To handle coherent signals with unknown arrival angles, an adaptive beamforming method is proposed which can be applied to an arbitrary array. The proposed method efficiently solves a generalized eigenvalue problem to estimate the arrival angles of the desired coherent signal group, by exploiting the Brent method in conjunction with alternating maximization. We discuss the condition for the correct direction estimation without erroneously taking interference direction estimates for the desired ones. Simulation results show that the performance of the proposed beamformer is very similar to that of the beamformer with the exact composite steering vector (CSV).

The availability of IP networks has increased its importance due to the evolving use of real-time and mission-critical applications on IP networks. Methods for preparing alternate routing tables that can be used for fast restoration from link failures have been investigated. In such methods, each node has to compute a number of alternate routing tables in advance since they have to prepare for each potential failure. The resulting huge number of alternate routing tables has prevented these methods from being deployed. In this paper, we propose a method for reducing the number of alternate routing tables for link failure. It analyzes three types of shortest path trees on the basis of link-state information. We show that the number of alternate routing tables can be reduced to 1/100, on average, from that with the conventional method, and that they are small enough to be stored in the memory of IP routers.

Two novel frequency rotation techniques that suppress multipath interference and increase the frequency diversity gain are proposed for uplink IFDMA systems. These benefits are especially important as the performance of traditional IFDMA falls significantly when the number of simultaneous accessing users becomes large. Frequency rotation was originally proposed to suppress the multipath interference and enlarge the frequency diversity gain of downlink access. Unfortunately, it cannot be applied to the uplink due to the loss of orthogonality among users in the frequency domain. In the proposed frequency rotation techniques, users do not share the multiple frequency orthogonal channels and thus orthogonality among users is maintained. The proposed technique is verified by computer simulations.

In this letter, the outage performance of multi-hop multiple-input multiple-output (MIMO) relaying systems is analyzed for spatially correlated Rayleigh fading channels. We focus on nonregenerative MIMO decouple-and-forward (DCF) relaying in orthogonal space-time block code (OSTBC) transmission and provide its outage probability given the assumption of ideal relay gain. The outage obtained here is shown a lower bound for using practical gains, which gets tight at high SNR. We conduct numerical studies to assess the impact of the spatial correlation between antennas on the outage probability.

Lee-Lee-Kim-Jeong proposed a hybrid authentication scheme to alleviate the latent security problems of mobile multi-hop networks. In this letter, we show that the Lee-Lee-Kim-Jeong scheme is insecure against the intercept attack.

The problem of recovering a high-resolution frame from a sequence of low-resolution frames is considered. In general, video frames cannot be related through global parametric transformation due to the arbitrary individual pixel movement between frame pairs. To overcome this problem, we propose to employ region-matching technique for motion estimation with a modified model for frame alignment. To do that, the reference frame is segmented into arbitrary-shaped regions which are further matched with that of the other frames. Then, the frame alignment is accomplished by optimizing the cost function that consists of L1-norm of the difference between the interpolated low-resolution (LR) frames and the simulated LR frames. The experimental results demonstrate that using region matching in motion estimation step with the modified alignment model works better than other motion models such as affine, block matching, and optical flow motion models.

This paper proposes an efficient multiuser relay scheme in OFDMA systems. In the proposed scheme, multiple terminals transmit their data packets simultaneously in the same subband and multiple relay stations retransmit their received signals in different subbands after subband conversion. A base station (BS) extracts individual packets from received signals in the different subbands. In advance of data transmission, the BS selects appropriate terminals so that the BS can extract individual data packets successfully. Numerical results show that the proposed relay scheme achieves higher system throughput than the conventional relay scheme when scheduling is applied to a larger number of terminals than the number of relay stations.

The approximation expression about error accumulation of a long-term prediction is derived. By analyzing this formula, we find that the factors that can affect the long-term predictability include the model parameters, prediction errors and the derivates of the used basis functions. To enlarge the maximum attempting time, we present that more suitable basis functions should be those with smaller derivative functions and a fast attenuation where out of the time series range. We compare the long-term predictability of a non-polynomial based algorithm and a polynomial one to prove the success of our method.

