2019 IEEE 19th International Conference on Communication Technology (ICCT)最新文献_第6页

CANDECOMP&PARAFAC-based Near-Field Source Localization by Passive Sensor Arrays 基于candecomp&parafac的无源传感器阵列近场源定位

2019 IEEE 19th International Conference on Communication Technology (ICCT) Pub Date : 2019-10-01 DOI: 10.1109/ICCT46805.2019.8947311

Haoyue Xiao, Yubai Li

引用次数: 0

Multi-layer Attention Mechanism Based Speech Separation Model 基于多层注意机制的语音分离模型

2019 IEEE 19th International Conference on Communication Technology (ICCT) Pub Date : 2019-10-01 DOI: 10.1109/ICCT46805.2019.8947242

M. Li, Tian Lan, Chuan Peng, Yuxin Qian, Qiao Liu

引用次数: 3

Computation Offloading and Resource Allocation for MEC in C-RAN: A Deep Reinforcement Learning Approach C-RAN中MEC的计算卸载和资源分配:一种深度强化学习方法

2019 IEEE 19th International Conference on Communication Technology (ICCT) Pub Date : 2019-10-01 DOI: 10.1109/ICCT46805.2019.8947070

Xiaoyan Jin, Jun Zhang, Xinghua Sun, Ping Zhang, Shu Cai

{"title":"Computation Offloading and Resource Allocation for MEC in C-RAN: A Deep Reinforcement Learning Approach","authors":"Xiaoyan Jin, Jun Zhang, Xinghua Sun, Ping Zhang, Shu Cai","doi":"10.1109/ICCT46805.2019.8947070","DOIUrl":"https://doi.org/10.1109/ICCT46805.2019.8947070","url":null,"abstract":"Mobile edge computing (MEC) technology has become a promising example for cloud radio access networks (CRAN) to provide close-range services, thereby reducing service delays and saving energy consumption. In this paper, we consider a multi-user MEC system and solve the problem of the computation offloading strategies and resource allocation policies. We set the total cost of delays and energy consumption as our optimization goal. However, getting an optimal strategy in a dynamic environment is challenging. Reinforcement learning (RL) aims at long-term cumulative rewards, which are essential for time-varying dynamic systems. Therefore, we propose an optimization framework based on deep RL to solve these problems. The deep neural network (DNN) is used to estimate the value function of the critics, thereby reducing the state space complexity of the optimization target. The actor part uses another DNN to represent a parametritis stochastic strategy and improve the strategy with the help of critics. Compared with other schemes, the simulation results show that the scheme significantly reduces the total cost.","PeriodicalId":306112,"journal":{"name":"2019 IEEE 19th International Conference on Communication Technology (ICCT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115775485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Deep Learning Architecture for Broadband DOA Estimation 宽带DOA估计的深度学习体系结构

2019 IEEE 19th International Conference on Communication Technology (ICCT) Pub Date : 2019-10-01 DOI: 10.1109/ICCT46805.2019.8947053

Wenli Zhu, Min Zhang

{"title":"A Deep Learning Architecture for Broadband DOA Estimation","authors":"Wenli Zhu, Min Zhang","doi":"10.1109/ICCT46805.2019.8947053","DOIUrl":"https://doi.org/10.1109/ICCT46805.2019.8947053","url":null,"abstract":"An efficient neural network-based approach for broadband direction of arrival (DOA) estimation is presented in this paper. The received data of the uniform circle array (UCA) is transformed into direction image, which is used as the input of the neural network. The phase component of the spatial covariance matrix of the received signal is extracted to form the direction image. We establish a convolutional neural network (CNN) with five hidden layers to learn the inverse mapping from the space of possible antenna element excitations to the space of possible angular directions to the signal source. DOA estimation is formulated as a regression problem, where the each DOA label to the direction image is consisted of the sine and cosine values of the angle of arrival. Simulation results show that the trained CNN network can be successfully used for broadband DOA estimation. The performance of the developed CNN model is comparable to the performance of the conventional algorithms at the lower signal-to-noise ratio. Importantly, the proposed CNN estimator further reduces the computation time which makes it successful to apply to real-time applications.","PeriodicalId":306112,"journal":{"name":"2019 IEEE 19th International Conference on Communication Technology (ICCT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124484179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 18

