Multi-style Chord Music Generation Based on Artificial Neural Network

With the continuous development of deep learning and artificial neural networks(ANNs), algorithmic composition has gradually become a hot research field. In order to solve the music-style problem in generating chord music, a multi-style chord music generation(MSCMG) network is proposed based on the previous ANN for creation. A music-style extraction module and a style extractor are added by the network on the original basis;the music-style extraction module divides the entire music content into two parts, namely the music-style information Mstyleand the music content information Mcontent. The style extractor removes the music-style information entangled in the music content information. The similarity of music generated by different models is compared in this paper. It is also evaluated whether the model can learn music composition rules from the database. Through experiments, it is found that the model proposed in this paper can generate music works in the expected style. Compared with the long short term memory(LSTM) network, the MSCMG network has a certain improvement in the performance of music styles.

Data augmentation method for insulators based on Cycle-GAN

Data augmentation is an important task of using existing data to expand data sets.Using generative countermeasure network technology to realize data augmentation has the advantages of high-quality generated samples,simple training,and fewer restrictions on the number of generated samples.However,in the field of transmission line insulator images,the freely synthesized samples are prone to produce fuzzy backgrounds and disordered samples of the main insulator features.To solve the above problems,this paper uses the cycle generative adversarial network(Cycle-GAN)used for domain conversion in the generation countermeasure network as the initial framework and uses the self-attention mechanism and channel attention mechanism to assist the conversion to realize the mutual conversion of different insulator samples.The attention module with prior knowledge is used to build the generation countermeasure network,and the generative adversarial network(GAN)model with local controllable generation is built to realize the directional generation of insulator belt defect samples.The experimental results show that the samples obtained by this method are improved in a number of quality indicators,and the quality effect of the samples obtained is excellent,which has a reference value for the data expansion of insulator images.

Machine learning-based zero-touch network and service management:a survey

The exponential growth of mobile applications and services during the last years has challenged the existing network infrastructures.Consequently,the arrival of multiple management solutions to cope with this explosion along the end-to-end network chain has increased the complexity in the coordinated orchestration of different segments composing the whole infrastructure.The Zero-touch Network and Service Management(ZSM)concept has recently emerged to automatically orchestrate and manage network resources while assuring the Quality of Experience(QoE)demanded by users.Machine Learning(ML)is one of the key enabling technologies that many ZSM frameworks are adopting to bring intelligent decision making to the network management system.This paper presents a comprehensive survey of the state-of-the-art application of ML-based techniques to improve ZSM performance.To this end,the main related standardization activities and the aligned international projects and research efforts are deeply examined.From this dissection,the skyrocketing growth of the ZSM paradigm can be observed.Concretely,different standardization bodies have already designed reference architectures to set the foundations of novel automatic network management functions and resource orchestration.Aligned with these advances,diverse ML techniques are being currently exploited to build further ZSM developments in different aspects,including multi-tenancy management,traffic monitoring,and architecture coordination,among others.However,different challenges,such as the complexity,scalability,and security of ML mechanisms,are also identified,and future research guidelines are provided to accomplish a firm development of the ZSM ecosystem.

Hybrid NOMA Based MIMO Offloading for Mobile Edge Computing in 6G Networks

Non-orthogonal multiple access (NOMA), multiple-input multiple-output (MIMO) and mobile edge computing (MEC) are prominent technologies to meet high data rate demand in the sixth generation (6G) communication networks. In this paper, we aim to minimize the transmission delay in the MIMO-MEC in order to improve the spectral efficiency, energy efficiency, and data rate of MEC offloading. Dinkelbach transform and generalized singular value decomposition (GSVD) method are used to solve the delay minimization problem. Analytical results are provided to evaluate the performance of the proposed Hybrid-NOMA-MIMO-MEC system. Simulation results reveal that the H-NOMA-MIMO-MEC system can achieve better delay performance and lower energy consumption compared to OMA.

Next Generation Network Enabled by ZTE's Softswitch Technology

Softswitch technology integrates the su-periorities of both an intelligence net-work and the Internet, which embodiesits maturity and advancement. With ahierarchical network model, it effectivelysolves problems of evolution and convergenceof current communication networks. It also fol-

Strategic Thinking on Next Generation Network

It is noted that the revolutionary development of technologies,fundamental change of traffic composition,trend of network convergence as well as market opening and competition have become the driving forces to develop Next Generation Networks (NGN).After introducing the concepts and characteristics of NGN,the paper details its 5 strategic development directions:evolution to softswitch-based next generation switching network, evolution to next generation mobile communication network represented by 3G,evolution to IPv6-based next generation Internet,evolution to diversified broadband access network,and evolution to next generation transport network based on optical networking.Finally,it briefs the strategic thinking on NGN of China Telecom,the largest fixed network carrier in the world.

