We propose a novel structure that can reduce the power consumption and extend the transmission distance of an electro-absorption modulator integrated with a DFB (EADFB) laser. To overcome the trade-off relationship of the optical loss and chirp parameter of the EA modulator, we integrate a semiconductor optical amplifier (SOA) with an EADFB laser. With the proposed SOA assisted extended reach EADFB laser (AXEL) structure, the LD and SOA sections are operated by an electrically connected input port. We describe a design for AXEL that optimizes the LD and SOA length ratio when their total operation current is 80mA. By using the designed AXEL, the power consumption of a 10-Gbit/s, 1.55-µm EADFB laser is reduced by 1/2 and at the same time the transmission distance is extended from 80 to 100km.

To suppress intercell interference for three-cell half-duplex relay systems, joint interference suppression and multiuser detection (MUD) schemes that estimate weight coefficients by the recursive least-squares (RLS) algorithm have been proposed but show much worse bit error rate (BER) performance than maximum likelihood detection (MLD). To improve the BER performance, this paper proposes a joint interference suppression and MUD scheme that estimates the weight coefficients by eigenvalue decomposition. The proposed scheme carries the same advantages as the conventional RLS based schemes; it does not need channel state information (CSI) feedback while incurring much less amount of computational complexity than MLD. In addition, it needs to know only two out of three preambles used in the system. Computer simulations of orthogonal frequency-division multiplexing (OFDM) transmission under three-cell and frequency selective fading conditions are conducted. It is shown that the eigendecomposition-based scheme overwhelmingly outperforms the conventional RLS-based scheme although requiring higher computational complexity.

In this letter, an effective algorithm is proposed to improve the performance of relay enhanced cellular networks, which is to allocate appropriate resources to each access point with quality of service constraint. First we derive the ergodic rate for backhaul link based on a poison point process model, and then allocate resources to each link according to the quality of service requirements and ergodic rate of links. Numerical results show that the proposed algorithm can not only improve system throughput but also improve the rate distribution of user equipment.

This paper deals with a novel, interesting problem of detecting frauds in comparison-shopping services (CSS). In CSS, there exist frauds who perform excessive clicks on a target item. They aim at making the item look very popular and subsequently ranked high in the search and recommendation results. As a result, frauds may distort the quality of recommendations and searches. We propose an approach of detecting such frauds by analyzing click behaviors of users in CSS. We evaluate the effectiveness of the proposed approach on a real-world clickstream dataset.

Smart education environment, that is a learning environment utilizing the Information Communication Technology (ICT), has attracted a great deal of attention. In order to expand this environment, we need a system that can establish the learning environment armed cloud systems to reduce a significant strain on teaching staff. The important issue for such system is extensibility because the system should be adapted to many kinds of original digital learning material with minimum modification. Therefore, this paper proposes “An Application Framework for Smart Education System: SES Framework”. In this Smart Education System, multi-aspect information concerning to a technical term embedded in the original digital learning material can be retrieved from different social media automatically. They can be also displayed on multi-screen devices according to user's operation. It is implemented based on “Transforming Model” which enables the migration of the original digital learning material to the smart education environment. It also has an easy operation flow for trainees named “three-step selection flow”. SES Framework derived from Model-View-Controller (MVC) pattern is based on the system architecture that enables triple mashup against the original digital learning material, external social media, and screen devices in front of users. All these functionalities have been implemented on cloud systems. We show SES Framework through the implementation example. We also demonstrate the effectiveness of SES Framework by indicating the system modification case study.

Human activity prediction has become a prerequisite for service recommendation and anomaly detection systems in a smart space including ambient assisted living (AAL) and activities of daily living (ADL). In this paper, we present a novel approach to predict the next-activity set in a multi-user smart space. Differing from the majority of the previous studies considering single-user activity patterns, our study considers multi-user activities that occur with a large variety of patterns. Its complexity increases exponentially according to the number of users. In the multi-user smart space, there can be inevitably multiple next-activity candidates after multi-user activities occur. To solve the next-activity problem in a multi-user situation, we propose activity set prediction rather than one activity prediction. We also propose activity sequence partitioning to reduce the complexity of the multi-user activity pattern. This divides an activity sequence into start, ongoing, and finish zones based on the features in the tendency of activity occurrences. The majority of the activities in a multi-user environment occur at the beginning or end, rather than the middle, of an activity sequence. Furthermore, the types of activities typically occurring in each zone can be sufficiently distinguishable. Exploiting these characteristics, we suggest a two-step procedure to predict the next-activity set utilizing a long short-term memory (LSTM) model. The first step identifies the zones to which current activities belong. In the next step, we construct three different LSTM models to predict the next-activity set in each zone. To evaluate the proposed approach, we experimented using a real dataset generated from our campus testbed. Our experiments confirmed the complexity reduction and high accuracy in the next-activity set prediction. Thus, it can be effectively utilized for various applications with context-awareness in a multi-user smart space.

