The increase in network access devices and demand for high quality of service (QoS) by the users have led to insufficient capacity for the network operators. Moreover, the existing control equipment and mechanisms are not flexible and agile enough for the dynamically changing environment of heterogeneous cellular networks (HetNets). This non-agile control plane is hard to scale with ever increasing traffic demand and has become the performance bottleneck. Furthermore, the new HetNet architecture requires tight coordination and cooperation for the densely deployed small cell base stations, particularly for interference mitigation and dynamic frequency reuse and sharing. These issues further complicate the existing control plane and can cause serious inefficiencies in terms of users' quality of experience and network performance. This article presents an SDN control framework for energy efficient downlink/uplink scheduling in HetNets. The framework decouples the control plane from data plane by means of a logically centralized controller with distributed agents implemented in separate entities of the network (users and base stations). The scheduling problem consists of three sub-problems: (i) user association, (ii) power control, (iii) resource allocation and (iv) interference mitigation. Moreover, these sub-problems are coupled and must be solved simultaneously. We formulate the DL/UL scheduling in HetNet as an optimization problem and use the Markov approximation framework to propose a distributed economical algorithm. Then, we divide the algorithm into three sub-routines for (i) user association, (ii) power control, (iii) resource allocation and (iv) interference mitigation. These sub-routines are then implemented on different agents of the SDN framework. We run extensive simulation to validate our proposal and finally, present the performance analysis.

Wi-Fi Direct is a promising and available technology for device-to-device (D2D) proximity communications. To improve the performances of Wi-Fi Direct communication, optimized radio resource allocations are important. This paper proposes network assisted Wi-Fi Direct (NAWD), which operates based on the media independent services framework of IEEE 802.21 standard, for optimizing radio resource allocations. The NAWD is enhanced Wi-Fi Direct with the assistance of infrastructure networks (e.g., cellular network) and allocates radio resources (e.g., frequency channels and transmit power) to reduce radio interferences among Wi-Fi Direct devices (e.g., smart phones and set-top boxes). The NAWD includes mechanisms for gathering configuration information (e.g., location information and network connection information) of Wi-Fi Direct devices and allocating optimized radio resources (e.g., frequency channels and transmit power) to reduce radio interferences among Wi-Fi Direct devices. Simulation results show that the proposed NAWD increases significantly SINR, power efficiency, and areal capacity compared to legacy Wi-Fi Direct, where areal capacity is total traffic throughput per unit area.

In this paper, we consider a coherently distributed (CD) source model. Since the CD source is characterized by four parameters: central azimuth direction-of-arrival (DOA), azimuth angular spread, central elevation DOA and elevation angular spread, the parameter estimation is normally complex. We propose an algorithm that combines the rotational invariance techniques (ESPRIT) and the generalized ESPRIT algorithm for the 2-dimensional (2D) central DOA estimation of CD sources. Using a pair of uniform circular arrays (UCAs), the proposed solution is able to obtain the central DOAs with both high accuracy and low computational complexity. The central elevation DOAs are estimated by using the rotational invariance relation between the two uniform circular sub-arrays. Based on the centrosymmetric structure of UCA, the generalized ESPRIT algorithm is then applied to estimate the central azimuth DOAs through one-dimensional searching. It is noteworthy that the central DOAs are estimated without any information of the deterministic angular distribution function (DADF). The performance of the proposed algorithm is demonstrated via computer simulations.

An online nonnegative matrix factorization (NMF) algorithm based on recursive least squares (RLS) is described in a matrix form, and a simplified algorithm for a low-complexity calculation is developed for frame-by-frame online audio source separation system. First, the online NMF algorithm based on the RLS method is described as solving the NMF problem recursively. Next, a simplified algorithm is developed to approximate the RLS-based online NMF algorithm with low complexity. The proposed algorithm is evaluated in terms of audio source separation, and the results show that the performance of the proposed algorithms are superior to that of the conventional online NMF algorithm with significantly reduced complexity.

