, the distributed GPC method based on neighborhood optimization with one-step delay communication is developed for on-line control of the whole system. Simulation studies for furnace temperature set-points optimization problem of the walking-beam-type reheating furnace are illustrated to verify the effectiveness and practicality of the proposed scheme.

In this paper, a new non-uniform weight-updating scheme for adaptive digital beamforming (DBF) is proposed. The unique feature of the letter is that the effective working range of the beamformer is extended and the computational complexity is reduced by introducing the robust DBF based on worst-case performance optimization. The robust parameter for each weight updating is chosen by analyzing the changing rate of the Direction of Arrival (DOA) of desired signal in LEO satellite communication. Simulation results demonstrate the improved performance of the new Non-Uniform Weight-Updating Beamformer (NUWUB).

In the conventional cellular macrocell implementation strategy, the main base station transmits the radio signals in the omnidirectional manner in order to provide a wide range of cellular transmission to the users. In reality, however, the users move from one place to another depending on their activities, hence, sometimes this creates areas where no user exists inside the macrocell. Nevertheless, the base station continues to transmit the radio signals to all the coverage areas due to its involuntary manner, thus causing waste of energy. In our previous work, an energy efficient LTE macrocell base station scheme based on hourly user location distribution, which utilized opportunistic beamforming, was proposed in order to provide the cellular transmission only to the area where the user density is high. The drawback of this scheme was that there were many users who cannot receive the cellular transmission because of the limitation of the beamforming shape. In this paper, to overcome this difficulty, a new energy efficient macrocell strategy will be proposed. Here, additional low power consumption femtocell access points are deployed inside the macrocell to support the energy efficient opportunistic beamforming based on the hourly user location distribution. Concretely, the femtocell access points are woken up only when the active calling users exist inside its range. The proposed new strategy will be evaluated in terms of the hourly successful calling user ratio, the total power consumption and the hourly average downlink throughput compared with the previously proposed beamforming transmission strategy and the conventional omnidirectional transmission. The results will show the effectiveness of the proposed strategy in providing an energy efficient cellular macrocell system with high quality cellular services.

In this paper, we study the problem of a Boolean function can be represented as the sum of two bent functions. This problem was recently presented by N. Tokareva when studying the number of bent functions [27]. Firstly, several classes of functions, such as quadratic Boolean functions, Maiorana-MacFarland bent functions, many partial spread functions etc, are proved to be able to be represented as the sum of two bent functions. Secondly, methods to construct such functions from low dimension ones are also introduced. N. Tokareva's main hypothesis is proved for n≤6. Moreover, two hypotheses which are equivalent to N. Tokareva's main hypothesis are presented. These hypotheses may lead to new ideas or methods to solve this problem. Finally, necessary and sufficient conditions on the problem when the sum of several bent functions is again a bent function are given.

A link adaptation scheme is devised for vector-perturbation (VP) zero-forcing beamforming (ZFBF) MIMO precoding and a link-adaptable VP-ZFBF precoder is applied to multi-point three-dimensional (3D) beamformers to be used in mmWave-band wireless access systems. Channel coding schemes used in current systems, e.g., turbo codes, possess systematic code structures. The VP gain can thus be predicted by searching for perturbation vectors for the symbol vectors mapped from information bits. On the basis of this principle, we constructed an efficient iterative modulation-and-coding-set (MCS) selection procedure for VP-ZFBF precoding. Simulation results demonstrate that our proposed scheme suitably passed on the VP gain to the selection of an appropriate higher-rate MCS index and thus achieved high throughputs by incorporating with multi-point 3D-beamformers.

Shrinkage widely linear recursive least squares (SWL-RLS) and its improved version called structured shrinkage widely linear recursive least squares (SSWL-RLS) algorithms are proposed in this paper. By using the relationship between the noise-free a posterior and a priori error signals, the optimal forgetting factor can be obtained at each snapshot. In the implementation of algorithms, due to the a priori error signal known, we still need the information about the noise-free a priori error which can be estimated with a known formula. Simulation results illustrate that the proposed algorithms have faster convergence and better tracking capability than augmented RLS (A-RLS), augmented least mean square (A-LMS) and SWL-LMS algorithms.

