Beijing University of Posts and Telecommunications

About: Beijing University of Posts and Telecommunications is a education organization based out in Beijing, Beijing, China. It is known for research contribution in the topics: MIMO & Quality of service. The organization has 39576 authors who have published 41525 publications receiving 403759 citations. The organization is also known as: BUPT.

A survey of word embeddings based on deep learning

Abstract: The representational basis for downstream natural language processing tasks is word embeddings, which capture lexical semantics in numerical form to handle the abstract semantic concept of words. Recently, the word embeddings approaches, represented by deep learning, has attracted extensive attention and widely used in many tasks, such as text classification, knowledge mining, question-answering, smart Internet of Things systems and so on. These neural networks-based models are based on the distributed hypothesis while the semantic association between words can be efficiently calculated in low-dimensional space. However, the expressed semantics of most models are constrained by the context distribution of each word in the corpus while the logic and common knowledge are not better utilized. Therefore, how to use the massive multi-source data to better represent natural language and world knowledge still need to be explored. In this paper, we introduce the recent advances of neural networks-based word embeddings with their technical features, summarizing the key challenges and existing solutions, and further give a future outlook on the research and application.

Echo-Liquid State Deep Learning for 360° Content Transmission and Caching in Wireless VR Networks With Cellular-Connected UAVs

Abstract: In this paper, the problem of content caching and transmission is studied for a wireless virtual reality (VR) network in which cellular-connected unmanned aerial vehicles (UAVs) capture videos on live games or sceneries and transmit them to small base stations (SBSs) that service the VR users. To meet the VR delay requirements, the UAVs can extract specific visible content (e.g., user field of view) from the original 360° VR data and send this visible content to the users so as to reduce the traffic load over backhaul and radio access links. The extracted visible content consists of 120° horizontal and 120° vertical images. To further alleviate the UAV-SBS backhaul traffic, the SBSs can also cache the popular contents that users request. This joint content caching and transmission problem are formulated as an optimization problem whose goal is to maximize the users’ reliability defined as the probability that the content transmission delay of each user satisfies the instantaneous VR delay target. To address this problem, a distributed deep learning algorithm that brings together new neural network ideas from liquid state machine (LSM), and echo state networks (ESNs) is proposed. The proposed algorithm enables each SBS to predict the users’ reliability so as to find the optimal contents to cache and content transmission format for each cellular-connected UAV. Analytical results are derived to expose the various network factors that impact content caching and content transmission format selection. Simulation results show that the proposed algorithm yields 25.4% and 14.7% gains, in terms of reliability compared to Q-learning and a random caching algorithm, respectively.

An effective approach to 5G: Wireless network virtualization

Abstract: Nowadays, the explosively growing demands for mobile service bring both challenges and opportunities to wireless networks, giving birth to fifth generation (5G) mobile networks. The features and requirements of different services are diverse in 5G. The management and coordination among heterogeneous networks, applications, and user demands need the 5G network to be open and flexible to ensure that network resources are allocated with high efficiency. To fulfill these requirements, wireless network virtualization is used to integrate heterogeneous wireless networks and coordinate network resources. In this article we propose a model of wireless network virtualization consisting of three planes: the data plane, the cognitive plane, and the control plane. A novel control signaling scheme has also been designed to support the proposed model. From the implementation perspective of network virtualization, a hierarchical control scheme based on cell-clustering has been used with dynamically optimized efficiency of resource utilization. Two use cases have been analyzed to demonstrate how the schemes work under the proposed model to improve resource efficiency and the user experience.

Direct Acyclic Graph based Ledger for Internet of Things: Performance and Security Analysis.

Abstract: Direct Acyclic Graph (DAG)-based ledger and the corresponding consensus algorithm has been identified as a promising technology for Internet of Things (IoT). Compared with Proof-of-Work (PoW) and Proof-of-Stake (PoS) that have been widely used in blockchain, the consensus mechanism designed on DAG structure (simply called as DAG consensus) can overcome some shortcomings such as high resource consumption, high transaction fee, low transaction throughput and long confirmation delay. However, the theoretic analysis on the DAG consensus is an untapped venue to be explored. To this end, based on one of the most typical DAG consensuses, Tangle, we investigate the impact of network load on the performance and security of the DAG-based ledger. Considering unsteady network load, we first propose a Markov chain model to capture the behavior of DAG consensus process under dynamic load conditions. The key performance metrics, i.e., cumulative weight and confirmation delay are analysed based on the proposed model. Then, we leverage a stochastic model to analyse the probability of a successful double-spending attack in different network load regimes. The results can provide an insightful understanding of DAG consensus process, e.g., how the network load affects the confirmation delay and the probability of a successful attack. Meanwhile, we also demonstrate the trade-off between security level and confirmation delay, which can act as a guidance for practical deployment of DAG-based ledgers.

Many-Body Effect and Device Performance Limit of Monolayer InSe.

Abstract: Due to a higher environmental stability than few-layer black phosphorus and a higher carrier mobility than few-layer dichalcogenides, two-dimensional (2D) semiconductor InSe has become quite a promising channel material for the next-generation field-effect transistors (FETs). Here, we provide the investigation of the many-body effect and transistor performance scaling of monolayer (ML) InSe based on ab initio GW-Bethe–Salpeter equation approaches and quantum transport simulations, respectively. The fundamental band gap of ML InSe is indirect and 2.60 eV. The optical band gap of ML InSe is 2.50 eV for the in-plane polarized light, with the corresponding exciton binding energy of 0.58 eV. The ML InSe metal oxide semiconductor FETs (MOSFETs) show excellent performances with reduced short-channel effects. The on-current, delay time, and dynamic power indicator of the optimized n- and p-type ML InSe MOSFETs can satisfy the high-performance and low-power requirements of the International Technology Roadmap for ...