Sorting is an extremely important computation kernel that has been accelerated in a lot of fields such as databases, image processing, and genome analysis. Given that advent of Internet of Things (IoT) era due to mobile technology progressions, the future needs a sorting method that is available on any environment, such as not only high performance systems like servers but also low computational performance machines like embedded systems. In this paper, we present an FPGA-based sorting accelerator combining Sorting Network and Merge Sorter Tree, which is customizable by means of tuning design parameters. The proposed FPGA accelerator sorts data sent from a host PC via the PCIe bus, and sends back the fully sorted data sequence to it. We also present a detailed analytical model that accurately estimates the sorting performance. Due to these characteristics, designers can know how fast a developed sorting hardware is in advance and can implement the best one to fulfill the cost and performance constraints. Our experiments show that the proposed hardware achieves up to 19.5x sorting performance, compared with Intel Core i7-3770K operating at 3.50GHz, when sorting 256M 32-bits integer elements. However, this result is limited because of insufficient memory bandwidth. To overcome this problem, we propose a data compression mechanism and the experimental result shows that the sorting hardware with it achieves almost 90% of the estimated performance, while the hardware without it does about 60%. In order to allow every designer to easily and freely use this accelerator, the RTL source code is released as open-source hardware.

In this letter, we focus on the subcarrier allocation problem for device-to-device (D2D) communication in cellular networks to improve the cellular energy efficiency (EE). Our goal is to maximize the weighted cellular EE and its solution is obtained by using a game-theoretic learning approach. Specifically, we propose a lower bound instead of the original optimization objective on the basis of the proven property that the gap goes to zero as the number of transmitting antennas increases. Moreover, we prove that an exact potential game applies to the subcarrier allocation problem and it exists the best Nash equilibrium (NE) which is the optimal solution to optimize the lower bound. To find the best NE point, a distributed learning algorithm is proposed and then is proved that it can converge to the best NE. Finally, numerical results verify the effectiveness of the proposed scheme.

In this paper, we propose a method to find similar sentences based on language resources for building a parallel corpus between English and Korean from Wikipedia. We use a Wiki-dictionary consisted of document titles from the Wikipedia and bilingual example sentence pairs from Web dictionary instead of traditional machine readable dictionary. In this way, we perform similarity calculation between sentences using sequential matching of the language resources, and evaluate the extracted parallel sentences. In the experiments, the proposed parallel sentences extraction method finally shows 65.4% of F1-score.

In this letter, we propose an algorithm for the 2-dimensional (2D) direction of arrival (DOA) estimation of noncircular coherently distributed (CD) sources using the centrosymmetric array. For a centrosymmetric array, we prove that the angular signal distributed weight (ASDW) vector of the CD source has a symmetric structure. To estimate azimuth and elevation angle, we perform a 2D searching based on generalized ESPRIT algorithm. The significant superiority of the proposed algorithm is that, the 2D central directions of CD sources can be found independently of deterministic angular distributed function (DADF). Simulations results verify the efficacy of the proposed algorithm.

Spectrum sharing effectively improves the spectrum usage by allowing secondary users (SUs) to dynamically and opportunistically share the licensed bands with primary users (PUs). The concept of cooperative spectrum sharing allows SUs to use portions of the PUs' radio resource for their own data transmission, under the condition that SUs help the PUs' transmission. The key issue with designing such a scheme is how to deal with the resource splitting of the network. In this paper we propose a relay-based cooperative spectrum sharing scheme in which the network consists of one PU and multiple SUs. The PU asks the SUs to relay its data in order to improve its energy efficiency, in return it rewards the SUs with a portion of its authorized spectrum. However each SU is only allowed to transmit its data via the rewarded channel at a power level proportional to the contribution it makes to the PU. Since energy cost is considered, the SUs must carefully determine their power level. This scheme forms a non-cooperative Stackelberg resource allocation game where the strategy of PU is the bandwidth it rewards and the strategy of each SU is power level of relay transmission. We first investigate the second stage of the sub-game which is addressed as power allocation game. We prove there exists an equilibrium in the power allocation game and provide a sufficient condition for the uniqueness of the equilibrium. We further prove a unique Stackelberg equilibrium exists in the resource allocation game. Distributed algorithms are proposed to help the users with incomplete information achieve the equilibrium point. Simulation results validate our analysis and show that our proposed scheme introduces significant utility improvement for both PU and SUs.

