2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)最新文献_第2页

2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) Pub Date : 2021-09-13 DOI: 10.1109/PIMRC50174.2021.9569677

Ling Huang, Kuan Wu, M. Jiang

引用次数: 0

GPAE-LSTMnet: A Novel Learning Structure for Mobile MIMO Channel Prediction GPAE-LSTMnet:一种新的移动MIMO信道预测学习结构

2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) Pub Date : 2021-09-13 DOI: 10.1109/PIMRC50174.2021.9569281

Zhuoran Xiao, Zhaoyang Zhang, Chongwen Huang, C. Zhong, Xiaoming Chen

{"title":"GPAE-LSTMnet: A Novel Learning Structure for Mobile MIMO Channel Prediction","authors":"Zhuoran Xiao, Zhaoyang Zhang, Chongwen Huang, C. Zhong, Xiaoming Chen","doi":"10.1109/PIMRC50174.2021.9569281","DOIUrl":"https://doi.org/10.1109/PIMRC50174.2021.9569281","url":null,"abstract":"Mobile channel estimation is very challenging as usually it requires more pilots and channel observations to obtain the channel state information (CSI) and the resultant estimation accuracy may decrease with the number of antennas and sub-carriers. Through exploring the long-and-short-term intrinsic spatial and temporal correlation among a set of historic channel instances randomly obtained within a certain communication environment, channel prediction can help increase the CSI accuracy w.r.t. to that obtained from only the pilots, and thus save signaling overhead and computational cost. In this paper, we propose a novel generative Periodic-Activator-enabled Auto Encoder-LSTM network (GPAE-LSTMnet) for accurate channel prediction of mobile MIMO channels, which first compresses the high dimensional channel matrix with high-frequency features to a low dimensional space with relatively low-frequency feature space that has high data smoothness and is suitable for time-series sequence prediction. After that, a LSTM network is used to predict the channel in the low dimensional space, which ensures high accuracy and low computational cost. Experimental results show that our proposed learning structure outperforms existing methods especially when the dimension of CSI to be predicted is relatively high, the time interval of the CSI sequence is relatively long and the number of network parameters is highly limited.","PeriodicalId":283606,"journal":{"name":"2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126998943","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: 4

Comparison of Multi-Connectivity Schemes on Different Layers for Reliable Low Latency Communication 可靠低延迟通信的不同层多连接方案的比较

2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) Pub Date : 2021-09-13 DOI: 10.1109/pimrc50174.2021.9569560

Marie-Theres Suer, Christoph Thein, H. Tchouankem, L. Wolf

{"title":"Comparison of Multi-Connectivity Schemes on Different Layers for Reliable Low Latency Communication","authors":"Marie-Theres Suer, Christoph Thein, H. Tchouankem, L. Wolf","doi":"10.1109/pimrc50174.2021.9569560","DOIUrl":"https://doi.org/10.1109/pimrc50174.2021.9569560","url":null,"abstract":"Wireless communication systems which provide low latency with high reliability are required for emerging industrial applications such as closed-loop control systems or mobile robotics. Multi-Connectivity (MC), i.e., using multiple communication paths simultaneously, can be a measure to enhance latency and reliability performance of wireless communication systems. MC schemes can be applied on different layers of the communication stack. While Physical (PHY) Layer MC schemes combine the paths at signal or symbol level, in higher layer schemes, i.e., MC schemes on MAC Layer or above, the paths are combined at packet level. Higher layer schemes provide more degrees of freedom for dynamic scheme adaptation, while PHY MC schemes have more information available. MC schemes on different layers need to be compared to evaluate their suitability to enhance latency and reliability performance in different scenarios. In this work system level simulations are performed with the network simulator ns-3 to compare PHY Layer MC schemes, i.e., selection combining (SC), maximum ratio combining (MRC) and joint decoding (JD), with higher layer MC schemes, i.e., MP-UDP with packet duplication (PD). Our results suggest that the gain of PHY Layer MC schemes increases with decreasing SINR. The higher layer MC schemes provide diversity not only on PHY but also on MAC and higher layers and could thus decrease access and queuing latency. The gain of MP-UDP increases with increasing network load. The insights obtained in this work can be used to develop dynamic MC schedulers that activate or deactivate certain MC schemes or switch between MC schemes on different layers based on the scenario.","PeriodicalId":283606,"journal":{"name":"2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130650504","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: 3

On the Secrecy-Reliability Performance Trade-off for NOMA-enabled 5G mmWave Networks 基于noma的5G毫米波网络的保密性与可靠性性能权衡

2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) Pub Date : 2021-09-13 DOI: 10.1109/pimrc50174.2021.9569610