Digital phase shifters are widely used to achieve space scanning in phased array antenna, and beam pointing accuracy depends on the bit number and resolution of the digital phase shifter. This paper proposes a novel phase feeding method to reduce the phase quantization error effects. A linear formula for the beam pointing deviation of a linear uniform array in condition of phase quantization error is derived, and the linear programming algorithm is introduced to achieve the minimum beam pointing deviation. Simulations are based on the pattern of the phased array, which gives each element a certain quantization phase error to find the beam pointing deviation. The novel method is then compared with previous methods. Examples show that a 32-element uniform linear array with 5-bit phase shifters using the proposed method can achieve a higher beam-steering accuracy than the same array with 11-bit phase shifters.

In this letter, a novel robust adaptive beamforming algorithm is addressed to improve the robustness against steering vector random errors (SVREs), which eliminates the signal of interest (SOI) component from the sample covariance matrix (SCM), based on interference-plus-noise covariance matrix (IPNCM) reconstruction over annulus uncertainty sets. Firstly, several annulus uncertainty sets are used to constrain the steering vectors (SVs) of both interferences and the SOI. Additionally the IPNCM is reconstructed according to its definition by estimating each interference SV over its own annulus uncertainty set via the subspace projection algorithm. Meanwhile, the SOI SV is estimated as the prime eigenvector of the SOI covariance matrix term calculated over its own annulus uncertainty set. Finally, a novel robust beamformer is formulated based on the new IPNCM and the SOI SV, and it outperforms other existing reconstruction-based beamformers when the SVREs exist, especially in low input signal-to-noise ratio (SNR) cases, which is proved through the simulation results.

This paper presents a 60 GHz analog/digital beamforming receiver that effectively suppresses interference signals, targeting the IEEE 802.11ad/WiGig standard. Combining two-stream analog frontends with interference rejection digital signal processing, the analog beamforming steers the antenna beam to the desired direction while the digital beamforming provides gain suppression in the interference direction. A prototype has been built with 40 nm CMOS analog frontends as well as offline baseband digital signal processing. Measurements show a 3.1 dB EVM advantage over conventional two-stream diversity during a packet collision situation.

The high-availability seamless redundancy (HSR) protocol is a representative protocol that fulfills the reliability requirements of the IEC61850-based substation automation system (SAS). However, it has the drawback of creating unnecessary traffic in a network. To solve this problem, a dual virtual path (DVP) algorithm based on HSR was recently presented. Although this algorithm dramatically reduces network traffic, it does not consider the substation timing requirements of messages in an SAS. To reduce unnecessary network traffic in an HSR ring network, we introduced a novel packet transmission (NPT) algorithm in a previous work that considers IEC61850 message types. To further reduce unnecessary network traffic, we propose an extended dual virtual paths (EDVP) algorithm in this paper that considers the timing requirements of IEC61850 message types. We also include sending delay (SD), delay queue (DQ), and traffic flow latency (TFL) features in our proposal. The source node sends data frames without SDs on the primary paths, and it transmits the duplicate data frames with SDs on the secondary paths. Since the EDVP algorithm discards all of the delayed data frames in DQs when there is no link or node failure, unnecessary network traffic can be reduced. We demonstrate the principle of the EDVP algorithm and its performance in terms of network traffic compared to the standard HSR, NPT, and DVP algorithm using the OPNET network simulator. Throughout the simulation results, the EDVP algorithm shows better traffic performance than the other algorithms, while guaranteeing the timing requirements of IEC61850 message types. Most importantly, when the source node transmits heavy data traffic, the EDVP algorithm shows greater than 80% and 40% network traffic reduction compared to the HSR and DVP approaches, respectively.

In the future Internet of Things/M2M network, enormous amounts of data generated from sensors must be processed and utilized by cloud applications. In recent years, sensor data stream delivery, which collects and sends sensor data periodically, has been attracting great attention. As for sensor data stream delivery, the receivers have different delivery cycle requirements depending on the applications or situations. In this paper, we propose a sensor data stream delivery method to accommodate heterogeneous cycles on the cloud. The proposed method uses distributed hashing to determine relay nodes on the cloud and construct delivery paths autonomously. We evaluate the effectiveness of the proposed method in simulations. The simulation results show that the proposed method halves the maximum load of nodes compared to the baseline methods and achieves high load balancing.