2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)最新文献_第4页

Primary User Activity Prediction in DSA Networks using Recurrent Structures 基于循环结构的DSA网络主用户活动预测

2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) Pub Date : 2019-11-01 DOI: 10.1109/DySPAN.2019.8935716

Debashri Roy, Tathagata Mukherjee, M. Chatterjee, E. Pasiliao

{"title":"Primary User Activity Prediction in DSA Networks using Recurrent Structures","authors":"Debashri Roy, Tathagata Mukherjee, M. Chatterjee, E. Pasiliao","doi":"10.1109/DySPAN.2019.8935716","DOIUrl":"https://doi.org/10.1109/DySPAN.2019.8935716","url":null,"abstract":"For unlicensed (secondary) users to opportunistically access the shared radio spectrum on a non-interfering basis, it is important that they are able to sense the transmission activities of the licensed (primary) users. However, spectrum sensing expend a considerable amount of energy and time, which can be reduced by reliably predicting the primary user activities. In this paper, we present recurrent neural network models which are able to accurately predict the primary users’ activity in dynamic spectrum access (DSA) networks so that the secondary users can opportunistically access the unused spectrum. Using Universal Software Radio Peripheral (USRP) Software Defined Radios (SDRs), we collect over-the-air data from 8 primary users and train the learning models that we use in conjunction with a central spectrum sensor. We start by implementing two machine learning models: (i) traditional linear regression and (ii) neural network model using Long Short Term Memory (LSTM). These models are able to predict the primary users’ activity with 75% and 97% accuracy respectively. To further improve the prediction accuracy, we exploit the spatio-temporal correlation in the collected data by implementing a Convolutional LSTM model-which achieves 99% accuracy for predicting the long-term activity of primary users. The experimental results demonstrate that the proposed models are able to successfully predict the primary users’ activities, thereby reducing both the under-utilizations and interference violations in DSA networks.","PeriodicalId":278172,"journal":{"name":"2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115926335","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

Quantitative Assessment of TV White Space in the Western Philippine Nautical Highway 菲律宾西部航海公路电视留白的定量评估

2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) Pub Date : 2019-11-01 DOI: 10.1109/DySPAN.2019.8935798

Rizza T. Loquias, C. G. Hilario, Mar Francis D. De Guzman, J. Marciano

{"title":"Quantitative Assessment of TV White Space in the Western Philippine Nautical Highway","authors":"Rizza T. Loquias, C. G. Hilario, Mar Francis D. De Guzman, J. Marciano","doi":"10.1109/DySPAN.2019.8935798","DOIUrl":"https://doi.org/10.1109/DySPAN.2019.8935798","url":null,"abstract":"In this paper, we present the quantitative results of a spectrum measurement campaign for the UHF TV band (470 -698 MHz) in the western segment of the Philippine Nautical Highway System (PNHS). The PNHS, also known as the Road Roll-On/Roll-Off Terminal System (RRTS) or Ro-Ro System, is an integrated linkage of inland highways and ferry routes forming a nationwide vehicle transport system in the Philippines that served approximately 77 million passengers in 2018. We used a portable spectrum measurement equipment to gather data in fixed inland, mobile inland, and mobile maritime environments of the Western Philippine Nautical Highway (W-PNH). To characterize and quantify white space, we adopted calculated thresholding using the 80% method (ITU-R SM.1753). We compare the results obtained from the field measurements to that of using the geo-location database approach (FCC method). A discussion on the implication of the available TV spectrum to maritime vehicular communication and pertinent supporting policy formulation in the Philippine settings is also provided.","PeriodicalId":278172,"journal":{"name":"2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115663718","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

Preserving Incumbent User’s Location Privacy Against Environmental Sensing Capability 基于环境感知能力的在位用户位置隐私保护

2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) Pub Date : 2019-11-01 DOI: 10.1109/DySPAN.2019.8935713

