2022 IEEE 8th International Conference on Computer and Communications (ICCC)最新文献

Design and Implementation of CNC Lathe Automatic Processing Unit Information Model Based on OPC UA 基于OPC UA的数控车床自动加工单元信息模型的设计与实现

2022 IEEE 8th International Conference on Computer and Communications (ICCC) Pub Date : 2022-12-09 DOI: 10.1109/ICCC56324.2022.10065741

Dongwei Wang, Lunxing Li, Liaomo Zheng, Beibei Li, Xingjun Liu, Xiaoting Song

引用次数: 0

A Neural Network Binary Quantization Method Based on W-Regularization and Variable Cosine Momentum 基于w正则化和变余弦动量的神经网络二值量化方法

2022 IEEE 8th International Conference on Computer and Communications (ICCC) Pub Date : 2022-12-09 DOI: 10.1109/ICCC56324.2022.10065794

Chang Liu, Yingxi Chen

引用次数: 0

A Modified Signal Reconstruction Method in Low Feedback Sampling Rate Digital Predistortion 一种改进的低反馈采样率数字预失真信号重构方法

2022 IEEE 8th International Conference on Computer and Communications (ICCC) Pub Date : 2022-12-09 DOI: 10.1109/ICCC56324.2022.10065817

Jiayan Wu, Bin Song, Songbai He, Chang Wu

引用次数: 0

Measurement and Analysis of LoRa Transmission Performance in Subway Station 地铁车站LoRa传输性能的测量与分析

2022 IEEE 8th International Conference on Computer and Communications (ICCC) Pub Date : 2022-12-09 DOI: 10.1109/ICCC56324.2022.10065792

Chunyu Liu, R. He, R. Xu, Ruifeng Chen, Jie Lv, Wei Zhang, Shaopeng Wang, Weiming Li, Wenpu Sun, Lizhe Li

{"title":"Measurement and Analysis of LoRa Transmission Performance in Subway Station","authors":"Chunyu Liu, R. He, R. Xu, Ruifeng Chen, Jie Lv, Wei Zhang, Shaopeng Wang, Weiming Li, Wenpu Sun, Lizhe Li","doi":"10.1109/ICCC56324.2022.10065792","DOIUrl":"https://doi.org/10.1109/ICCC56324.2022.10065792","url":null,"abstract":"Developing smart stations has become an important trend for the future rail traffic system, and the realization requires using Internet of Things (IoT) technology to improve performance. Although it has been widely considered to develop an IoT wireless sensor network to monitor subway station environment, there is still a lack of realistic measurement for deployment of IoT in station. In this paper, performances of long range (LoRa) and Narrow Band Internet of Things (NB-IoT) in subway station scenario are investigated. The transmission performances of LoRa in subway concourse, platforms, and passage scenarios are measured and evaluated. The received signal strength indication (RSSI), packet loss rate, and transmission delay are discussed based on measurements. It is found that LoRa performs fairly well in subway concourse and platform scenarios, with RSSI of more than -70 dBm and packet loss rate of less than 1%. However, in subway passage scenario, RSSI is relatively low and packet loss rate can be high. These results are helpful for deploying LoRa system in subway stations.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"260 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117348452","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: 0

Distributed Precoder Design for Uplink TDD MU-MIMO Systems 上行TDD MU-MIMO系统的分布式预编码器设计

2022 IEEE 8th International Conference on Computer and Communications (ICCC) Pub Date : 2022-12-09 DOI: 10.1109/ICCC56324.2022.10066015

Jiyu Dong, Yi Sun, Rong Fu, Chunming Zhao, Ming Jiang

{"title":"Distributed Precoder Design for Uplink TDD MU-MIMO Systems","authors":"Jiyu Dong, Yi Sun, Rong Fu, Chunming Zhao, Ming Jiang","doi":"10.1109/ICCC56324.2022.10066015","DOIUrl":"https://doi.org/10.1109/ICCC56324.2022.10066015","url":null,"abstract":"In the existing designs for uplink multi-user Multiinput Multi-output (MU-MIMO) systems, centralized schemes usually provide good performance where the precoder is com-puted by the base station (BS) and then fed back to each terminal. However, this brings huge amounts of feedback overhead and therefore is hard to implement. The 5G protocol supports the use of the uplink codebook to deploy a precoder, hence the feedback cost is significantly compressed by transmitting only the index. In this letter, we develop a novel distributed precoder design for the uplink time division duplex (TDD) MU-MIMO systems subject to the transmit power constraint in terms of each terminal or each antenna. Taking both the error rate performance and the feedback overhead into account, the proposed scheme allows each terminal to obtain its own precoder based on the alternating optimization. Under the distributed strategy, no precoder feedback is required for the system, while with acceptable performance loss. In addition to the analysis, simulation results are presented to validate the effectiveness of the proposed scheme.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124947741","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 275GHz to 296GHz Power Amplifier Using Embedding Network in 65nm-CMOS with 29.4dB Peak Power Gain 基于嵌入网络的65nm cmos 275GHz至296GHz功率放大器，峰值功率增益29.4dB

