Carlos Bocanegra, Kubra Alemdar, S. García, Chetna Singhal, K. Chowdhury
{"title":"NetBeam: Networked and Distributed 3-D Beamforming for Multi-user Heterogeneous Traffic","authors":"Carlos Bocanegra, Kubra Alemdar, S. García, Chetna Singhal, K. Chowdhury","doi":"10.1109/DySPAN.2019.8935797","DOIUrl":"https://doi.org/10.1109/DySPAN.2019.8935797","url":null,"abstract":"The paper presents theoretical development and a system implementation of NetBeam, a framework for fully programmable, reconfigurable and distributed beamforming. NetBeam allows for joint mechanical antenna steering, grouping of a network of individual transmitter radios for specific target receivers, as well as digital beamforming that satisfies higher layer application demands. We make the following theoretical contributions: (i) We utilize, for the first time, a machine learning approach that uses Kriging for predicting antenna gains for arbitrary 3-D placements of transmitter - receiver pairs. NetBeam efficiently exploits fine-grained and accurate antenna gain predictions of the model, while estimating the uncertainty at unexplored locations through a Gaussian distribution. (ii) We allocate antennas to receivers by formulating the scenario as a bipartite graph, followed by perfect matching strategies that maximize the channel gain. (iii) We leverage the CSI computed in stage (i) to compute the optimum digital beamforming weights by trading off SINR and power consumption that meets application requirements using semidefinite optimization. Our implementation addresses many practical aspects of distributed beamforming including achieving fast frequency, time, and phase synchronization. NetBeam minimizes the gap to optimal channel gain in a 3-D space, and reduces the total transmit power up to 60%, while still managing to provide the required SINR.","PeriodicalId":278172,"journal":{"name":"2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":"14 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":"121213513","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}
{"title":"The Economics of Multi-Network Access","authors":"Nandi Zhang, M. Sirbu, J. Peha","doi":"10.1109/DySPAN.2019.8935674","DOIUrl":"https://doi.org/10.1109/DySPAN.2019.8935674","url":null,"abstract":"Traditionally, a cell phone remains on a single, primary mobile network operator (MNO) as long as it is available, and roams onto another MNO only when outside the primary MNO's coverage. Multi-network access (MNA) is a new scheme where a cell phone may use any one of multiple MNOs at any place, anytime. One such example is a multi-operator mobile virtual network operator (MO-MVNO) like Google Fi. This paper quantifies how much MNA can reduce the cost of cellular data services, and shows that the amount of infrastructure and/or spectrum resources needed to produce a given network capacity can be reduced by over 20%. Greater resource savings can be realized if MNA-capable devices attach to towers of higher SINR rather than higher expected data rate. The amount of resources saved increases faster than linearly with increasing fraction of MNA-capable devices on the network, so as an MO-MVNO gains market share, it could demand better wholesale prices from partner MNOs. If the distribution of traffic volume between partner MNOs shifts significantly with MNA, an MNO losing traffic share may not have an incentive to participate in MNA unless it could demand a much higher wholesale price than other partner MNOs, possibly close to or even above the retail price net of market cost. The eventual economic impacts on each operator adopting MNA are the result of complex considerations involving not only business decisions like investment and wholesale pricing, but also technical parameters like network selection algorithms and resource allocation schemes.","PeriodicalId":278172,"journal":{"name":"2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":"96 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":"124080465","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}
{"title":"Radio Environment Map Updating Procedure Based on Hypothesis Testing","authors":"Keita Katagiri, T. Fujii","doi":"10.1109/DySPAN.2019.8935724","DOIUrl":"https://doi.org/10.1109/DySPAN.2019.8935724","url":null,"abstract":"In this paper, we propose an updating method of a radio environment map (REM) using Welch’s t -test. The REM provides statistical radio information about primary users (PUs) to secondary users (SUs). By using REM, SUs can predict path loss and shadowing deviation in each location. However, the estimation accuracy of the radio environment is degraded if the surrounding environment changes since the initial REM is constructed. The database server should update the REM by detecting the change of the radio environment. Therefore, in this paper, we consider that the database server judges the change of the radio environment by using Welch’s t-test, which is one of the hypothesis testings. In the proposed method, the sensor nodes observe the received power in each location and report this information to the database server. The database server tests the difference of the average received power between the initial REM and the new observed datasets and decides the requirement of update of the REM. The simulation results show that the proposed method can detect the change of the radio environment and accurately predict the average received power than the updating method using oblivion factor.","PeriodicalId":278172,"journal":{"name":"2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":"84 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":"132841494","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}
