2020 IEEE Wireless Communications and Networking Conference (WCNC)最新文献_第9页

C2 RC: Channel Congestion-based Re-transmission Control for 3GPP-based V2X Technologies 基于3gpp的V2X技术的信道拥塞重传控制

2020 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2020-05-01 DOI: 10.1109/WCNC45663.2020.9120851

Gaurang Naik, J. Park, J. Ashdown

{"title":"C2 RC: Channel Congestion-based Re-transmission Control for 3GPP-based V2X Technologies","authors":"Gaurang Naik, J. Park, J. Ashdown","doi":"10.1109/WCNC45663.2020.9120851","DOIUrl":"https://doi.org/10.1109/WCNC45663.2020.9120851","url":null,"abstract":"The 3rd Generation Partnership Project (3GPP) is actively designing New Radio Vehicle-to-Everything (NR V2X)—a 5G NR-based technology for V2X communications. NR V2X, along with its predecessor Cellular V2X (C-V2X), is set to enable low-latency and high-reliability communications in high-speed and dense vehicular environments. A key reliability-enhancing mechanism that is available in C-V2X and is likely to be re-used in NR V2X is packet re-transmissions. In this paper, using a systematic and extensive simulation study, we investigate the impact of this feature on the system performance of C-V2X. We show that statically configuring vehicles to always disable or enable packet re-transmissions either fails to extract the full potential of this feature or leads to performance degradation due to increased channel congestion. Motivated by this, we propose and evaluate Channel Congestion-based Re-transmission Control (C2 RC), which, based on the observed channel congestion, allows vehicles to autonomously decide whether or not to use packet re-transmissions without any role of the cellular infrastructure. Using our proposed mechanism, C-V2X-capable vehicles can boost their performance in lightly-loaded environments, while not compromising on performance in denser conditions.","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130571339","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

A Simple Novel Idle Slot Prediction and Avoidance Scheme Using Prediction Bits for DFSA in RFID 基于预测位的RFID空槽预测与避免方案

2020 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2020-05-01 DOI: 10.1109/WCNC45663.2020.9120457

Gan Luan, N. Beaulieu

引用次数: 1

Fine-grained Analysis and Optimization of Flexible Spatial Difference in User-centric Network 用户中心网络柔性空间差异的细粒度分析与优化

2020 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2020-05-01 DOI: 10.1109/WCNC45663.2020.9120499

Danyang Wu, Hongtao Zhang

{"title":"Fine-grained Analysis and Optimization of Flexible Spatial Difference in User-centric Network","authors":"Danyang Wu, Hongtao Zhang","doi":"10.1109/WCNC45663.2020.9120499","DOIUrl":"https://doi.org/10.1109/WCNC45663.2020.9120499","url":null,"abstract":"In user-centric network, traditional typical user analysis method based on spatial average results is no longer applicable due to the flexible spatial difference, which is the large fluctuations in user performance with spatial location. Especially because of power control leading to keen spatial competition, the spatial difference becomes much significantly, so that fine-grained analysis method is needed to evaluate its performance. This paper analyzes the spatial difference in user-centric network with power control through meta distribution from many different fine-grained perspectives to reveal that power control improves the performance not only in the sense of the spatial average, but also in the complete spatial distribution. Specifically, the complementary cumulative distribution function (CCDF) of the conditional transmitting success probability, the mean local delay and the 5%-tile users performance are given to depict power control effect on the individual links. This analysis provides the optimal values of the area and intensity for power control deployment in user-centric network. Numerical results show that after applying power control the users of high coverage probability can be improved at most by 38%, the mean local delay decreases by 2x and 4x gains can be obtained as for the 5%-tile user’s performance.","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129910408","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

A Low-Complexity Algorithm for Cell Identity Detection in NB-IoT Physical Layer 一种低复杂度的NB-IoT物理层小区身份检测算法

2020 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2020-05-01 DOI: 10.1109/WCNC45663.2020.9120525

Hung-Ying Chang, Jian-Bin Chang, Chao-Yu Chen

引用次数: 1

End-to-end Throughput Optimization in Multi-hop Wireless Networks with Cut-through Capability 具有直通能力的多跳无线网络的端到端吞吐量优化