2022 IEEE 8th International Conference on Computer and Communications (ICCC) Pub Date : 2022-12-09 DOI: 10.1109/ICCC56324.2022.10065736

Jianguo Yu, Zhiyao Wang

引用次数: 0

Simultaneous Detection of Helmet and Mask Wearing Based on YOLO Improved Algorithm 基于YOLO改进算法的头盔和面罩佩戴同步检测

2022 IEEE 8th International Conference on Computer and Communications (ICCC) Pub Date : 2022-12-09 DOI: 10.1109/ICCC56324.2022.10066031

Xiaojun Xia, Wenkang Shi, Ying Gao

引用次数: 1

A Short-Term Load Forecasting Method via Model Selection Based on Random Forest 基于随机森林模型选择的短期负荷预测方法

2022 IEEE 8th International Conference on Computer and Communications (ICCC) Pub Date : 2022-12-09 DOI: 10.1109/ICCC56324.2022.10065825

Ziyi Li, Jingyi Zhang, Wenpeng Jing, Zhaoming Lu, Wei Zheng, X. Wen

{"title":"A Short-Term Load Forecasting Method via Model Selection Based on Random Forest","authors":"Ziyi Li, Jingyi Zhang, Wenpeng Jing, Zhaoming Lu, Wei Zheng, X. Wen","doi":"10.1109/ICCC56324.2022.10065825","DOIUrl":"https://doi.org/10.1109/ICCC56324.2022.10065825","url":null,"abstract":"Short-term load forecasting(STLF) is an essential module of energy management system, which is of great signifi-cance to the economic dispatch and operation stability in smart grid. There is a large collection of methods developed for STLF, but it is still challenging to provide high precision STLF under different weather conditions which are the main factors affecting power generation load, especially for distributed photovoltaic power generation load. A short-term load forecasting method via model selection based on random forest is proposed in this paper to realize reliable and accurate daily power generation load forecasting under different conditions. We first perform clustering analysis on the raw data through K-means. In particular, we consider both weighted meteorological factors and historical load to improve clustering performance. Secondly, we establish a model pool consisting of state-of-the-art machine learning(ML) models which is selected from four alternative ML models, and each model is the best model for each cluster. Then, we train a random forest based on each set of data and its optimal model label. In the prediction stage, random forest is utilized to directly select an appropriate model from model pool to obtain the final prediction load. The performance of the proposed method is validated on real generation load of practical scenarios. The result indicates the superiority and advantages of the model selection based STLF method compared with the single model methods, and the mean absolute error(MAE), root mean square error(RMSE) and mean absolute percentage error(MAPE) are reduced by 118.5054(KW), 10.43% and 2.08%, respectively.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"169 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123791698","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: 0

ICTCAM: Introducing Convolution to Transformer-Based Weakly Supervised Semantic Segmentation 将卷积引入到基于变压器的弱监督语义分割

2022 IEEE 8th International Conference on Computer and Communications (ICCC) Pub Date : 2022-12-09 DOI: 10.1109/ICCC56324.2022.10065791

Diaoyin Tan, Yu Liu, Huaxin Xiao, Yang Peng, Maojun Zhang

引用次数: 0

Deep Reinforcement Learning Based UAV Trajectory Design for Data Collection Scenario with No-Fly Zones 基于深度强化学习的禁飞区数据采集场景无人机轨迹设计

2022 IEEE 8th International Conference on Computer and Communications (ICCC) Pub Date : 2022-12-09 DOI: 10.1109/ICCC56324.2022.10065712

Yunfei Gao, Mingliu Liu, Ziwei Mei, Yulin Hu

{"title":"Deep Reinforcement Learning Based UAV Trajectory Design for Data Collection Scenario with No-Fly Zones","authors":"Yunfei Gao, Mingliu Liu, Ziwei Mei, Yulin Hu","doi":"10.1109/ICCC56324.2022.10065712","DOIUrl":"https://doi.org/10.1109/ICCC56324.2022.10065712","url":null,"abstract":"Recently, unmanned aerial vehicle (UAV)-assisted communication system has been introduced as a promising paradigm for the future space-aerial-terrestrial integrated communications. In this paper, we investigate an UAV communication system, where the UAV is employed to assist multiple ground loT devices for data collection in the area of interest with the existence of no-fly zones. Unlike existing approaches focusing only on simplified line-of-sigh (LoS)-dominant channel model, this paper considers a more practical probability LoS channel model, which considers path loss and shadowing. On the premise of satisfying the data throughput requirements of all ground loT devices, we intend to minimize the total task completion time by jointly optimizing UAV's trajectory and communication scheduling. To tackle the non-convex and difficult intractable problem, we first transform the original problem into an Markov decision process (MDP) problem, and then we propose a trajectory design solution based on deep reinforcement learning (DRL) algorithm for completion time minimization. The UAV serves as an agent in the process of execution algorithm, interacting with the environment and constantly improving its own mobile strategy. Finally, numerical results demonstrate that the proposed design contributes to significant performance enhancement and can be applied to practical scenarios with no-fly zones.","PeriodicalId":263098,"journal":{"name":"2022 IEEE 8th International Conference on Computer and Communications (ICCC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122356650","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: 0