2020 IEEE Wireless Communications and Networking Conference (WCNC)最新文献_第8页

Joint User-Centric Clustering and Frequency Allocation in Ultra-Dense C-RAN 超密集C-RAN中以用户为中心的联合聚类与频率分配

2020 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2020-05-01 DOI: 10.1109/WCNC45663.2020.9120743

Qiang Liu, Songlin Sun, Hui Gao

{"title":"Joint User-Centric Clustering and Frequency Allocation in Ultra-Dense C-RAN","authors":"Qiang Liu, Songlin Sun, Hui Gao","doi":"10.1109/WCNC45663.2020.9120743","DOIUrl":"https://doi.org/10.1109/WCNC45663.2020.9120743","url":null,"abstract":"This paper considers the downlink ultra-dense cloud radio access network (C-RAN), which employs multiple radio remote head (RRH) cooperation to guarantee the minimum achievable transmission rate for each user equipment (UE). However, due to the limited orthogonal frequency resources, it is difficult to achieve this goal. To maximize the coverage probability of the system, we focus on the joint user-centric clustering and frequency allocation problem. To reduce the computational complexity, this problem is split into two sub-problems: user-centric clustering and frequency allocation. Firstly, we propose a novel binary user-centric clustering strategy, which includes serving clusters and silent clusters. This strategy determines the acceptable combination of serving clusters and silent clusters to guarantee the minimum transmission rate for each UE and simplify the complexity of the subsequent frequency allocation. Then based on the generated clusters, a new graph generation method is proposed. The advantage of this graph is that we can allocate frequency resources by simply judging the relationship between the serving clusters in the graph without complicated calculations. Numerical simulation results show that the joint binary user-centric clustering and location-based frequency allocation scheme is superior to the benchmark solutions in terms of the coverage probability.","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"27 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":"132287531","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

Caching and Pricing based on Blockchain in a Cache-delivery Market 缓存交付市场中基于区块链的缓存和定价

2020 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2020-05-01 DOI: 10.1109/WCNC45663.2020.9120478

Yuanzhuo Lin, Hui Tian, Jiazhi Ren, Shaoshuai Fan

引用次数: 3

Capacity Analysis of Time-Indexed Media-based Modulation 基于时间索引的媒体调制的容量分析

2020 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2020-05-01 DOI: 10.1109/WCNC45663.2020.9120838

Bharath Shamasundar, L. N. Theagarajan, A. Chockalingam

引用次数: 2

A Differentially Private Classification Algorithm With High Utility for Wireless Body Area Networks 一种实用的无线体域网络差分私有分类算法

2020 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2020-05-01 DOI: 10.1109/WCNC45663.2020.9120495

Xianwen Sun, Lingyun Shi, Longfei Wu, Zhitao Guan, Xiaojiang Du, M. Guizani

{"title":"A Differentially Private Classification Algorithm With High Utility for Wireless Body Area Networks","authors":"Xianwen Sun, Lingyun Shi, Longfei Wu, Zhitao Guan, Xiaojiang Du, M. Guizani","doi":"10.1109/WCNC45663.2020.9120495","DOIUrl":"https://doi.org/10.1109/WCNC45663.2020.9120495","url":null,"abstract":"The advancement of the wireless body area networks (WBAN) and sensor technologies allows us to collect a variety of physiological and behavioral data from human body. And appropriate application of machine learning methods can greatly promote the development of e-health. Nevertheless, the collected data contains personal privacy information. When using the machine learning methods to analyze the collected data, some information of the training data will be stored in the learning models unconsciously. To handle such information disclosure problem, we propose a differentially private classification algorithm based on ensemble decision tree with high utility for wireless body area networks. In order to improve the accuracy and stableness of classification, the bagging framework of ensemble learning is used in our algorithm. We aggregate the results of multiple private decision trees as the final classification in a weight-based voting way. For each private decision tree trained on the bootstrap samples, we offer a novel privacy budget allocation strategy that allows the nodes in larger depth to get more privacy budget, which can mitigate the problem of excessive noise introduced to leaf nodes to some extent. The better classification accuracy and stableness of this new algorithm, especially on small dataset, are demonstrated by simulation experiments.","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"598 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":"134435118","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