2020 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2020-05-01 DOI: 10.1109/WCNC45663.2020.9120679

Shengbo Liu, Liqun Fu

{"title":"End-to-end Throughput Optimization in Multi-hop Wireless Networks with Cut-through Capability","authors":"Shengbo Liu, Liqun Fu","doi":"10.1109/WCNC45663.2020.9120679","DOIUrl":"https://doi.org/10.1109/WCNC45663.2020.9120679","url":null,"abstract":"In-band full-duplex (FD) technique can efficiently improve the end-to-end throughput of a multi-hop network via enabling multi-hop FD amplify-and-forward relaying (cut-through) transmission. This paper investigates the optimal hop size of a cut-through transmission and spatial reuse to achieve the maximum achievable end-to-end throughput of a multi-hop network. In particular, we consider spatial reuse and establish an interference model for a string-topology multi-hop network with x-hop cut-through transmission, and show that the maximum achievable end-to-end throughput is a function of x and the spatial separation between two concurrently active cut-through transmissions. Through extensive numerical studies, we show that the achievable date rate of a cut-through transmission drastically decreases along with the increase of the hop size x. Furthermore, we find that the 2-hop cut-through transmission mode can always achieve the maximum end-to-end throughput using Shannon Capacity formula if the spatial reuse is properly addressed. On the other hand, the results show that the 5-hop cut-through transmission mode can obtain the maximum end-to-end throughput with discrete channel rates when the self-interference cancellation is perfect and the hop distance is small.","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127632235","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

Clustering-Based Scenario-Aware LTE Grant Prediction 基于聚类的场景感知LTE授权预测

2020 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2020-05-01 DOI: 10.1109/WCNC45663.2020.9120789

Peter Brand, Muhammad Sabih, J. Falk, Jonathan Ah Sue, Jürgen Teich

{"title":"Clustering-Based Scenario-Aware LTE Grant Prediction","authors":"Peter Brand, Muhammad Sabih, J. Falk, Jonathan Ah Sue, Jürgen Teich","doi":"10.1109/WCNC45663.2020.9120789","DOIUrl":"https://doi.org/10.1109/WCNC45663.2020.9120789","url":null,"abstract":"Reducing the energy consumption of mobile phones is a crucial design goal for cellular modem solutions for LTE and 5G standards. Recent approaches for dynamic power management incorporate traffic prediction to power down components of the modem as often as possible. These predictive approaches have been shown to still provide substantial energy savings, even if trained purely on-line. However, a higher prediction accuracy could be achieved when performing predictor training off-line. Additionally, having pre-trained predictors opens up the ability to successfully employ predictive techniques also in less favorable situations such as short intervals of stable traffic patterns. For this purpose, we introduce a notion of similarity, based on which a clustering is performed to identify similar traffic patterns. For each resulting cluster, i.e., an identified traffic scenario, one predictor is designed and trained off-line. At run time, the system selects the pre-trained predictor with the lowest average short-term false negative rate allowing for energy-efficient and highly accurate on-line prediction. Through experiments, it is shown that the presented mixed static/dynamic approach is able to improve the prediction accuracy and energy savings compared to a state-of-the-art approach by factors of up to 2 and up to 1.9, respectively.","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121970073","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

Multi-BS association and Pilot Allocation via Pursuit Learning 基于追求学习的多bs关联与试点分配

2020 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2020-05-01 DOI: 10.1109/WCNC45663.2020.9120561

Naufan Raharya, Wibowo Hardjawana, Obada Al-Khatib, B. Vucetic

{"title":"Multi-BS association and Pilot Allocation via Pursuit Learning","authors":"Naufan Raharya, Wibowo Hardjawana, Obada Al-Khatib, B. Vucetic","doi":"10.1109/WCNC45663.2020.9120561","DOIUrl":"https://doi.org/10.1109/WCNC45663.2020.9120561","url":null,"abstract":"Pilot contamination (PC) interference causes an inaccurate user equipment’s (UE) channel estimations and significant signal-to-interference ratio (SINR) degradations. To combat the PC effect and to maximize network spectral efficiency, pilot allocation can be combined with multi-Base Station (BS) association and then solved by using learning algorithm efficiently. However, current methods separate the pilot allocation and multi-BS association in the network. This results in suboptimal network spectral efficiency performance and can cause an outage where some UEs are not allocated pilots due to the limited availability of pilots at each BS. In this paper, we propose a multi-BS association and pilot allocation optimization via pursuit learning. Here, we design a parallel pursuit learning algorithm that decomposes the optimization function into smaller entities called learning automata. Each learning automaton computes the joint pilot allocation and BS association solution in parallel, by using the reward from the environment. Simulation results show that our scheme outperforms the existing schemes and does not cause an outage.","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122421892","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