{"title":"SenseChain: Blockchain based Reputation System for Distributed Spectrum Enforcement","authors":"M. Careem, A. Dutta","doi":"10.1109/DySPAN.2019.8935812","DOIUrl":"https://doi.org/10.1109/DySPAN.2019.8935812","url":null,"abstract":"Distributed enforcement of spectrum policies require fusion of sensing results from a set of spatially scattered sensors to detect anomalous behavior with the highest possible accuracy. Central to this problem is the lack of trust or reputation of the participating sensors, which often leads to incorrect and biased inferences. In SenseChain, we leverage the distributed consensus mechanism employed in Blockchain networks to capture the reputation of the sensors, leading to a highly reliable and accurate enforcement system. Specifically, we define and analyze a detection mechanism to identify falsifying sensors using a distributed anomaly detection system and use the Blockchain to record the individual’s behavior. The reputation is then based on the combination of the difficulty level of the consensus method and the degree of falsehood in the reported sensor values. We evaluate SenseChain using an integrated Blockchain and anomaly detection simulator to show that DLTs can be used to track reputation of distributed sensors for distributed enforcement of spectrum policies.","PeriodicalId":278172,"journal":{"name":"2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":"111 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":"133675066","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}
Soo Min Kwon, Song Yang, Jian Liu, X. Yang, Wesam Saleh, Shreya Patel, Christine Mathews, Yingying Chen
{"title":"Demo: Hands-Free Human Activity Recognition Using Millimeter-Wave Sensors","authors":"Soo Min Kwon, Song Yang, Jian Liu, X. Yang, Wesam Saleh, Shreya Patel, Christine Mathews, Yingying Chen","doi":"10.1109/DySPAN.2019.8935665","DOIUrl":"https://doi.org/10.1109/DySPAN.2019.8935665","url":null,"abstract":"In this demo, we introduce a hands-free human activity recognition framework leveraging millimeter-wave (mmWave) sensors. Compared to other existing approaches, our network protects user privacy and can remodel a human skeleton performing the activity. Moreover, we show that our network can be achieved in one architecture, and be further optimized to have higher accuracy than those that can only get singular results (i.e. only get pose estimation or activity recognition). To demonstrate the practicality and robustness of our model, we will demonstrate our model in different settings (i.e. facing different backgrounds) and effectively show the accuracy of our network.","PeriodicalId":278172,"journal":{"name":"2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":"35 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":"128404747","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}
{"title":"Intelligent-CW: AI-based Framework for Controlling Contention Window in WLANs","authors":"A. Y. Abyaneh, Mohammed Hirzallah, M. Krunz","doi":"10.1109/DySPAN.2019.8935851","DOIUrl":"https://doi.org/10.1109/DySPAN.2019.8935851","url":null,"abstract":"The heterogeneity of technologies that operate over the unlicensed 5 GHz spectrum, such as LTE-Licensed-Assisted-Access (LAA), 5G New Radio Unlicensed (NR-U), and WiFi, calls for more intelligent and efficient techniques to coordinate channel access beyond what current standards offer. Wi-Fi standards require nodes to adopt a fixed value for the minimum contention window (CW$_{min})$, which prohibits a node from reacting to aggressive nodes that set their CWmin to small values. To address this problem, we propose a framework called Intelligent-CW (ICW) that allows nodes to adapt their CWmin values based on observed transmissions, ensuring they receive their fair share of the channel airtime. The CWmin value at a node is set based on a random forest, a machine learning model that includes a large number of decision trees. We train the random forest in a supervised manner over a large number of WLAN scenarios, including different misbehaving and aggressive scenarios. Under aggressive scenarios, our simulation results reveal that ICW provides nodes with higher throughput $(153.9$% gain) and 64% lower frame latency than standard techniques. In order to measure the fairness contribution of individual nodes, we introduce a new fairness metric. Based on this metric, ICW is shown to provide $10. 89 times $ improvement in fairness in aggressive scenarios compared to standard techniques.","PeriodicalId":278172,"journal":{"name":"2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":"7 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":"131708124","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}
M. Tonnemacher, Chance Tarver, Joseph Cavallar, J. Camp
{"title":"Machine Learning Enhanced Channel Selection for Unlicensed LTE","authors":"M. Tonnemacher, Chance Tarver, Joseph Cavallar, J. Camp","doi":"10.1109/DySPAN.2019.8935859","DOIUrl":"https://doi.org/10.1109/DySPAN.2019.8935859","url":null,"abstract":"We propose a mechanism for unlicensed LTE channel selection that not only takes into account interference to and from Wi-Fi access points but also considers other LTE operators in the unlicensed band. By collecting channel utilization statistics and sharing this information periodically with other unlicensed LTE eNBs, each eNB can improve their channel selection given their limited knowledge of the full topology. While comparing our algorithm to existing solutions, we find that the similarity between sensed Wi-Fi occupation at neighboring eNBs greatly impacts the performance of channel selection algorithms. To achieve better performance across diverse scenarios, we expand on our statistical channel selection formulation to include reinforcement learning, thereby balancing the shared contextual information with historical performance. We simulate operation in the unlicensed band using our channel selection algorithm and show how Wi-Fi load and inter-cell interference estimation can jointly be used to select transmission channels for all small cells in the network. Our approaches lead to an increase in user-perceived throughput and spectral efficiency across the entire band when compared to the greedy channel selection.","PeriodicalId":278172,"journal":{"name":"2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":"53 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":"122900658","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}