A novel generalized side-information cancellation (GSIC) precoder is proposed for multiuser multi-input multi-output (MIMO) downlink systems with channel state information at the transmitter. The proposed transceiver involves the following stages. First, a minimum mean square error (MMSE) based channel inversion (MMSE-CI) technique is utilized to suppress multiuser broadcast interference. By using a GSIC technique, it can further reduce the residual multiuser interference and the noise induced by MMSE-CI preprocessing. Next, with a singular value decomposition method, the spatial stream interference of each user is suppressed by the pre-processing and post-processing eigenvector matrices. Finally, the proposed precoder can be extended to joint water filling and diagonal loading methods for performance enhancement. For the correlated MIMO channels, signal subspace and antenna selection methods, incorporating the proposed GSIC precoder, are further designed to maximize the sum rate performance. Simulation results show that the proposed GSIC precoder outperforms the conventional precoders. Besides, simulation results confirm that the proposed GSIC precoder with water filling, diagonal loading, and signal subspace techniques exhibits excellent performance.

With the increasing demand of Internet-of-Things applicability in various devices and location-based services (LBSs) with positioning capabilities, we proposed simple and effective post-processing techniques to reduce positioning error and provide more precise navigation to users in a pedestrian environment in this letter. The proposed positioning error reduction techniques (Technique 1-minimum range securement and bounce elimination, Technique 2-direction vector-based error correction) were studied considering low complexity and wide applicability to various types of positioning systems, e.g., global positioning system (GPS). Through the real field tests in urban areas, we have verified that an average positioning error of the proposed techniques is significantly decreased compared to that of a GPS-only environment.

Several kinds of techniques for excellent multi-user interference (MUI) cancellation have been proposed for direct-detection synchronous optical code division multiple access (OCDMA) systems. All these techniques utilize modified prime sequence codes (MPSCs) as signature codes and can remove MUI errors efficiently. In this paper, the features of three typical MUI cancellers are studied and compared in detail. The authors defined the parameter “decision distance” to show the feature of MUI cancellers. The bit error rate performance of each canceller is investigated by computer simulation and compared with that of the basic on-off keying (OOK) scheme without cancellation. Then, we investigate the relationship between the decision distance and the bit error rate performance. It is shown that every canceller has a better bit error rate performance than the basic OOK scheme. Especially, the equal weight orthogonal (EWO) scheme, whose decision distance is the largest, has the best error resistance property of the three MUI cancellers. The results show that the decision distance is a useful index to evaluate the error resistance property of MUI cancellation schemes.

Recently, P2PTV is a popular application to deliver video streaming data over the Internet. On the overlay network, P2PTV applications create logical links between pairs of peers considering round trip time (RTT) without physical network consideration. P2PTV packets are shared over a network without localization awareness which is a serious problem for Internet Service Providers (ISPs). A delay-insertion-based traffic localization scheme was proposed for solving this problem. However, this scheme sometimes leads the newly joining peer to download streaming traffic from a local neighbor peer which has only scarce upload bandwidth. This paper proposes a novel scheme of delay-insertion-based traffic localization in which the router estimates relay capability to each relay peer candidate and leads the newly joining peer to connect to a neighbor peer with sufficient performance for relaying video data. Parameters were evaluated for the optimized condition in the relay capability estimation process. In addition, experiments conducted on a real network show that our proposed scheme can prevent the newly joining peer from downloading video data from peers with insufficient relay capability and maintain video quality close to normal in a P2PTV system while ensuring efficient traffic localization at the level of the Autonomous System (AS) network.

We newly propose the first lateral mode selective active multimode interferometer laser diode. The design principle is to arrange identical propagation path of different lateral mode. Thanks to multimode waveguide structure, 0th mode and 1st order mode has individual propagation path within one device. Individual lasing of fundamental mode as well as first mode was confirmed successfully.

This paper describes optical access networks focusing on passive optical network (PON) technologies from a technical point of view. Optical access networks have been applied to fiber-to-the-home as a driving force of broadband services and their use will continue growing in the near future. They will be applied as an aggregate component of broadband wireless networks. This paper also addresses solutions for their application.

In underlay cognitive radio (CR) multicast networks, the cognitive base station (CBS) can transmit at the lowest rate of all the secondary users (SUs) within the multicast group. Existing works showed that the sum rate of such networks saturates when the number of SUs increases. In this letter, for CR multicast networks with multiple channels, we group the SUs into different subgroups, each with an exclusive channel. Then, the problem of joint user grouping and power allocation to maximize the sum rate of all subgroups under the interference power constraint and the transmit power constraint is investigated. Compared to exponential complexity in the number of SUs required by the optimal algorithm, we proposed an efficient algorithm with only linear complexity. Simulation results confirm that the proposed algorithm achieves the sum rate very closed to that achieved by the optimal algorithm and greatly outperforms the maximum signal-to-noise-ratio based user grouping algorithm and the conventional algorithm without user grouping.