Compact and room-temperature operable terahertz emitting devices have been proposed using a semiconductor coupled multilayer cavity that consists of two functional cavity layers and three distributed Bragg reflector (DBR) multilayers. Two cavity modes with an optical frequency difference in the terahertz region are realized since two cavities are coupled by the intermediate DBR multilayer. In the proposed device, one cavity is used as the active layer for two-color lasing in the near-infrared region by current injection and the other is used as the second-order nonlinear optical medium for difference-frequency generation of the two-color fundamental laser light. The control of the nonlinear polarization by face-to-face bonding of two epitaxial wafers with different orientations is quite effective to achieve bright terahertz emission from the coupled cavity. In this study, two-color emission by optical excitation was measured for the wafer-bonded GaAs/AlGaAs coupled multilayer cavity containing self-assembled InAs quantum dots (QDs). We found that optical loss at the bonding interface strongly affects the two-color emission characteristics when the bonding was performed in the middle of the intermediate DBR multilayer. The effect was almost eliminated when the bonding position was carefully chosen by considering electric field distributions of the two modes. We also fabricated the current-injection type devices using the wafer-bonded coupled multilayer cavities. An assemble of self-assembled QDs is considered to be desirable as the optical gain medium because of the discrete nature of the electronic states and the relatively wide gain spectrum due to the inhomogeneous size distribution. The gain was, however, insufficient for two-color lasing even when the nine QD layers were used. Substituting two types of InGaAs multiple quantum wells (MQWs) for the QDs, we were able to demonstrate two-color lasing of the device when the gain peaks of MQWs were tuned to the cavity modes by lowering the operating temperature.

This paper proposes a dynamic spectrum controlled (DSTC) channel allocation algorithm to increase the total throughput of satellite communication (SATCOM) systems. To effectively use satellite resources such as the satellite's maximum transponder bandwidth and maximum transmission power and to handle the propagation gain variation at all earth stations, the DSTC algorithm uses two new transmission techniques: spectrum compression and spectrum division. The algorithm controls various transmission parameters, such as the spectrum compression ratio, number of spectrum divisions, combination of modulation method and FEC coding rate (MODCOD), transmission power, and spectrum bandwidth to ensure a constant transmission bit rate under variable propagation conditions. Simulation results show that the DSTC algorithm achieves up to 1.6 times higher throughput than a simple MODCOD-based algorithm.

This paper addresses the issue of source retrieval in plagiarism detection. The task of source retrieval is retrieving all plagiarized sources of a suspicious document from a source document corpus whilst minimizing retrieval costs. The classification-based methods achieved the best performance in the current researches of source retrieval. This paper points out that it is more important to cast the problem as ranking and employ learning to rank methods to perform source retrieval. Specially, it employs RankBoost and Ranking SVM to obtain the candidate plagiarism source documents. Experimental results on the dataset of PAN@CLEF 2013 Source Retrieval show that the ranking based methods significantly outperforms the baseline methods based on classification. We argue that considering the source retrieval as a ranking problem is better than a classification problem.

This paper proposes a recommendation-based bandwidth calendaring system for packet transport networks. The system provides a user-portal interface with which users can directly reserve packet transport resources. In this regard, the system recommends multi-grade (e.g., multi-price) reservation plans. By adjusting grades of plans in accordance with network resource utilization, this system provides not only reservation flexibility for users but also efficient utilization of network resources. For recommending multi-grade plans, pre-computation of resource allocation is required for every time slot. Because the number of time slots is huge, we also propose an algorithm for fast computation of resource allocation based on time-slot aggregation. Our evaluation suggests that our algorithm can produce a sub-optimal solution within quasi-real time for a large-scale network. We also show that our recommendation-based system can increase the service-provider-revenue in peaky traffic demand environments.

