The theoretically minimum length of a signal for fundamental frequency estimation in a noisy environment is discussed. Assuming that the noise is additive white Gaussian, it is known that a Cramér-Rao lower bound (CRLB) is given by the length and other parameters of the signal. In this paper, we define the minimum length as the length whose CRLB is less than or equal to the specific variance for any parameters of the signal. The specific variance is allowable variance of the estimate within an application of fundamental frequency estimation. By reformulating the CRLB with respect to the initial phase of the signal, the algorithms for determining the minimum length are proposed. In addition, we develop the methods of deciding the specific variance for general fundamental frequency estimation and pitch estimation. Simulation results in terms of both the fundamental frequency estimation and the pitch estimation show the validity of our approach.

Two-track squeeze and adjacent track interference (ATI) are major barriers to increasing track density in hard disk drives (HDD). These depend on skew angles made by a magnetic head and circumferential direction on a magnetic disk. This paper describes relationships between the skew angle and the magnetic core width (MCW) which affects two-track squeeze and ATI performance. We propose a design concept of a track pitch profile at different skew angles considering MCW. Equivalent robustness of ATI performance on different skew angle conditions is obtained with the optimized track pitch.

In this paper, we present a new electro-optic (EO) probing system based on heterodyne detection. The use of a recirculating frequency shifter allows to expand the bandwidth of the system far beyond what is attainable with a conventional heterodyne EO set-up. The performance for the frequencies up to 50GHz is analysed to forecast the viability of the system up to the THz range.

The network operations center of a communication carrier play an important and critical role in the early stage of disaster response because its function is the maintenance of communication services, which includes traffic control and restoration of services. This paper describes traffic control and restoration of services affected by the Great East Japan Earthquake. This paper discusses challenges on traffic congestion and restoration for future large-scale disasters.

Much research which has shown the usage of social ties could improve the location predictive performance, but as the strength of social ties is varying constantly with time, using the movement data of user's close friends at different times could obtain a better predictive performance. A hybrid Markov location prediction algorithm based on dynamic social ties is presented. The time is divided by the absolute time (week) to mine the long-term changing trend of users' social ties, and then the movements of each week are projected to the workdays and weekends to find the changes of the social circle in different time slices. The segmented friends' movements are compared to the history of the user with our modified cross-sample entropy to discover the individuals who have the relatively high similarity with the user in different time intervals. Finally, the user's historical movement data and his friends' movements at different times which are assigned with the similarity weights are combined to build the hybrid Markov model. The experiments based on a real location-based social network dataset show the hybrid Markov location prediction algorithm could improve 15% predictive accuracy compared with the location prediction algorithms that consider the global strength of social ties.

Information Centric Networking (ICN) had merits in terms of mobility, security, power consumption and network traffic. When a large-scale disaster occurred, the current communication system might be fragile and the server based network service might be unavailable due to the damages, network congestions, and power failure, etc. In this paper, we proposed an ICN based Disaster Information Sharing Service (DISS) [1], [2] system. DISS could provide robust information sharing service. Users could publish disaster information as a content message with the help of our DISS. In addition, by utilizing DISS's message naming strategy, users could retrieve disaster information even without a server connection. The ICN based DISS could reduce the probability of network congestion when a large number of simultaneous connections occurring. It could provide server-less service in poor network condition. DISS allows users retrieve disaster information from terminals or ICN nodes. During disasters, sharing information timely and effective could protect people from disaster, ensure people's safety.

At present, wireless local area networks (WLANs) based on IEEE802.11 are widely deployed in both private premises and public areas. In a public environment offering several access points (APs), a station (STA) needs to choose which AP to associate with. In this paper, we propose a distributed association control scheme with user guidance to increase users' utility based on uplink and downlink throughputs of individual stations. As part of the scheme, we also present a simple throughput estimation method that considers physical data rate, traffic demand, and frame length in both uplink and downlink. Basically, in the proposed scheme, an AP selects a user and suggests that the user moves to another AP if certain conditions are met. The user then decides whether to accept the suggestion or not in a self-interested manner or in a voluntary manner for the benefit of all users including the user's own self. Through simulations under this condition, we confirm that our distributed association control scheme can improve user utility and fairness even though the channel quality of the new AP is unknown in advance.

In this letter, a local pattern coding scheme is proposed to reduce the dimensionality of feature vectors in the local ternary pattern. The proposed method encodes the ternary patterns into a binary pattern by clustering similar ternary patterns. The experimental results show that the proposed method outperforms the previous methods.

This paper presents an automatic method to track soccer players in soccer video recorded from a single camera where the occurrence of pan-tilt-zoom can take place. The automatic object tracking is intended to support texture extraction in a free viewpoint video authoring application for soccer video. To ensure that the identity of the tracked object can be correctly obtained, background segmentation is performed and automatically removes commercial billboards whenever it overlaps with the soccer player. Next, object tracking is performed by an attribute matching algorithm for all objects in the temporal domain to find and maintain the correlation of the detected objects. The attribute matching process finds the best match between two objects in different frames according to their pre-determined attributes: position, size, dominant color and motion information. Utilizing these attributes, the experimental results show that the tracking process can handle occlusion problems such as occlusion involving more than three objects and occluded objects with similar color and moving direction, as well as correctly identify objects in the presence of camera movements.