In this paper, we present an interactive and intuitive graph-cut-based video segmentation system while taking both color and motion information into consideration with a stroke-based user interface. Recently, graph-cut-based methods become prevalent for image and video segmentation. However, most of them deal with color information only and usually failed under circumstances where there are some regions in both foreground and background with similar colors. Unfortunately, it is usually hard to avoid, especially when the objects are filmed under a natural environment. To make such methods more practical to use, we propose a graph-cut-based video segmentation method based on both color and motion information, since the foreground objects and the background usually have different motion patterns. Moreover, to make the refinement mechanism easy to use, the strokes drawn by the user are propagated to the temporal-spatial video volume according to the motion information for visualization, so that the user can draw some additional strokes to refine the segmentation result in the video volume. The experiment results show that by combining both color and motion information, our system can resolve the wrong labeling due to the color similarity, even the foreground moving object is behind an occlusion object.

In most cases in wireless networks, a user has a two-way communication that consists of two sessions: uplink and downlink sessions, and its overall satisfaction to the communication depends on the quality of service of both sessions. However, in most previous approaches in wireless resource allocation, the satisfactions of a user for its uplink and downlink sessions are modeled separately and treated independently, which fails to accurately model user's overall satisfaction to its communication. Hence, in this paper we model user's overall satisfaction to its communication considering both its uplink and downlink sessions. To this end, we propose a novel concept for a utility function to model user's overall satisfaction to its communication, which is called a user-level utility function, considering user's satisfaction to uplink and downlink sessions jointly. To show the appropriateness of our approach, we apply our user-level utility functions to scheduling problems in TDMA wireless networks and show the performance improvement of our approach over the traditional approach that does not treat uplink and downlink sessions of a user jointly.

Motivated by the recent research in crosslayer design of cooperative wireless network, we propose a distributed cooperative routing algorithm for a multihop multi-relay wireless network to achieve selection diversity. We propose two algorithms, rate optimal path selection and outage optimal path selection, to satisfy the different requirements of the systems. Both algorithms work on distributed processing without requiring any centralized controller. Simulations are conducted to evaluate the performance of the proposal. The results of the simulations show that the proposed routing algorithms significantly improve the end-to-end data rate and outage performance compared with noncooperative routing protocols.

With the progress of ubiquitous technology, ubiquitous learning presents new opportunities to learners. Situations of a learner can be grasped through analyzing the learner's actions collected by sensors, RF-IDs, or cameras in order to provide support at proper time, proper place, and proper situation. Training for acquiring skills and enhancing physical abilities through exercise and experience in the real world is an important domain in u-learning. A training program may last for several days and has one or more training units (exercises) for a day. A learner's performance in a unit is considered as short term state. The performance in a series of units may change with patterns: progress, plateau, and decline. Long term state in a series of units is accumulatively computed based on short term states. In a learning/training program, it is necessary to apply different support strategies to adapt to different states of the learner. Adaptation in learning support is significant, because a learner loses his/her interests easily without adaptation. Systems with the adaptive support usually provide stimulators to a learner, and a learner can have a great motivation in learning at beginning. However, when the stimulators reach some levels, the learner may lose his/her motivation, because the long term state of the learner changes dynamically, which means a progress state may change to a plateau state or a decline state. In different long term learning states, different types of stimulators are needed. However, the stimulators and advice provided by the existing systems are monotonic without changeable support strategies. We propose a mutual adaptive support. The mutual adaptation means each of the system and the learner has their own states. On one hand, the system tries to change its state to adapt to the learner's state for providing adaptive support. On the other hand, the learner can change its performance following the advice given based on the state of the system. We create a ubiquitous pet (u-pet) as a metaphor of our system. A u-pet is always with the learner and encourage the leaner to start training at proper time and to do training smoothly. The u-pet can perform actions with the learner in training, change its own attributes based on the learner's attributes, and adjust its own learning rate by a learning function. The u-pet grasps the state of the learner and adopts different training support strategies to the learner's training based on the learner's short and long term states.

A fuel-supply system using movable fuel-supply vehicles (FSVs) is proposed and its performance is evaluated. Both FSVs and vehicles requesting fuel are equipped with networked sensors. The sensors in FSVs are location sensors, and those in vehicles requesting fuel are for determining the remaining amount of fuel and the location of the vehicle. The time from when a fuel request is generated until the request is satisfied is the most basic performance metric for this system. Explicit formulas for the probabilistic distribution of this request time are also derived. Numerical examples show that the number of movable FSVs can be smaller than that of fixed fuel stations by about 80% or more than two orders of magnitude. This result suggests that movable FSVs may reduce the cost of the fuel supply infrastructure for alternative-fuel vehicles such as fuel-cell vehicles.