A novel dimensionality reduction method, Fisher Discriminant Locality Preserving Canonical Correlation Analysis (FDLP-CCA), for visualizing Web images is presented in this paper. FDLP-CCA can integrate two modalities and discriminate target items in terms of their semantics by considering unique characteristics of the two modalities. In this paper, we focus on Web images with text uploaded on Social Networking Services for these two modalities. Specifically, text features have high discriminate power in terms of semantics. On the other hand, visual features of images give their perceptual relationships. In order to consider both of the above unique characteristics of these two modalities, FDLP-CCA estimates the correlation between the text and visual features with consideration of the cluster structure based on the text features and the local structures based on the visual features. Thus, FDLP-CCA can integrate the different modalities and provide separated manifolds to organize enhanced compactness within each natural cluster.

The Technical Committee on Communication Behavior Engineering addresses the research question “How do we construct a communication network system that includes users?”. The growth in highly functional networks and terminals has brought about greater diversity in users' lifestyles and freed people from the restrictions of time and place. Under this situation, the similarities of human behavior cause traffic aggregation and generate new problems in terms of the stabilization of network service quality. This paper summarizes previous studies relevant to communication behavior from a multidisciplinary perspective and discusses the research approach adopted by the Technical Committee on Communication Behavior Engineering.

With the ever-increasing number of web services registered in service communities, many users are apt to find their interested web services through various recommendation techniques, e.g., Collaborative Filtering (i.e., CF)-based recommendation. Generally, CF-based recommendation approaches can work well, when a target user has similar friends or the target services (i.e., services preferred by the target user) have similar services. However, when the available user-service rating data is very sparse, it is possible that a target user has no similar friends and the target services have no similar services; in this situation, traditional CF-based recommendation approaches fail to generate a satisfying recommendation result. In view of this challenge, we combine Social Balance Theory (abbreviated as SBT; e.g., “enemy's enemy is a friend” rule) and CF to put forward a novel data-sparsity tolerant recommendation approach Ser_RecSBT+CF. During the recommendation process, a pruning strategy is adopted to decrease the searching space and improve the recommendation efficiency. Finally, through a set of experiments deployed on a real web service quality dataset WS-DREAM, we validate the feasibility of our proposal in terms of recommendation accuracy, recall and efficiency. The experiment results show that our proposed Ser_RecSBT+CF approach outperforms other up-to-date approaches.

In this letter, we consider a cognitive radio network where multiple secondary users (SUs) share the spectrum bands with multiple primary users (PUs) who are facing security threats from multiple eavesdroppers. By adopting the PU secrecy outage constraint to protect the PUs, we optimize the joint user and power allocation for the SUs to maximize the SU ergodic transmission rate. Simulation results are presented to verify the effectiveness of the proposed algorithm. It is shown that the proposed algorithm outperforms the existing scheme, especially for a large number of PUs and a small number of SUs. It is also shown that the number of eavesdroppers has negligible impact on the performance improvement of the proposed algorithm compared to the existing scheme. In addition, it is shown that increasing the number of eavesdroppers has insignificant impact on the SU performance if the number of eavesdroppers is already large.

In this paper, the recent advances in cooperative distributed antenna transmission (CDAT) are introduced for spatial diversity and multi-user spatial multiplexing in 5G mobile communications network. CDAT is an advanced version of the coordinated multi-point (CoMP) transmission. Space-time block coded transmit diversity (STBC-TD) for spatial diversity and minimum mean square error filtering combined with singular value decomposition (MMSE-SVD) for multi-user spatial multiplexing are described under the presence of co-channel interference from adjacent macro-cells. Blind selected mapping (blind SLM) which requires no side information transmission is introduced in order to suppress the increased peak-to-average signal power ratio (PAPR) of the transmit signals when CDAT is applied. Some computer simulation results are presented to confirm the effectiveness of CDAT techniques.

This paper proposes a proportional fair-based joint optimization method for user association and the bandwidth ratio of protected radio resources exclusively used by pico base stations (BSs) for inter-cell interference coordination (ICIC) in heterogeneous networks where low transmission-power pico BSs overlay a high transmission-power macro BS. The proposed method employs an iterative algorithm, in which the user association process for a given bandwidth ratio of protected radio resources and the bandwidth ratio control of protected radio resources for a given user association are applied alternately and repeatedly up to convergence. For user association, we use our previously reported decentralized iterative user association method based on the feedback information of each individual user assisted by a small amount of broadcast information from the respective BSs. Based on numerical results, we show that the proposed method adaptively achieves optimal user association and bandwidth ratio control of protected radio resources, which maximizes the geometric mean user throughput within the macrocell coverage area. The system throughput of the proposed method is compared to that for conventional approaches to show the performance gain.

The growing demand for high-speed data communication has continued to meet the need for ever-increasing I/O bandwidth in recent VLSI systems. However, signal integrity issues, such as intersymbol interference (ISI) and reflections, make the channel band-limited at high-speed data rates. We propose high-speed data transmission techniques for VLSI systems using Tomlinson-Harashima precoding (THP). Because THP can eliminate ISI by inverting the characteristics of channels with limited peak and average power at the transmitter, it is suitable for implementing advanced low-voltage and high-speed VLSI systems. This paper presents a novel double-rate THP equalization technique especially intended for multi-valued data transmission to further improve THP performance. Simulation and measurement results show that the proposed THP equalization with a double sampling rate can enhance the data transition time and, therefore, improve the eye opening.