On Optimizing Signaling Efficiency of Retransmissions for Voice LTE 语音LTE重传信令效率优化研究

2020 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2020-05-01 DOI: 10.1109/WCNC45663.2020.9120735

Chia-An Hsu, K. Lin, Yi Ren, Y. Tseng

{"title":"On Optimizing Signaling Efficiency of Retransmissions for Voice LTE","authors":"Chia-An Hsu, K. Lin, Yi Ren, Y. Tseng","doi":"10.1109/WCNC45663.2020.9120735","DOIUrl":"https://doi.org/10.1109/WCNC45663.2020.9120735","url":null,"abstract":"The emergence of voice over LTE enables voice traffic transmissions over 4G packet-switched networks. Since voice traffic is characterized by its small payload and frequent transmissions, the corresponding control channel overhead would be high. Semi-persistent scheduling (SPS) is hence proposed in LTE-A to reduce such overhead. However, as wireless channels typically fluctuate, tremendous retransmissions due to poor channel conditions, which are still scheduled dynamically, would lead to a large overhead. To reduce the control message overhead caused by SPS retransmissions, we propose a new SPS retransmission protocol. Different from traditional SPS, which removes the downlink control indicators (DCI) directly, we compress some key fields of all retransmissions’ DCIs in the same subframe as a fixed-length hint. Thus, the base station does not need to send this information to different users individually but just announces the hint as a broadcast message. In this way, we reduce the signaling overhead and at the same time, preserve the flexibility of dynamic scheduling. Our simulation results show that, by enabling DCI compression, our design improves signaling efficiency by $2.16times$, and the spectral utilization can be increased by up to 60%.","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"24 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":"133725451","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

Deep Adaptation Networks Based Gesture Recognition using Commodity WiFi 基于深度适应网络的商用WiFi手势识别

2020 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2020-05-01 DOI: 10.1109/WCNC45663.2020.9120726

Zijun Han, Lingchao Guo, Zhaoming Lu, X. Wen, Wei Zheng

{"title":"Deep Adaptation Networks Based Gesture Recognition using Commodity WiFi","authors":"Zijun Han, Lingchao Guo, Zhaoming Lu, X. Wen, Wei Zheng","doi":"10.1109/WCNC45663.2020.9120726","DOIUrl":"https://doi.org/10.1109/WCNC45663.2020.9120726","url":null,"abstract":"Device-free gesture recognition plays a crucial role in smart home applications, setting human free from wearable devices and causing no privacy concerns. Prior WiFi-based recognition systems have achieved high accuracy in a static environment, but with limitations in adapting changes in environments and locations. In this paper, we propose a fine-grained deep adaptation networks based gesture recognition scheme (DANGR) using the Channel State Information (CSI). DANGR applies wavelet transformation for amplitude denoising, and conjugate calibration to remove CSI time-variant random phase offsets. A Generative Adversarial Networks (GAN) based data augmentation approach is proposed to reduce the large consumptions of data collection and the over-fitting risks caused by incomplete dataset. The distribution of CSI in various environments may be biased. In order to shrink these domains discrepancies in environments, we adopt domain adaptation based on multikernel Maximum Mean Discrepancy scheme, which matches the mean-embeddings of abstract representations across domains in a reproducing kernel Hilbert space. Extensive empirical evidence shows that DANGR yields mean 94.5% accuracy of gesture recognition confronting environmental variations, providing a promising scheme for practical and long-run implementation.","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"35 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":"132932373","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: 13

User Slicing Scheme with Functional Split Selection in 5G Cloud-RAN 5G Cloud-RAN中具有功能拆分选择的用户切片方案