Trajectory Design and Generalization for UAV Enabled Networks:A Deep Reinforcement Learning Approach 基于深度强化学习的无人机网络轨迹设计与泛化

2020 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2020-05-01 DOI: 10.1109/WCNC45663.2020.9120668

Xuan Li, Qiang Wang, Jie Liu, Wenqi Zhang

{"title":"Trajectory Design and Generalization for UAV Enabled Networks:A Deep Reinforcement Learning Approach","authors":"Xuan Li, Qiang Wang, Jie Liu, Wenqi Zhang","doi":"10.1109/WCNC45663.2020.9120668","DOIUrl":"https://doi.org/10.1109/WCNC45663.2020.9120668","url":null,"abstract":"In this paper, an unmanned aerial vehicle (UAV) flies as a base station (BS) to provide wireless communication service. We propose two algorithms for designing the trajectory of the UAV and analyze the impact of different training approaches on transferring to new environments. When the UAV is used to track users that move along some specific paths, we propose a proximal policy optimization (PPO) -based algorithm to maximize the instantaneous sum rate (MSR-PPO). The UAV is modeled as a deep reinforcement learning (DRL) agent to learn how to move by interacting with the environment. When the UAV serves users along unknown paths for emergencies, we propose a random training proximal policy optimization (RT-PPO) algorithm which can transfer the pre-trained model to new tasks to achieve quick deployment. Unlike classical DRL algorithms that the agent is trained on the same task to learn its actions, RT-PPO randomizes the features of tasks to get the ability to transfer to new tasks. Numerical results reveal that MSR-PPO achieves a remarkable improvement and RT-PPO shows an effective generalization performance.","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121148282","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

Throughput Performance Study of Smart Antenna System in WiFi Networks WiFi网络中智能天线系统的吞吐量性能研究

2020 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2020-05-01 DOI: 10.1109/WCNC45663.2020.9120674

Hsin-Li Chiu, Sau-Hsuan Wu, Hsi-Lu Chao

引用次数: 1

MalPortrait: Sketch Malicious Domain Portraits Based on Passive DNS Data MalPortrait:基于被动DNS数据绘制恶意域画像

2020 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2020-05-01 DOI: 10.1109/WCNC45663.2020.9120488

Zhizhou Liang, Tianning Zang, Yuwei Zeng

{"title":"MalPortrait: Sketch Malicious Domain Portraits Based on Passive DNS Data","authors":"Zhizhou Liang, Tianning Zang, Yuwei Zeng","doi":"10.1109/WCNC45663.2020.9120488","DOIUrl":"https://doi.org/10.1109/WCNC45663.2020.9120488","url":null,"abstract":"Malicious domain detection is of great significance for cybersecurity. Most prior works detect malicious domains based on individual features, which are only related to the attributes of domains themselves and can be easily changed to avoid detection. To solve the problem, we propose a novel system called MalPortrait, which combines individual features and association information of domains to detect malicious domains. In MalPortrait, we show the association information among domains by a domain association graph where vertices represent domains and edges connect domains resolved to the same IP. Based on the graph, we combine individual features (e.g., string-based, network-based) of each domain and its association information to generate new features. Compared with individual features, the new features are harder to be tampered with and can help determine whether a domain is malicious from a more comprehensive perspective. We evaluate MalPortrait on the passive DNS traffic collected from real-world large ISP networks. Our experimental results show that MalPortrait can accurately identify malicious domain names with a precision of 96.8% and a recall of 95.5%. Compared with prior works, MalPortrait performs better and hardly relies on additional knowledge (e.g., IP reputation, Domain whois).","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124133227","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