ZTE Softswitch the Working Solution to Build the New Generation Network

ZTE Softswitch supports the interoperability and convergence oflegacy PSTN/ISDN, PLMN, IN, and the Internet, allowing operatorsor service providers to offer diversified services to any subscriber atany time on a ZTE Softswitch network.With powerful C4 and C5 features, ZTE Softswitch effectivelysolves the evolution problems in the existing networks, protectinglegacy network investment and reducing future investment to a prof-itable level for providers.

Next Generation Mobile Video Networking

HWANG Jenq-Neng received his Ph.D. degree from the University of Southern California, USA. In the summer of 1989, Dr. HWANG joined the De- partment of Electrical Engineering of the Universi- ty of Washington in Seattle, USA, where he has been promoted to Full Professor since 1999. He served as the Associate Chair for Research fi＇om 2003 to 2005, and from 2011-2015. He is current- ly the Associate Chair for Global Affairs and Inter- national Development in the EE Depamnent. Hehas written more than 330 journal papers, conference papers and book chapters in the areas of machine learning, muhimedia signal processing, and muhimedia system integration and networking, including an au- thored textbook on ＂Multimedia Networking： from Theory to Practice,＂ published by Cambridge University Press. Dr. HWANG has close work- ing relationship with the industry on muhimedia signal processing and nmltimedia networking.

Service Convergence in Next Generation Network

The convergence of communication services becomes a focus in the industry along with the requirement for full-service operation and technical development. Service convergence includes two aspects: The convergence of the fixed and mobile networks; and the convergence of traditional communications and Internet services. This requires balancing the conflicts between the openness and operationability of terminal capability and network convergence. Unified authentication and authorization are the basis for service convergence in terms of operationability. Modular network and open terminal are technical solutions for the service convergence.

Next Generation Network Service Provision Mode and Its Developing Trend

The provision mode of the telecommunication service has experienced an evolving process, and showing the developing trend from distributed to centralized, from integrated to separated, and from closed to open. To suit this trend, there will be three provision modes as Session Initiation Protocol (SIP) server, Open Service Access (OSA) application server and intelligent network(IN) in Next Generation Network (NGN), provides all kinds of services and applications to the subscribers. With the popularity of broadband access and Internet, the NGN will provide single telecommunication service and act as the important national infrastructure to offer various information services to the subscribers. The service provision mode will be more open, diversified, and individualized.

Wavelet Neural Network Based Traffic Prediction for Next Generation Network

By using netflow traffic collecting technology, some traffic data for analysis are collected from a next generation network （NGN） operator. To build a wavelet basis neural network （NN）, the Sigmoid function is replaced with the wavelet in NN. Then the wavelet multiresolution analysis method is used to decompose the traffic signal, and the decomposed component sequences are employed to train the NN. By using the methods, an NGN traffic prediction model is built to predict one day＇s traffic. The experimental results show that the traffic prediction method of wavelet NN is more accurate than that without using wavelet in the NGN traffic forecasting.

Next Generation Network

Next Generation Network(NGN)is not a single architecture but a set of architectures with a common set of principles and hence varies by service provider history,target applications and assets.The paper introduces NGN functional requirements,NGN services and NGN architectural features.It also discusses why NGN is needed,when NGN is targeted,NGN trends and NGN deployment.It concludes that it is no longer a case whether NGN is needed but rather when and at what speed of the evolution.

Quality of Service in Next Generation Networks

To guarantee the Quality of Service (QoS) is one of the key objectives of the next generation network.Based on the introduction of the Next Generation Network(NGN) and the definition of QoS,various aspects of QoS are analyzed in this article,with emphasis on different approaches and business models.It is noted that QoS concerns the parametric network performance parameters and the application “satisfaction” level.

