NEC Technologies (United Kingdom)

The development of renewable energy sources supplying electrical power systems in a large scale could cause important stability issues at the system level. A possible solution would be the introduction of grid forming controllers or the power electronic converters interfacing these sources. One of the suggested grid-forming technologies is the Virtual Synchronous Machine (VSM), which emulates the transient electromechanical characteristics of traditional synchronous machines. In this paper, the controller of a proposed grid forming converter will be presented. In a small power system load and fault disturbances, balanced and unbalanced, will be applied, presenting the behaviour of the proposed grid forming converter. Electromagnetic transient (EMT) software is used to study the converter output waveforms, as RMS models partially hide the response of the power converters during abnormal operation.

Interference management for Small Cell (SC) networks has drawn great attention from both academia and industry due to its importance in Long-Term Evolution (LTE) and emerging 5G networks. Although various approaches have been proposed in the literature, many of them face practical limitations such as showing gains only in specific scenarios, relying on ideal fronthaul, or becoming computationally intractable as the network size increases. In this paper, a novel framework is proposed for interference management in centralized SC networks by jointly utilizing graph theory and optimization theory. It extends the classic center-edge frequency reuse schemes into a more fine-grained scale, thus capturing the complex interference relationships in SC networks. The cell-level resource partition can be semi-statically updated according to the traffic dynamics while existing Medium Access Control (MAC) schedulers can be used for subframe-level resource allocation, not requiring fiber fronthaul. LTE system-level simulation results show that the proposed scheme can significantly improve both cell edge and mean user throughput with practical complexity.

This article discusses novel wireless and optical technologies to address the radical new challenges of small cell mobile backhaul (MBH). Specifically, we examine 60 GHz and 70-80 GHz millimeter-wave technologies for high-capacity last mile and pre-aggregation backhaul, and orthogonal frequency-division multiple access passive optical networks as the optical technology complement for enabling flexible cost-efficient hybrid backhaul coverage. Flexible high-capacity hybrid millimeter wave/optical MBH network operation is next verified via network simulations in the context of a demanding, urban small-cell backhaul application. Finally, a novel software defined networking tool called the backhaul resource manager is introduced for automated dynamic resource provisioning and capacity-aware path computation that improves fairness, network utilization and end-to-end user quality of experience. The introduction of the novel wireless, optical, and software-defined technologies thus has the potential to truly revolutionize the future MBH network.

Wireless sensor nodes are becoming more and more common in various settings and require a long battery life for better maintainability. Since most sensor nodes are powered by batteries, energy efficiency is a critical problem. In an experiment, we observed that when peak power consumption is high, battery voltage drops quickly, and the sensor stops working even though some useful charge remains in the battery. We propose three off-line algorithms that extend battery life by scheduling sensors' execution time that is able to reduce peak power consumption as much as possible under a deadline constraint. We also developed a simulator to evaluate the effectiveness of these algorithms. The simulation results showed that one of the three algorithms dramatically can extend battery life approximately three time as long as in simultaneous sensor activation.

Feedback implosion is a major problem limiting scalability in multicast satellite networks that arises when a large number of users transmit their feedback messages (FBMs) through the uplink channel, occupying a significant portion of system resources. This paper investigates how suppression of FBMs may be achieved through a novel feedback suppression scheme in which each user unilaterally decides whether to send a FBM or not. The users decisions are modeled applying game theory with inaccurate information. For this problem, the Bayesian equilibrium for the two and N-player game is investigated. It is proved that the feedback suppression game has a unique Bayesian equilibrium point. Then, based on appropriate numerical and simulation results, it is demonstrated that the proposed scheme avoids feedback implosion while at the same time it keeps feedback latency at very low levels. Finally, it is shown that the proposed scheme exhibits a significant performance improvement compared to existing exponential timer-based schemes.