Sourabh Solanki, D. Gurjar, P. Sharma, S. Sharma, S. Chatzinotas

{"title":"On the Secrecy-Reliability Performance Trade-off for NOMA-enabled 5G mmWave Networks","authors":"Sourabh Solanki, D. Gurjar, P. Sharma, S. Sharma, S. Chatzinotas","doi":"10.1109/pimrc50174.2021.9569610","DOIUrl":"https://doi.org/10.1109/pimrc50174.2021.9569610","url":null,"abstract":"The evolution of 5G wireless networks poses significant research challenges such as securing the user data, maintaining certain latency and reliability requirements etc. However, it can be challenging to simultaneously meet these performance requisites, which may lead to resort to a trade-off among different metrics. This paper investigates the secrecy-reliability performance trade-off (SRPT) for non-orthogonal multiple access (NOMA)-based millimeter wave (mmWave) networks. Herein, we consider two end-users, namely primary and secondary, which are served by an mmWave base station using downlink NOMA. Besides, a passive eavesdropper lying in the vicinity of these end-users attempts to intercept their legitimate message signals. For this set-up, we derive the closed-form expressions of the outage probability (OP) of a targeted end-user and intercept probability (IP) of the eavesdropper to analyze the SRPT of the system. We further propose a low-complexity average channel state information (CSI)-based power allocation strategy to improve the reliability of a targeted user while maintaining its information secrecy. Moreover, we obtain the condition under which NOMA guarantees superior secrecy performance than that of orthogonal multiple access (OMA) scheme. We corroborate our theoretical analysis via simulation results presented in terms of IP and OP.","PeriodicalId":283606,"journal":{"name":"2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123940077","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: 3

Sidelink-Assisted URLLC Built on Cooperative Retransmissions With Optimum Power Control 基于最优功率控制的协同重传的边链辅助URLLC

2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) Pub Date : 2021-09-13 DOI: 10.1109/PIMRC50174.2021.9569334

Tapisha Soni, M. Schellmann, Alois Knoll

{"title":"Sidelink-Assisted URLLC Built on Cooperative Retransmissions With Optimum Power Control","authors":"Tapisha Soni, M. Schellmann, Alois Knoll","doi":"10.1109/PIMRC50174.2021.9569334","DOIUrl":"https://doi.org/10.1109/PIMRC50174.2021.9569334","url":null,"abstract":"The fifth generation of wireless technology (5G) has advanced exceptionally in the past few years, giving rise to challenging quality of service (QoS) requirements and diverse deployment scenarios. Among the set of available services, ultra-reliable low-latency communication (URLLC) imposes stringent reliability and latency requirements. For improving the reliability under strict latency constraints in an error-prone downlink (DL), we have proposed a sidelink (SL)-assisted cooperative retransmission scheme, which takes advantage of multiple independently fading device-to-device (D2D) links. For the cooperative scheme, power control is useful for balanced user contributions and to control additional interference imposed to the system. Hence, this paper focuses on designing an optimal power control for the cooperative sidelink retransmission scheme, which gradually increments the power with every retransmission attempt. The objective is to utilize minimum power without compromising the desired latency and reliability performance. Results from system level evaluation reveal significant power savings in comparison to the reference power control scheme, which uses the maximum transmit power per device, limited by the DL path-loss power constraint only.","PeriodicalId":283606,"journal":{"name":"2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123685594","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

Deep Learning-Based Estimator for Fast HARQ Feedback in URLLC 基于深度学习的URLLC快速HARQ反馈估计方法

2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) Pub Date : 2021-09-13 DOI: 10.1109/PIMRC50174.2021.9569443

Saleh Almarshed, D. Triantafyllopoulou, K. Moessner

{"title":"Deep Learning-Based Estimator for Fast HARQ Feedback in URLLC","authors":"Saleh Almarshed, D. Triantafyllopoulou, K. Moessner","doi":"10.1109/PIMRC50174.2021.9569443","DOIUrl":"https://doi.org/10.1109/PIMRC50174.2021.9569443","url":null,"abstract":"Autonomous systems and mission-critical applications demand ultra-reliable low-latency communication (URLLC). To build wireless communication networks capable of accommodating such applications, optimization of the airinterface characteristics is vital. This paper leverages recent advancements in the field of Artificial Intelligence (AI) technologies to optimize specific aspects of the air interface design to satisfy these stringent link reliability and latency requirements. The precise aim of this research is to reduce the link latency caused by the presence of the Hybrid Automatic Repeat reQuest (HARQ) mechanism. To this end, we propose a novel deep learning-based algorithm (Deep-HARQ), employing a deep neural network (DNN) with fully connected layers to estimate the decodability of the coded-received in-phase and quadrature (I/Q) signals prior to accomplishing the majority of the complex reception tasks. This enables the receiver to respond faster, allowing for the reduction of the signal round-trip time (RTT). To evaluate Deep-HARQ with a realistic dataset, we collected training and validation samples from a waveform compatible with 3GPP 5G NR Release 15 standards. The simulation results reveal a faster estimation response, with an accuracy enhancement of 12% compared to relevant algorithms in the literature.","PeriodicalId":283606,"journal":{"name":"2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121567621","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: 6

