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| 1 | QoS-Aware Dynamic Resource Management in Heterogeneous Mobile Cloud Computing Networks显示文摘In mobile cloud computing(MCC) systems,both the mobile access network and the cloud computing network are heterogeneous,implying the diverse configurations of hardware,software,architecture,resource,etc.In such heterogeneous mobile cloud(HMC) networks,both radio and cloud resources could become the system bottleneck,thus designing the schemes that separately and independently manage the resources may severely hinder the system performance.In this paper,we aim to design the network as the integration of the mobile access part and the cloud computing part,utilizing the inherent heterogeneity to meet the diverse quality of service(QoS)requirements of tenants.Furthermore,we propose a novel cross-network radio and cloud resource management scheme for HMC networks,which is QoS-aware,with the objective of maximizing the tenant revenue while satisfying the QoS requirements.The proposed scheme is formulated as a restless bandits problem,whose 'indexability' feature guarantees the low complexity with scalable and distributed characteristics.Extensive simulation results are presented to demonstrate the significant performance improvement of the proposed scheme compared to the existing ones. | SI Pengbo ZHANG Qian F. Richard YU ZHANG Yanhua | 2014 | China Communications2014，11，5： | 7 |
| 2 | Selective transmission and channel estimation in massive MIMO systems显示文摘Massive MIMO systems have got extraordinary spectral efficiency using a large number of base station antennas,but it is in the challenge of pilot contamination using the aligned pilots.To address this issue,a selective transmission is proposed using time-shifted pilots with cell grouping,where the strong interfering users in downlink transmission cells are temporally stopped during the pilots transmission in uplink cells.Based on the spatial characteristics of physical channel models,the strong interfering users are selected to minimize the inter-cell interference and the cell grouping is designed to have less temporally stopped users within a smaller area.Furthermore,a Kalman estimator is proposed to reduce the unexpected effect of residual interferences in channel estimation,which exploits both the spatial-time correlation of channels and the share of the interference information.The numerical results show that our scheme significantly improves the channel estimation accuracy and the data rates. | 杨睿哲 Zong Liang Si Pengbo Ma Dawei Zhang Yanhua | 2016 | High Technology Letters2016，22，1： | 5 |
| 3 | Blockchain and MEC-Assisted Reliable Billing Data Transmission over Electric Vehicular Network:An Actor–Critic RL Approach显示文摘Recently,electric vehicles(EVs)have been widely used under the call of green travel and environmental protection,and diverse requirements for charging are also increasing gradually.In order to ensure the authenticity and privacy of charging information interaction,blockchain technology is proposed and applied in charging station billing systems.However,there are some issues in blockchain itself,including lower computing efficiency of the nodes and higher energy consumption in the consensus process.To handle the above issues,in this paper,combining blockchain and mobile edge computing(MEC),we develop a reliable billing data transmission scheme to improve the computing capacity of nodes and reduce the energy consumption of the consensus process.By jointly optimizing the primary and replica nodes offloading decisions,block size and block interval,the transaction throughput of the blockchain system is maximized,as well as the latency and energy consumption of the system are minimized.Moreover,we formulate the joint optimization problem as a Markov decision process(MDP).To tackle the dynamic and continuity of the system state,the reinforcement learning(RL)is introduced to solve the MDP problem.Finally,simulation results demonstrate that the performance improvement of the proposed scheme through comparison with other existing schemes. | Xinyu Ye Meng Li Pengbo Si Ruizhe Yang Enchang Sun Yanhua Zhang | 2021 | China Communications2021，18，8： | 3 |
| 4 | Optimal Cooperative Internetwork Spectrum Sharing for Cognitive Radio Systems with Spectrum Pooling显示文摘 | SI Pengbo JI Hong YU F R | 2010 | IEEE Transactions on Vehicular Technology2010，59，4： | 1 |
| 5 | Proximal Policy Optimization-Based Committee Selection Algorithm in Blockchain-Enabled Mobile Edge Computing Systems显示文摘To cope with the low latency requirements and security issues of the emerging applications such as Internet of Vehicles(Io V)and Industrial Internet of Things(IIo T),the blockchain-enabled Mobile Edge Computing(MEC)system has received extensive attention.However,blockchain is a computing and communication intensive technology due to the complex consensus mechanisms.To facilitate the implementation of blockchain in the MEC system,this paper adopts the committee-based Practical Byzantine Fault Tolerance(PBFT)consensus algorithm and focuses on the committee selection problem.Vehicles and IIo T devices generate the transactions which are records of the application tasks.Base Stations(BSs)with MEC servers,which serve the transactions according to the wireless channel quality and the available computing resources,are blockchain nodes and candidates for committee members.The income of transaction service fees,the penalty of service delay,the decentralization of the blockchain and the communication complexity of the consensus process constitute the performance index.The committee selection problem is modeled as a Markov decision process,and the Proximal Policy Optimization(PPO)algorithm is adopted in the solution.Simulation results show that the proposed PPO-based committee selection algorithm can adapt to the system design requirements with different emphases and outperforms other comparison methods. | Wenjun Wu Dehao Sun Kaiqi Jin Yang Sun Pengbo Si | 2022 | China Communications2022，19，6： | 1 |