In LTE and LTE-Advanced uplink, the interference power in a cell depends on the user scheduling and power assignment in neighboring cells. As a result, it is hard to accurately estimate the signal-to-interference-plus-noise ratio (SINR) values and make the right MCS (Modulation and Coding Scheme) selection. To address this challenge, we propose open-loop and closed-loop power control schemes to reduce both the average and the variance of the interference power in order to improve the system performance. It is shown that compared to the existing fractional power control (FPC) in LTE, the proposed schemes improve the cell-average throughput by 7-8% while maintaining the same cell-edge throughput in networks with low penetration loss, and improve the cell-average throughput by 4-6% and the cell-edge throughput by 15-23% in networks with high penetration loss.

本論文では，ニューラルネットワークを用いた MaC モデルに基づく感情生成システムを提案する．提案システムは，感情を価値判断に用いる心のメカニズムと，選択的注意や反射・熟考のプロセスを処理する意識のメカニズムという２つのメカニズムを持つ心と意識の概念モデルであるMaC（Mind and Consiousness）モデルに基づいたモデルであり，MaC モデルの感情生成部分にカオスニューラルネットワークとボルツマンマシンを導入している．ボルツマンマシンは同じ入力に対して確率的に複数の出力を行うように学習させることができる．提案システムでは，この性質を利用することで，同じ外部入力に対しても時には違った感情が生成されるという人間らしさを実現する．一方，カオスニューラルネットワークは外部入力と履歴を考慮して学習したデータを動的に出力することができる．提案システムでは，この性質を利用して，過去の履歴を考慮した感情の生成を行い，人間らしさを実現する．計算機実験とロボットを用いた実験を行い，提案システムにおいて，外部入力のみに依存しない自然な感情生成が行えること，提案システムを実装したロボットにおいて手動で操作したロボットに近い自然な行動が実現できることを確認した．

Acceleration technologies, in particular GPUs and Cell, are receiving considerable attention in modern-day HPC. Compared to classic accelerators and traditional CPUs, these devices not only exhibit higher compute density, but also sport significant memory bandwidth and vector-like capabilities to stream data at bandwidth of 100 GB/s or more. The latter qualifies such accelerators as a rebirth of vector computing. With large-scale deployments of GPUs such as Tokyo Tech's TSUBAME 1.2 supercomputer facilitating 680 GPUs in a 100-Teraflops scale supercomputer, we can demonstrate that, even under a massively parallel setting, GPUs can scale both in dense linear algebra codes as well as vector-oriented CFD codes. In both cases, however, careful algorithmic developments, especially latency hiding, are important to maximize their performance.

This paper presents a Reduced-reference based video-quality estimation method suitable for individual end-user quality monitoring of IPTV services. With the proposed method, the activity values for individual given-size pixel blocks of an original video are transmitted to end-user terminals. At the end-user terminals, the video quality of a received video is estimated on the basis of the activity-difference between the original video and the received video. Psychovisual weightings and video-quality score adjustments for fatal degradations are applied to improve estimation accuracy. In addition, low-bit-rate transmission is achieved by using temporal sub-sampling and by transmitting only the lower six bits of each activity value. The proposed method achieves accurate video quality estimation using only low-bit-rate original video information (15kbps for SDTV). The correlation coefficient between actual subjective video quality and estimated quality is 0.901 with 15kbps side information. The proposed method does not need computationally demanding spatial and gain-and-offset registrations. Therefore, it is suitable for real-time video-quality monitoring in IPTV services.

We have already proposed a Gigabit Ethernet-Optical Switched Access Network (GE-OSAN) architecture that realizes longer transmission distances and achieves higher security than the conventional Passive Optical Network (PON). To confirm the technical feasibility of the architecture, we introduce here a GE-OSAN prototype system for down-stream transmission. We present the Optical Switching Module (OSM), which uses (Pb,La)(Zr,Ti)O3 (PLZT) optical packet switches, and show that it realizes switching within 10ns of the designed position in the Inter-Frame Gap (IFG). We also introduce an Optical Network Unit (ONU) with optical burst receiver that uses off-the-shelf commercial devices to reduce its cost; two types of an optical to electrical signal (O/E) converter are implemented for performance comparison. After testing both of them, we select the one that satisfies our acquisition time requirement of 64ns.