H. Kokkinen, Seppo Yrjölä, J. Milheiro, J. P. Borrego, N. Carvalho
{"title":"Results of the Demonstration of Licensed Shared Access with Sensing of Secondary Signal","authors":"H. Kokkinen, Seppo Yrjölä, J. Milheiro, J. P. Borrego, N. Carvalho","doi":"10.1109/DySPAN.2019.8935682","DOIUrl":"https://doi.org/10.1109/DySPAN.2019.8935682","url":null,"abstract":"Supplying radio spectrum for all demand is challenging. Licensed Shared Access (LSA) is a technology to allow different types of spectrum users to share radio spectrum. The current spectrum sharing systems are mainly based on propagation modeling. There are also a few examples of using spectrum sensing of the primary signal. Sensing the secondary spectrum user is a novel interference protection concept, and validation and piloting is required to find out its applicability in real environment. An end-to-end demonstration system was built together with mobile network operators, broadcasters, network vendors, technology providers, academia and the regulator to test the concept in spectrum sharing between LTE and Program Making and Special Events (PMSE) users in the 2.3 GHz band in Portugal. This paper presents the demonstration system, test setup results of the validation. Results showed that sensing of secondary signal at the receiver location of the primary user is an accurate and cost-efficient interference protection method for dynamic spectrum access. The system performed particularly well in the spectrum sharing arrangement, where the mobile network is always on, and the relatively high tower and high-power base stations are the main interference source. Furthermore, the concept was proven applicable in use cases where PMSE was deployed in a relatively small distinct area. The system can be deployed as a stand-alone setup or in combination with the propagation modelling-based methods.","PeriodicalId":278172,"journal":{"name":"2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":"12 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":"123870820","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}
{"title":"Poster: Using Commodity WiFi Devices For Object Sensing And Imaging","authors":"Laxima Niure Kandel, Zhuosheng Zhang, Shucheng Yu","doi":"10.1109/DySPAN.2019.8935637","DOIUrl":"https://doi.org/10.1109/DySPAN.2019.8935637","url":null,"abstract":"Object identification and imaging play an important role in many real-life applications such as robotics, automated vehicle networks and search and rescue operations in the aftermath of natural disasters. Existing traditional imaging systems require installing custom-built hardware and dedicated infrastructure which are expensive and not scalable. Also, they are not occlusion immune. With the pervasive and wide availability of WiFi infrastructure, in this project, we explore the possibility of seeing the world through the low-priced commodity WiFi devices by exploiting multipath reflections. WiFi-based solutions are promising due to their ubiquity and low cost. And unlike optical and infrared signals, WiFi can “see-through” walls, clothes and fabrics. We prototyped a $ 6 times 6 -$antenna planar array using commodity Intel NUCs and used 4 different objects for creating an image using a 2D Fourier transform. Our initial results using commercial off-the-shelf (COTS) hardware show promising results in the Line of Sight (LOS) environment.","PeriodicalId":278172,"journal":{"name":"2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":"32 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":"128993052","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}
C. Bowyer, David Greene, Tyler Ward, Marco Menéndez, J. Shea, T. Wong
{"title":"Reinforcement Learning for Mixed Cooperative/Competitive Dynamic Spectrum Access","authors":"C. Bowyer, David Greene, Tyler Ward, Marco Menéndez, J. Shea, T. Wong","doi":"10.1109/DySPAN.2019.8935725","DOIUrl":"https://doi.org/10.1109/DySPAN.2019.8935725","url":null,"abstract":"A dynamic spectrum sharing problem with a mixed collaborative/competitive objective and partial information about peers’ performances that arises from the DARPA Spectrum Collaboration Challenge is considered. Because of the very high complexity of the problem and the enormous size of the state space, it is broken down into the subproblems of channel selection, flow admission control, and transmission schedule assignment. The channel selection problem is the focus of this paper. A reinforcement learning algorithm based on a reduced state is developed to select channels, and a neural network is used as a function approximator to fill in missing values in the resulting input-action matrix. The performance is compared with that obtained by a hand-tuned expert system.","PeriodicalId":278172,"journal":{"name":"2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN)","volume":"10 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":"129084815","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}