| 6 | Deep reinforcement learning based worker selection for distributed machine learning enhanced edge intelligence in internet of vehicles显示文摘Nowadays,Edge Information System(EIS)has received a lot of attentions.In EIS,Distributed Machine Learning(DML),which requires fewer computing resources,can implement many artificial intelligent applications efficiently.However,due to the dynamical network topology and the fluctuating transmission quality at the edge,work node selection affects the performance of DML a lot.In this paper,we focus on the Internet of Vehicles(IoV),one of the typical scenarios of EIS,and consider the DML-based High Definition(HD)mapping and intelligent driving decision model as the example.The worker selection problem is modeled as a Markov Decision Process(MDP),maximizing the DML model aggregate performance related to the timeliness of the local model,the transmission quality of model parameters uploading,and the effective sensing area of the worker.A Deep Reinforcement Learning(DRL)based solution is proposed,called the Worker Selection based on Policy Gradient(PG-WS)algorithm.The policy mapping from the system state to the worker selection action is represented by a deep neural network.The episodic simulations are built and the REINFORCE algorithm with baseline is used to train the policy network.Results show that the proposed PG-WS algorithm outperforms other comparation methods. | Junyu Dong Wenjun Wu Yang Gao Xiaoxi Wang Pengbo Si | 2020 | Intelligent and Converged Networks2020，1，3： | 1 |
| 7 | Optimal cooperative internetwork spectrum sharing for cognitive radios systems with spectrum pooling显示文摘 | Si Pengbo Ji Hong Yu Fei | | 0，，05： | 1 |
| 8 | Distributed Sender Scheduling for Multimedia Transmis- sion in Wireless Mobile Peer-to-Peer Net- works显示文摘 | SI Pengbo YU F R JI Hong | 2009 | IEEE Transaction on Wireless Com- munications2009，8，9： | 1 |
| 9 | Distributed Sender Scheduling for Multimedia Transmis- sion in Wireless Mobile Peer-to-Peer Networks 显示文摘 | SI Pengbo YU F R JI Hong | 2009 | IEEE Transactions on Wireless Communi- cations2009，8，9： | 1 |
| 10 | Carbon nanodots enhanced performance of Cs_(0.15)FA_(0.85)PbI_(3) perovskite solar cells显示文摘A high-quality hybrid Cs_(0.15)FA_(0.85)PbI_(3) thin film is deposited through doping of carbon nanodots(CNDs)into perovskite precursor solution.The corresponding inverted planar perovskite solar cells(PSCs)of ITO/PTAA/Cs_(0.15)FA_(0.85)PbI_(3)/PC_(61)BM/BCP/Ag exhibit an improvement in efficiency from 17.36%to 20.06%,which could be attributed to the passivation of the defects at the crystallized perovskite thin film and enhanced perovskite phase uniformity.The results of electron trap density indicate that the addition of CNDs significantly reduces the defects density at the perovskite thin film and the recombination of charge carriers in transport process is minimized.These results demonstrate that low-cost CNDs are effective additives for passivating defects,further reducing charge carrier recombination and improving device efficiency. | Yu Gao Wenzhan Xu Fang He Pengbo Nie Qingdan Yang Zhichun Si Hong Meng Guodan Wei | 2021 | Nano Research2021，14，7： | 0 |
| 11 | Deep reinforcement learning based task offloading in blockchain enabled smart city显示文摘With the expansion of cities and emerging complicated application,smart city has become an in-telligent management mechanism.In order to guarantee the information security and quality of service(QoS)of the Internet of Thing(IoT)devices in the smart city,a mobile edge computing(MEC)en-abled blockchain system is considered as the smart city scenario where the offloading process of com-puting tasks is a key aspect infecting the system performance in terms of service profit and latency.The task offloading process is formulated as a Markov decision process(MDP)and the optimal goal is the cumulative profit for the offloading nodes considering task profit and service latency cost,under the restriction of system timeout as well as processing resource.Then,a policy gradient based task of-floading(PG-TO)algorithm is proposed to solve the optimization problem.Finally,the numerical re-sult shows that the proposed PG-TO has better performance than the comparison algorithm,and the system performance as well as QoS is analyzed respectively.The testing result indicates that the pro-posed method has good generalization. | 金凯琦 WU Wenjun GAO Yang YIN Yufen SI Pengbo | 2023 | High Technology Letters2023，29，3： | 0 |