A New Channel Estimation Algorithm for Time-Varying Multi-Path Channel in MIMO-OFDM Systems MIMO-OFDM系统时变多径信道估计新算法

2019 IEEE 19th International Conference on Communication Technology (ICCT) Pub Date : 2019-10-01 DOI: 10.1109/ICCT46805.2019.8947205

Can Liu, Chucheng Chen, Jianbin Lu, X. Dai

引用次数: 1

Interference Alignment Algorithm for High-Speed Railway Wireless Communication Based on Mobile User Classification 基于移动用户分类的高速铁路无线通信干扰对准算法

2019 IEEE 19th International Conference on Communication Technology (ICCT) Pub Date : 2019-10-01 DOI: 10.1109/ICCT46805.2019.8947246

Ziwen Tang, Jie Sheng, Cheng Wu, Yiming Wang

引用次数: 0

Delay CoMP of LoRa Modulation in Wireless Tree Topology Network 无线树状拓扑网络中LoRa调制的时延比较

2019 IEEE 19th International Conference on Communication Technology (ICCT) Pub Date : 2019-10-01 DOI: 10.1109/ICCT46805.2019.8947128

Hongqiang Li, Yubing Zhang, Xu Zhao, Xiaoke Tang

{"title":"Delay CoMP of LoRa Modulation in Wireless Tree Topology Network","authors":"Hongqiang Li, Yubing Zhang, Xu Zhao, Xiaoke Tang","doi":"10.1109/ICCT46805.2019.8947128","DOIUrl":"https://doi.org/10.1109/ICCT46805.2019.8947128","url":null,"abstract":"The rapid development of Internet of Things (IoT) puts forward much requirements for wireless communication technology. Low Power Wide Area Networks (LPWAN) are designed for low bandwidth, low power, long range and large number of connected IoT applications. As one of the LPWAN, Low Power Long Range Transceiver (LoRa) described as a Frequency Shift Chirp Modulation (FSCM), is widely concerned and studied. In this paper, the signal reception of LoRa modulation in the wireless tree topology is analyzed, and the multi-user interference analysis proves that the multi-user interference has a great impact on the system performance. At the same time, we proposed Delay Coordinated Multiple Points Transmission (DCoMP). Multiple nodes close to each other send the same data to the target node. Due to the inaccuracy of synchronization between nodes, there will be a certain timing offset when sending signals to the same target node. After combining signals of multiple nodes according to different timing offset, the receiver performance of signals can be improved. The coordinated nodes can also actively adjust the signal sending timing according to the path time delay and processing delay, so as to improve the receiving performance of the signal merging algorithm of the receiver node. LoRa modulation improves the signal reception performance by adopting DCoMP transmission, thus improving the overall throughput of the system.","PeriodicalId":306112,"journal":{"name":"2019 IEEE 19th International Conference on Communication Technology (ICCT)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123552931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

MMSE-based Detector for Generalized Space-Time-Frequency Index Modulation Systems with Carrier Frequency Offsets 载波频偏广义空时频指数调制系统基于mmse的检波器

2019 IEEE 19th International Conference on Communication Technology (ICCT) Pub Date : 2019-10-01 DOI: 10.1109/ICCT46805.2019.8947006

Shiwen Fan, Shu Fang, Yan Zhao, Yue Xiao, Xiaotian Zhou

引用次数: 1

Implementation of Encryption and Decryption Algorithms for Security of Mobile Devices 移动设备安全加解密算法的实现

2019 IEEE 19th International Conference on Communication Technology (ICCT) Pub Date : 2019-10-01 DOI: 10.1109/ICCT46805.2019.8947111

B. Varun, V. AbhishekM., A. Gangadhar, U. Purushotham

引用次数: 2

Simulation of CBMeMber Multi-target Tracking Algorithm Based on Gauss Mixture 基于高斯混合的CBMeMber多目标跟踪算法仿真

2019 IEEE 19th International Conference on Communication Technology (ICCT) Pub Date : 2019-10-01 DOI: 10.1109/ICCT46805.2019.8947076

Linxi Wang, Xiaoxi Hu, Xun Han, Yin Kuang, Xinquan Yang

引用次数: 0