In this paper, we propose an analytical approach for adaptive decode-and-forward (ADF) relaying schemes consisting of burst data transmission based on pilot symbol assisted-channel estimation (PSA-CE) methods over quasi-static Rayleigh fading channels. At first, we focus on the error-event at relay nodes in which the transmission mode switching is carried out burst by burst, whereas previous studies assumed the transmission mode switching symbol-by-symbol, thus showing lower error rate bound. Under consideration of burst transmission for ADF relay systems, we derive exact error rate expressions which better estimate the performance of actual systems. Then, the average bit and burst error rates are derived in approximated expressions for an arbitrary link signal-to-noise ratio (SNR) related with channel estimation errors. Their accuracy is confirmed by comparison with simulation results. Furthermore, ADF relay systems with PSA-CE schemes are confirmed to select correctly decoded relay nodes without additional signaling between relay nodes and the destination node and it is verified to achieve the performance at a cost of negligible SNR loss.

This paper extends our previously proposed non-orthogonal multiple access (NOMA) scheme to the base station (BS) cooperative multiple-input multiple-output (MIMO) cellular downlink for future radio access. The proposed NOMA scheme employs intra-beam superposition coding of a multiuser signal at the transmitter and the spatial filtering of inter-beam interference followed by the intra-beam successive interference canceller (SIC) at the user terminal receiver. The intra-beam SIC cancels out the inter-user interference within a beam. This configuration achieves reduced overhead for the downlink reference signaling for channel estimation at the user terminal in the case of non-orthogonal user multiplexing and enables the use of the SIC receiver in the MIMO downlink. The transmitter beamforming (precoding) matrix is controlled based on open loop-type random beamforming using a block-diagonalized beamforming matrix, which is very efficient in terms of the amount of feedback information from the user terminal. Simulation results show that the proposed NOMA scheme with block-diagonalized random beamforming in BS cooperative multiuser MIMO and the intra-beam SIC achieves better system-level throughput than orthogonal multiple access (OMA), which is assumed in LTE-Advanced. We also show that BS cooperative operation along with the proposed NOMA further enhances the cell-edge user throughput gain which implies better user fairness and universal connectivity.

We propose a joint channel, power and rate allocation scheme to minimize the weighted group outage probability of the secondary users (SUs) in a downlink cognitive radio (CR) multicast network coexisting with a primary network, subject to the service outage constraint as well as the interference power constraint and the transmit power constraint. It is validated by simulation results that, compared to the existing schemes, the proposed scheme achieves lower group outage probability.

The Satellite/Terrestrial Integrated mobile Communication System (STICS), which allows terrestrial mobile phones to communicate directly through a satellite, has been studied [1]. Satellites are unaffected by the seismic activity that causes terrestrial damage, and therefore, the STICS can be expected to be a measure that ensures emergency call connection. This paper first describes the basic characteristics of call blocking rates of terrestrial mobile phone systems in areas where non-functional base stations are geographically clustered, as investigated through computer simulations that showed an increased call blocking rate as the number of non-functional base stations increased. Further simulations showed that restricting the use of the satellite system for emergency calls only ensures the STICS's capacity to transmit emergency communications; however, these simulations also revealed a weakness in the low channel utilization rate of the satellite system [2]. Therefore, in this paper, we propose increasing the channel utilization rate with a priority channel framework that divides the satellite channels between priority channels for emergency calls and non-priority channels that can be available for emergency or general use. Simulations of this priority channel framework showed that it increased the satellite system's channel utilization rate, while continuing to ensure emergency call connection [3]. These simulations showed that the STICS with a priority channel framework can provide efficient channel utilization and still be expected to provide a valuable secondary measure to ensure emergency communications in areas with clustered non-functional base stations during large-scale disasters.

This paper investigates the detection performance of an improved energy detector for a secondary user with spatially correlated multiple antennas. In an improved energy detector, an arbitrary positive power operation p replaces the squaring operation in a conventional energy detector, and the optimum value of p that gives the best detection performance may be different from 2. Firstly, for a given value of p, we derive closed-form expressions for the probability of detection and the probability of false alarm when antennas at the secondary user are exponentially correlated. We then find the optimum value of p for two different detection criteria-maximizing the probability of detection for a target probability of false alarm, and minimizing the probability of false alarm for a target probability of detection. We show that the optimum p is strongly dependent on system parameters like number of antennas, antenna correlation coefficient among multiple antennas, and average received signal-to-noise ratio (SNR). From results, we infer that, in low SNR regime, the effect of antenna correlation is less pronounced on the optimum p. Finally, we find the optimum values of p and threshold jointly that minimize the total error rate.