Yousi Lin, Yuxian Ye, Yaling Yang

引用次数: 5

Cache-Enabled Dynamic Spectrum Access via Deep Recurrent Q-Networks with Partial Observation 基于部分观测的深度递归q网络的缓存动态频谱访问

2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) Pub Date : 2019-11-01 DOI: 10.1109/DySPAN.2019.8935688

Yue Xu, Jianyuan Yu, R. Buehrer

引用次数: 2

Cellular Signal Identification Using Convolutional Neural Networks: AWGN and Rayleigh Fading Channels 使用卷积神经网络的蜂窝信号识别：AWGN 和瑞利衰落信道

2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) Pub Date : 2019-11-01 DOI: 10.1109/DySPAN.2019.8935857

Hongtao Xia, Khalid Alshathri, V. Lawrence, Yu-dong Yao, Armando Montalvo, M. Rauchwerk, R. Cupo

引用次数: 23

Spectrum Management over Dynamic Spectrum Access based HetNets 基于动态频谱接入的HetNets频谱管理

2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) Pub Date : 2019-11-01 DOI: 10.1109/DySPAN.2019.8935768

S. Anand, Vijay Kumar, R. Chandramouli

引用次数: 1

Exploring Spatial-Temporal Patterns From Individual User Cellular Traffic 从单个用户蜂窝通信中探索时空模式

2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) Pub Date : 2019-11-01 DOI: 10.1109/DySPAN.2019.8935840

Lixing Yu, Wenqiang Jin, Ming Li, P. Li

引用次数: 0

Demo: Highly Accurate Prediction of Radio Environment for V2V Communications 演示:V2V通信中无线电环境的高精度预测

2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) Pub Date : 2019-11-01 DOI: 10.1109/DySPAN.2019.8935699

Keita Katagiri, T. Fujii

引用次数: 5

Dynamic Spectrum Access Network Scaling with Multiple Users: A Market-based Analysis 多用户动态频谱接入网扩展:基于市场的分析

2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) Pub Date : 2019-11-01 DOI: 10.1109/DySPAN.2019.8935788

Mohammad Daniyal Zulfiqar, Sumit Roy, Shreemoy Mishra

引用次数: 1

Asynchronous Blind Modulation Classification in the Presence of Non-Gaussian Noise 非高斯噪声存在下的异步盲调制分类

2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN) Pub Date : 2019-11-01 DOI: 10.1109/DySPAN.2019.8935687

Jitong Ma, Chen Peng, Shih-Chun Lin, T. Qiu

{"title":"Asynchronous Blind Modulation Classification in the Presence of Non-Gaussian Noise","authors":"Jitong Ma, Chen Peng, Shih-Chun Lin, T. Qiu","doi":"10.1109/DySPAN.2019.8935687","DOIUrl":"https://doi.org/10.1109/DySPAN.2019.8935687","url":null,"abstract":"Blind modulation classification is an essential and fundamental step before signal detection in intelligent communication systems. However, in complicated electromagnetic environment, identifying asynchronous modulated signals remains a challenging task. In order to improve the performance of asynchronous modulation classification in non-Gaussian noise, this paper proposes a novel BMC method based on complex correntropy and Conv1D (one-dimensional convolution neural network), namely CC-Conv1D. First, complex correntropy is employed to extract discriminating features from asynchronous modulated signals, while non-Gaussian noise can be effectively suppressed by complex correntropy. Furthermore, theoretical analysis is conducted to demonstrate the effectiveness of complex correntropy in feature extraction and non-Gaussian noise suppression. Moreover, Conv1D is adopted to identify different modulation schemes due to its merits of recognizing the shape of extracted features with low computational complexity. Experimental implementation is conducted via USRP N210 and USRP 2901, and the results show that our solution can achieve at least 97.5% accuracy in practical wireless communications.","PeriodicalId":278172,"journal":{"name":"2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125700622","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: 2