Machine Learning Enables Predictive Resource Recommendation for Minimal Latency Mobile Networking 机器学习为最小延迟移动网络提供预测性资源推荐

2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) Pub Date : 2021-09-13 DOI: 10.1109/pimrc50174.2021.9569506

Yingze Wang, Qimei Cui, Kwang-Cheng Chen

{"title":"Machine Learning Enables Predictive Resource Recommendation for Minimal Latency Mobile Networking","authors":"Yingze Wang, Qimei Cui, Kwang-Cheng Chen","doi":"10.1109/pimrc50174.2021.9569506","DOIUrl":"https://doi.org/10.1109/pimrc50174.2021.9569506","url":null,"abstract":"To achieve the minimal latency, proactive wireless communication has been proposed to facilitate proactive mobile networks. Due to lacking closed-loop control, random selection of radio resource units (RRUs) serves the only way to the critical radio resource allocation (RRA), which inevitably suffers collisions of simultaneous utilizing the same RRUs to result in loss of packets, particularly in the uplink. Macroscopic view on the uplink and downlink network operation cycle insightfully suggests that it is still possible to construct a delayed version of semi-closed-loop operation to predictively utilize radio resource in the uplink of proactive mobile network. A two-stage reinforcement learning mechanism to enable the recommendation of radio resource utilization from network infrastructure to mobile smart machines is proposed, which consists of the multi-armed bandit scheme for RRA and the neural network to learn historical utilization of RRUs. Simulations verify machine learning enables smart and predictive RRA with superior performance that can lead to the minimal latency of mobile networking.","PeriodicalId":283606,"journal":{"name":"2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124354090","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: 7

Data Traffic Offloading and Rate Control for Vehicles Using Radio Environment, Network Load and Route Planning 基于无线电环境、网络负荷和路径规划的车辆数据流量分流与速率控制

2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) Pub Date : 2021-09-13 DOI: 10.1109/PIMRC50174.2021.9569428

T. Ohseki, K. Yamazaki, Daiki Maemoto, Shigeki Kawai, Tsuneo Nakata, Akira Itou

{"title":"Data Traffic Offloading and Rate Control for Vehicles Using Radio Environment, Network Load and Route Planning","authors":"T. Ohseki, K. Yamazaki, Daiki Maemoto, Shigeki Kawai, Tsuneo Nakata, Akira Itou","doi":"10.1109/PIMRC50174.2021.9569428","DOIUrl":"https://doi.org/10.1109/PIMRC50174.2021.9569428","url":null,"abstract":"In recent years, it has become common for vehicles to connect to networks via radio access networks to exchange various data. In the future, the number of service providers that provide information to and collect information from vehicles will increase, and the traffic from these service providers may occupy a large portion of the radio resources consumed in the radio access network. Therefore, it is desirable to improve the frequency utilization efficiency of the traffic related to these service providers. In this paper, we provide a quantitative demonstration of the concept of traffic control using the load information on radio access networks that the mobile network operator can collect from its own network, the information on radio environment that the service provider collects, and the route planning of the vehicle to its destination. Specifically, based on the above information, traffic control will be performed within the range where the vehicle can move within the allowable delay time, such as downloading data at points with low load and good radio environment in the downlink, and controlling the streaming rate according to the load and radio environment in the uplink. Computer simulations show that for downlink, both the frequency utilization efficiency and UE throughput during download can be improved, and for uplink, the frequency utilization efficiency can be improved while improving the amount of successfully transmitted data.","PeriodicalId":283606,"journal":{"name":"2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127974055","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

Efficient Non-Line-of-Sight Identification in Localization Using a Bank of Neural Networks 基于神经网络库的高效非视线定位识别

2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) Pub Date : 2021-09-13 DOI: 10.1109/PIMRC50174.2021.9569433

Abbas Abolfathimomtaz, Mostafa Mohammadkarimi, M. Ardakani

引用次数: 0

Adaptive Modulation for Wireless Federated Learning 无线联邦学习的自适应调制

2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) Pub Date : 2021-09-13 DOI: 10.1109/PIMRC50174.2021.9569588

Xinyi Xu, Guanding Yu, Shengli Liu

引用次数: 2