2020 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2020-05-01 DOI: 10.1109/WCNC45663.2020.9120828

Salma Matoussi, Ilhem Fajjari, N. Aitsaadi, R. Langar

{"title":"User Slicing Scheme with Functional Split Selection in 5G Cloud-RAN","authors":"Salma Matoussi, Ilhem Fajjari, N. Aitsaadi, R. Langar","doi":"10.1109/WCNC45663.2020.9120828","DOIUrl":"https://doi.org/10.1109/WCNC45663.2020.9120828","url":null,"abstract":"Next Generation 5G Radio Access Network (NGRAN) is envisioned to integrate the slicing approach to build a flexible network supporting diverse use-cases with customized architectures, features and services. RAN processing functional splits have been standardized to add new deployment design capabilities and enhance cost efficiency. A further challenge consists in how to meet the multitude use-case’s requirements while considering different design models in the physical infrastructure. Current related works are tackling the slice embedding problem from a cell-centric perspective. However, to achieve greater flexibility and better resource utilization, a user-centric approach should be more exploited. In this paper, we propose a SLICE-HPSO scheme that jointly harnesses radio, processing and link resources at the user level to build multiple user slices on top of the physical infrastructure. Our proposal is tailored to different user quality-of-service requirements and to the diverse functional splits resource requests. SLICE-HPSO is in compliance with the 3GPP and optimizes further the heterogeneous resource usage while meeting the scalability requirement.","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"35 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114100128","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

Characterization for High-Speed Railway Channel enabling Smart Rail Mobility at 22.6 GHz 实现22.6 GHz智能铁路机动性的高速铁路信道特性

2020 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2020-05-01 DOI: 10.1109/WCNC45663.2020.9120474

Lei Ma, K. Guan, Dong Yan, Danping He, B. Ai, Junhyeong Kim, Heesang Chung

引用次数: 4

A Secure Session Key Negotiation Scheme in WPA2-PSK Networks WPA2-PSK网络中的安全会话密钥协商方案

2020 IEEE Wireless Communications and Networking Conference (WCNC) Pub Date : 2020-05-01 DOI: 10.1109/WCNC45663.2020.9120510

J. Guo, Miao Wang, Hanwen Zhang, Yujun Zhang

{"title":"A Secure Session Key Negotiation Scheme in WPA2-PSK Networks","authors":"J. Guo, Miao Wang, Hanwen Zhang, Yujun Zhang","doi":"10.1109/WCNC45663.2020.9120510","DOIUrl":"https://doi.org/10.1109/WCNC45663.2020.9120510","url":null,"abstract":"Wi-Fi Protected Access II Pre-Shared Key (WPA2-PSK) is a hot way to wireless security in public Wi-Fi networks. It works on a pre-configured passphrase shared with all stations in the same Wi-Fi network. Session keys (e.g., Pairwise Transient Key, PTK) between stations and the access point (AP) are derived from the passphrase. The WPA2-PSK networks can authenticate external stations, however, they fail to guarantee confidential communication if internal attackers own the passphrase in the network since all stations derive their PTK using the same passphrase. To prevent internal stations from eavesdropping the PTK, a secure session key negotiation scheme in WPA2-PSK Networks (SSKNS) is proposed. We introduce a temporary session key (TSK), which is encrypted using elliptic curve cryptography (ECC) and exchanged securely between the station and the AP in the Wi-Fi association process. Through AES algorithm with TSK, the station encrypts its own nonce used to generate the unique PTK in the 4-way process. Our scheme neither modifies the legacy process related to PTK generation nor adds plethoric overhead on excessive protection of all messages. Security analysis and simulations performed in NS-3 demonstrate that by consuming a few computation overheads, SSKNS can effectively provide security level, compared with the existing schemes.","PeriodicalId":415064,"journal":{"name":"2020 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"6 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":"116785790","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