The establishment of inter-domain traffic engineered paths is a requisite to accomplishing an end-to-end bandwidth guarantee and end-to-end resource optimization. Though the inter-domain paths must be reliable, it is difficult to compute suitable backup inter-domain paths in advance when the traffic engineering information is not disclosed outside of each domain. This means that the inter-domain path computation must satisfy the severe requirement of path establishment delay, since all inter-domain paths traversing the links in failure need to be computed after the failure occurs. Though several inter-domain path computation schemes have been proposed, their relative characteristics remain unknown. First, this paper classifies the conventional inter-domain path computation schemes into two types, i.e. end-to-end and per-domain schemes, and compares their performances under various traffic loads. Based on results of the comparisons, this paper proposes an adaptive inter-domain path computation scheme that can satisfy the severe requirement of the path establishment delay. In this scheme, the domain sequence from the source node to the destination node is divided into multiple sub-domain sequences according to the traffic load in each domain. The end-to-end path computation scheme is applied to the sub-domain sequences under heavy traffic loads, while the per-domain path computation scheme is applied to those under normal traffic loads. The simulation results show that the proposed scheme can adaptively satisfy the requirement for the path establishment delay while it maintains the optimality of path computation, even if the traffic load applied to each domain changes.

We propose requirement validation criteria and a method based on the interaction between actors in an information system. We focus on the cyclical transitions of one actor's situation against another and clarify observable stimuli and responses based on these transitions. Both actors' situations can be listed in a state transition table, which describes the observable stimuli or responses they send or receive. Examination of the interaction between both actors in the state transition tables enables us to detect missing or defective observable stimuli or responses. Typically, this method can be applied to the examination of the interaction between a resource managed by the information system and its user. As a case study, we analyzed 332 requirement defect reports of an actual system development project in Japan. We found that there were a certain amount of defects regarding missing or defective stimuli and responses, which can be detected using our proposed method if this method is used in the requirement definition phase. This means that we can reach a more complete requirement definition with our proposed method.

A continuous belief propagation (BP) decoding algorithm for a hybrid automatic repeat request (ARQ) system is proposed in this paper. The proposed continuous BP decoding algorithm utilizes the extrinsic information generated in the last iteration of the previous transmission for a continuous progression of the decoding through retransmissions. This allows the continuous BP decoding algorithm to accelerate the decoding convergence for codeword determination, especially when the number of retransmissions is large or a currently combined packet has punctured nodes. Simulation results verify the effectiveness of the proposed continuous BP decoding algorithm.

In this letter, we propose an improved speech/ nonspeech classification method to effectively classify a multimedia source. To improve performance, we introduce a feature based on spectral duration analysis, and combine recently proposed features such as high zero crossing rate ratio (HZCRR), low short time energy ratio (LSTER), and pitch ratio (PR). According to the results of our experiments on speech, music, and environmental sounds, the proposed method obtained high classification results when compared with conventional approaches.

In this letter, DFT-based channel estimation (CE) with a strong interference detector is proposed for OFDM systems. Computer simulations demonstrate that the proposed scheme achieves similar performance to an interference-free system and is a significant enhancement over conventional methods.

With simultaneous multi-user transmissions, spatial division multiple access (SDMA) provides substantial throughput gain over the single user transmission. However, its implementation in WLANs with contention-based IEEE 802.11 MAC remains challenging. Problems such as coordinating and synchronizing the multiple users need to be solved in a distributed way. In this paper, we propose a distributed MAC protocol for WLANs with SDMA support. A dual-mode CTS responding mechanism is designed to accomplish the channel estimation and user synchronization required for SDMA. We analytically study the throughput performance of the proposed MAC, and dynamic parameter adjustment is designed to enhance the protocol efficiency. In addition, the proposed MAC protocol does not rely on specific physical layer realizations, and can work on legacy IEEE 802.11 equipment with slight software updates. Simulation results show that the proposed MAC outperforms IEEE 802.11 significantly, and that the dynamic parameter adjustment can effectively track the load variation in the network.

This paper presents an autonomous navigation system for a mobile robot using randomly distributed passive RFID tags. In the case of randomly distributed RFID tags, it is difficult to provide the precise location of the robot especially in the area of sparse RFID tag distribution. This, combined with the wide turning radius of the robot, can cause the robot to enter a zigzag exploration path and miss the goal. In RFID-based navigation, the key is to reduce both the number of RFID tags and the localization error for practical use in a large space. To cope with these, we utilized the Read time, which measures the reading time of each RFID tag. With this, we could estimate accurately the localization and orientation without using any external sensors or increasing the RFID tags. The average estimation errors of 7.8 cm in localization and 11 degrees in orientation were achieved with 102 RFID tags in the area of 4.2 m by 6.2 m. Our proposed method is verified with the path trajectories produced during navigation compared with conventional approaches.