This paper proposes applying random (opportunistic) beamforming to base station (BS) cooperative multiuser multiple-input multiple-output (MIMO) transmission. This proposal comprises two parts. First, we propose a block-diagonalized random unitary beamforming matrix. The proposed beamforming matrix achieves better throughput distribution compared to the purely random unitary beamforming matrix when the average path loss determined by distance-dependent loss and shadowing loss is largely different among transmitter antennas, which is true in BS cooperative MIMO. Second, we propose an online update algorithm for a random beamforming matrix to improve the throughput compared to the purely random and channel-independent beamforming matrix generation, especially when the number of users is low. Different from conventional approaches, the proposed online update algorithm does not increase the overhead of the reference signal transmission and control delay. Simulation results show the effectiveness of the proposed method using a block-diagonalized random unitary beamforming matrix with online updates in a BS cooperative multiuser MIMO scenario.

High dynamic range (HDR) images that include large differences in brightness levels are studied to address the lack of knowledge on the quality estimation method for real HDR images. For this, we earlier proposed a new metric, the independent signal-to-noise ratio (ISNR), using the independent pixel value as the signal instead of the peak value (PSNR). Next, we proposed the local peak signal-to-noise ratio (LPSNR), using the maximum value of neighboring pixels, as an improved version. However, these methods did not sufficiently consider human perception. To address this issue, here we proposed an objective estimation method that considers spatial frequency characteristics based on the actual brightness. In this method, the approximated function for human characteristics is calculated and used as a 2D filter on an FFT for spatial frequency weighting. In order to confirm the usefulness of this objective estimation method, we compared the results of the objective estimation with a subjective assessment. We used the organic EL display which has a perfect contrast ratio for the subjective assessment. The results of experiments showed that perceptual weighting improves the correlation between the SNR and MOS of the subjective assessment. It is recognized that the weighted LPSNR gives the best correlation.

In this Letter, a new iris recognition approach based on local Gabor orientation feature is proposed. On one hand, the iris feature extraction method using the traditional Gabor filters can cause time-consuming and high-feature dimension. On the other hand, we can find that the changes of original iris texture in angle and radial directions are more obvious than the other directions by observing the iris images. These changes in the preprocessed iris images are mainly reflected in vertical and horizontal directions. Therefore, the local directional Gabor filters are constructed to extract the horizontal and vertical texture characteristics of iris. First, the iris images are preprocessed by iris and eyelash location, iris segmentation, normalization and zooming. After analyzing the variety of iris texture and 2D-Gabor filters, we construct the local directional Gabor filters to extract the local Gabor features of iris. Then, the Gabor & Fisher features are obtained by Linear Discriminant Analysis (LDA). Finally, the nearest neighbor method is used to recognize the iris. Experimental results show that the proposed method has better iris recognition performance with less feature dimension and calculation time.

Considering worse-case channel uncertainties, we investigate the robust energy efficient (EE) beamforming design problem in a K-user multiple-input-single-output (MISO) interference channel. Our objective is to maximize the worse-case sum EE under individual transmit power constraints. In general, this fractional programming problem is NP-hard for the optimal solution. To obtain an insight into the problem, we first transform the original problem into its lower bound problem with max-min and fractional form by exploiting the relationship between the user rate and the minimum mean square error (MMSE) and using the min-max inequality. To make it tractable, we transform the problem of fractional form into a subtractive form by using the Dinkelbach transformation, and then propose an iterative algorithm using Lagrangian duality, which leads to the locally optimal solution. Simulation results demonstrate that our proposed robust EE beamforming scheme outperforms the conventional algorithm.

A prompt rescue is a serious operation when a catastrophic disaster occurs. In an uncommunicable area where the existing communication systems are damaged, it is, however, difficult to collect SOS messages of victims. So far, we have proposed a smartphone application named SOSCast to collect SOS messages via device-to-device transmission in such an area. However, with the limitation of coverage area and battery consumption, it decreases the possibility of finding the victim due to the risk of losing the SOS messages. In this paper, thus, we propose an information-sharing cluster to virtually extend the communication coverage area and to secure the SOS messages by reducing the battery consumption. In the performance evaluation, compared with the original SOSCast, we showed that the proposed method can reduce battery consumption to secure the message through a prototype system and simulation experiments.

In this letter, a novel collaborative representation graph based on the local and global consistency label propagation method, denoted as CRLGC, is proposed. The collaborative representation graph is used to reduce the cost time in obtaining the graph which evaluates the similarity of samples. Considering the lacking of labeled samples in real applications, a semi-supervised label propagation method is utilized to transmit the labels from the labeled samples to the unlabeled samples. Experimental results on three image data sets have demonstrated that the proposed method provides the best accuracies in most times when compared with other traditional graph-based semi-supervised classification methods.