| 12 | Pseudo-label based semi-supervised learning in the distributed machine learning framework显示文摘With the emergence of various intelligent applications,machine learning technologies face lots of challenges including large-scale models,application oriented real-time dataset and limited capabilities of nodes in practice.Therefore,distributed machine learning(DML) and semi-supervised learning methods which help solve these problems have been addressed in both academia and industry.In this paper,the semi-supervised learning method and the data parallelism DML framework are combined.The pseudo-label based local loss function for each distributed node is studied,and the stochastic gradient descent(SGD) based distributed parameter update principle is derived.A demo that implements the pseudo-label based semi-supervised learning in the DML framework is conducted,and the CIFAR-10 dataset for target classification is used to evaluate the performance.Experimental results confirm the convergence and the accuracy of the model using the pseudo-label based semi-supervised learning in the DML framework.Given the proportion of the pseudo-label dataset is 20%,the accuracy of the model is over 90% when the value of local parameter update steps between two global aggregations is less than 5.Besides,fixing the global aggregations interval to 3,the model converges with acceptable performance degradation when the proportion of the pseudo-label dataset varies from 20% to 80%. | 王晓曦 WU Wenjun YANG Feng SI Pengbo ZHANG Xuanyi ZHANG Yanhua | 2022 | High Technology Letters2022，28，2： | 0 |
| 13 | The adaptive distributed learning based on homomorphic encryption and blockchain显示文摘The privacy and security of data are recently research hotspots and challenges.For this issue,an adaptive scheme of distributed learning based on homomorphic encryption and blockchain is proposed.Specifically,in the form of homomorphic encryption,the computing party iteratively aggregates the learning models from distributed participants,so that the privacy of both the data and model is ensured.Moreover,the aggregations are recorded and verified by blockchain,which prevents attacks from malicious nodes and guarantees the reliability of learning.For these sophisticated privacy and security technologies,the computation cost and energy consumption in both the encrypted learning and consensus reaching are analyzed,based on which a joint optimization of computation resources allocation and adaptive aggregation to minimize loss function is established with the realistic solution followed.Finally,the simulations and analysis evaluate the performance of the proposed scheme. | 杨睿哲 ZHAO Xuehui ZHANG Yanhua SI Pengbo TENG Yinglei | 2022 | High Technology Letters2022，28，4： | 0 |
| 14 | A stream layered cooperative relay multicast scheme and capacity analysis in cellular systems显示文摘 | 王成金 Si Pengbo Li Yi Zhang Lin Ji Hong | 2011 | High Technology Letters2011，17，4： | 0 |
| 15 | Optimal energy-efficient power control for cognitive radio based on static and dynamic features of primary users显示文摘 | Ge Wendong Ji Hong Si Pengbo | 2011 | High Technology Letters2011，17，4： | 0 |
| 16 | Spectrum sensing sequence prediction in cognitive radio networks显示文摘 | An Chunyan Ji Hong Si Pengbo Maoxu | 2011 | High Technology Letters2011，17，4： | 0 |
| 17 | Analysis and Optimization of Validation Procedure in Blockchain-Enhanced Wireless Resource Sharing and Transactions显示文摘To ensure the security of resource and intelligence sharing in 6G,blockchain has been widely adopted in wireless communications and applications.Although blockchain can ensure the traceability and non-tamperability of data in the concatenated blocks,it cannot guarantee the honest behaviors of users in the application before the generation of transactions.Thus,additional technologies are required to ensure that the source of blockchain data is reliable.In this paper,the detailed procedure is designed for the application-oriented task validation in the blockchainenhanced computing resource sharing and transactions in ultra dense networks(UDN).The corresponding queuing model is built and analyzed with the consideration of the wireless re-transmission and the probability of malicious deception by users.Based on the analysis results,the UDN deployment is optimized to save network cost while ensuring latency performance.Numerical results verify our analysis,and the optimized system deployment including the number and service capacities of both base stations and mobile edge computing(MEC)servers are also given with various system settings. | Enyu Du Yang Gao Wenjun Wu Zhaoxin Yang Yufeng Yin Pengbo Si | 2023 | China Communications2023，20，10： | 0 |
| 18 | Optimal Spectrum Management with Dynamic Service and Cost Constraints in Multihop CR Networks显示文摘 | Qiuran Li Pengbo Si Ruizhe Yang Yanhua Zhang | 2016 | 信息工程期刊(中英文版)2016，6，4： | 0 |
| 19 | Error propagation determined iterative channel estimation with ICI mitigation for fast time-varying OFDM channels显示文摘The intersubcarrier interference(ICI) degrades the performance of the pilot-aided channel estimation in fast time-varying orthogonal frequency division multiplexing(OFDM) systems.To solve the error propagation in joint channel estimation and data detection due to this ICI,a scheme of error propagation determined iterative estimation is proposed,where in the first iteration,Kalman filter based on signal to interference and noise is designed with ICI transformed to be part of the noise,and for the later iterations,a determined iterative estimation algorithm obtains an optimal output from all iterations using the iterative updating strategy.Simulation results present the significant improvement in the performance of the proposed scheme in high-mobility situation in comparison with the existing ones. | 张杰 Yang Ruizhe Si Pengbo Zhang Yanhua Yu Richard | 2014 | High Technology Letters2014，20，4： | 0 |
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