Service chaining (SC) is a method for realizing a service by transferring flows among several service functions (SFs) that process packets. A route among SFs is called a service path (SP). Service chaining is being developed to reduce costs, increase flexibility, and shorten time-to-market. SC technologies are expected to be applied to carrier networks so that large communication carriers benefit from them. We assume that SPs process the traffic of services that treat all users in the same way such as an Internet access service for home users. An SP processes flows from several users. We do not assume that each SP is assigned to a user. Because a carrier network accommodates many users, each service will be heavily utilized. Therefore, it is assumed that the amount of traffic of a service is larger than the resource of an SF apparatus. Several SPs are required to process the traffic. SPs are supposed to meet two requirements. One is guaranteeing minimum bandwidth. The other is reducing the number of SF apparatuses, i.e., high resource utilization. Resource utilization depends on the combination of the resource quantities of SF apparatuses. Network operators have to determine the bandwidth of each SP within the range from the minimum bandwidth to the resource quantities of SF apparatuses to maximize resource utilization. Methods for determining the bandwidth of each SP have not been proposed for meeting the two requirements. Therefore, we propose a resource allocation method for this purpose. The proposed method determines the bandwidth of each SP on the basis of the combination of the resource quantities of SF apparatuses for guaranteeing the minimum bandwidth and maximizing resource utilization and allocates necessary resources to each SP. We also evaluate the proposed method and confirm that it can guarantee the minimum bandwidth of SPs and achieve high resource utilization regardless of the combination of the resource quantities of SF apparatuses. Although SF apparatuses are generally produced without considering the combinations of resource quantities of SF apparatuses in SPs, the proposed method can provide more options for selecting SF apparatuses.

Sound source localization is an essential technique in many applications, e.g., speech enhancement, speech capturing and human-robot interaction. However, the performance of traditional methods degrades in noisy or reverberant environments, and it is sensitive to the spatial location of sound source. To solve these problems, we propose a sound source localization framework based on bi-direction interaural matching filter (IMF) and decision weighting fusion. Firstly, bi-directional IMF is put forward to describe the difference between binaural signals in forward and backward directions, respectively. Then, a hybrid interaural matching filter (HIMF), which is obtained by the bi-direction IMF through decision weighting fusion, is used to alleviate the affection of sound locations on sound source localization. Finally, the cosine similarity between the HIMFs computed from the binaural audio and transfer functions is employed to measure the probability of the source location. Constructing the similarity for all the spatial directions as a matrix, we can determine the source location by Maximum A Posteriori (MAP) estimation. Compared with several state-of-the-art methods, experimental results indicate that HIMF is more robust in noisy environments.

In this paper, we deal with the fixed-length lossy compression, where a fixed-length sequence emitted from the information source is encoded into a codeword, and the source sequence is reproduced from the codeword with a certain distortion. We give lower and upper bounds on the minimum number of codewords such that the probability of exceeding a given distortion level is less than a given probability. These bounds are characterized by using the α-mutual information of order infinity. Further, for i.i.d. binary sources, we provide numerical examples of tight upper bounds which are computable in polynomial time in the blocklength.

Average coding rate of a multi-shot Tunstall code, which is a variation of variable-to-fixed length (VF) lossless source codes, for stationary memoryless sources is investigated. A multi-shot VF code parses a given source sequence to variable-length blocks and encodes them to fixed-length codewords. If we consider the situation that the parsing count is fixed, overall multi-shot VF code can be treated as a one-shot VF code. For this setting of Tunstall code, the compression performance is evaluated using two criterions. The first one is the average coding rate which is defined as the codeword length divided by the average block length. The second one is the expectation of the pointwise coding rate. It is proved that both of the above average coding rate converge to the entropy of a stationary memoryless source under the assumption that the geometric mean of the leaf counts of the multi-shot Tunstall parsing trees goes to infinity.

A generalization of compression via substring enumeration (CSE) for k-th order Markov sources with a finite alphabet is proposed, and an upper bound of the codeword length of the proposed method is presented. We analyze the worst case maximum redundancy of CSE for k-th order Markov sources with a finite alphabet. The compression ratio of the proposed method asymptotically converges to the optimal one for k-th order Markov sources with a finite alphabet if the length n of a source string tends to infinity.

This letter deals with the Slepian-Wolf coding problem for general sources. The second-order achievable rate region is derived using quantity which is related to the smooth max-entropy and the conditional smooth max-entropy. Moreover, we show the relationship of the functions which characterize the second-order achievable rate region in our study and previous study.

We treat lossless fixed-to-variable length source coding under general sources for finite block length setting. We evaluate the threshold of the overflow probability for prefix and non-prefix codes in terms of the smooth max-entropy. We clarify the difference of the thresholds between prefix and non-prefix codes for finite block length. Further, we discuss our results under the asymptotic block length setting.