Telecom Regulation of Next Generation Network in China

The advent of the Next Generation Network (NGN), a new service-driven network, urges the telecom service operators to consider transforming from single-service providers to full-service providers. During the transformation, they should be concerned about the network user number and the network quality as well as the value added network information. The low threshold for service provision brings a new breed of service providers, which impacts upon the current regulation policy. To adapt to the development of the NGN, it is a necessity to improve the regulation policy in terms of service operators management, user management, Quality of Service (QoS) assurance, service monitoring, charging, and settlement. Meanwhile, regulatory authorities should establish a new body as quickly as possible to meet the trend of the NGN convergence. The new regulatory body would be responsible for regulating operators who will be awarded full-service licenses, and managing new service providers effectively to guarantee the user’s interests.

Model for Generating Scale-Free Artificial Social Networks Using Small-World Networks

The Internet of Things(IoT)has the potential to be applied to social networks due to innovative characteristics and sophisticated solutions that challenge traditional uses.Social network analysis(SNA)is a good example that has recently gained a lot of scientific attention.It has its roots in social and economic research,as well as the evaluation of network science,such as graph theory.Scientists in this area have subverted predefined theories,offering revolutionary ones regarding interconnected networks,and they have highlighted the mystery of six degrees of separation with confirmation of the small-world phenomenon.The motivation of this study is to understand and capture the clustering properties of large networks and social networks.We present a network growth model in this paper and build a scale-free artificial social network with controllable clustering coefficients.The random walk technique is paired with a triangle generating scheme in our proposed model.As a result,the clustering controlmechanism and preferential attachment(PA)have been realized.This research builds on the present random walk model.We took numerous measurements for validation,including degree behavior and the measure of clustering decay in terms of node degree,among other things.Finally,we conclude that our suggested random walk model is more efficient and accurate than previous state-of-the-art methods,and hence it could be a viable alternative for societal evolution.

ZTE Unveils Next Generation iCTN Transport Network Solution and Flagship Product ZXONE 5800 at MWC Barcelona 2009

ZTE Corporation (ZTE),a leading global provider of telecommunications equipment and network solutions,shined at the Mobile World Congress (MWC) 2009 by rolling out its next generation intelligent Converged Transport

ZTE Debuts New Generation IPTN Bearer Network Solution

ZTE Corporation announced the formal launch of its new generation IPTN bearer network solution targeting mobile backhaul and multi-service delivery to meet the needs of IP-based services on August 27,2009.It features packet

Tackling IoT Scalability with 5G NFV-Enabled Network Slicing

With emerging large volume and diverse heterogeneity of Internet of Things (IoT) applications, the one-size-fits-all design of the current 4G networks is no longer adequate to serve various types of IoT applications. Consequently, the concepts of network slicing enabled by Network Function Virtualization (NFV) have been proposed in the upcoming 5G networks. 5G network slicing allows IoT applications of different QoS requirements to be served by different virtual networks. Moreover, these network slices are equipped with scalability that allows them to grow or shrink their instances of Virtual Network Functions (VNFs) when needed. However, all current research only focuses on scalability on a single network slice, which is the scalability at the VNF level only. Such a design will eventually reach the capacity limit of a single slice under stressful incoming traffic, and cause the breakdown of an IoT system. Therefore, we propose a new IoT scalability architecture in this research to provide scalability at the NS level and design a testbed to implement the proposed architecture in order to verify its effectiveness. For evaluation, three systems are compared for their throughput, response time, and CPU utilization under three different types of IoT traffic, including the single slice scaling system, the multiple slices scaling system and the hybrid scaling system where both single slicing and multiple slicing can be simultaneously applied. Due to the balanced tradeoff between slice scalability and resource availability, the hybrid scaling system turns out to perform the best in terms of throughput and response time with medium CPU utilization.

UEs Power Reduction Evolution with Adaptive Mechanism over LTE Wireless Networks

At present, the major drawback for mobile phones is the issue of power consumption. As one of the alternatives to decrease the power consumption of standard, power-hungry location-based services usually require the knowledge of how individual phone features consume power. A typical phone feature is that the applications related to multimedia streaming utilize more power while receiving, processing, and displaying the multimedia contents, thus contributing to the increased power consumption. There is a growing concern that current battery modules have limited capability in fulfilling the long-term energy need for the progress on the mobile phone because of increasing power consumption during multimedia streaming processes. Considering this, in this paper, we provide an offline meaning sleep-mode method to compute the minimum power consumption comparing with the power-on solution to save power by implementing energy rate adaptation(RA) mechanism based on mobile excess energy level purpose to save battery power use. Our simulation results show that our RA method preserves efficient power while achieving better throughput compared with the mechanism without rate adaptation(WRA).