J. Kokkoniemi, Alexandros-Apostolos A. Boulogeorgos, M. Aminu, Janne J. Lehtomäki, A. Alexiou, M. Juntti
{"title":"Stochastic Analysis of Indoor THz Uplink with Co-Channel Interference and Phase Noise","authors":"J. Kokkoniemi, Alexandros-Apostolos A. Boulogeorgos, M. Aminu, Janne J. Lehtomäki, A. Alexiou, M. Juntti","doi":"10.1109/ICCWorkshops49005.2020.9145251","DOIUrl":"https://doi.org/10.1109/ICCWorkshops49005.2020.9145251","url":null,"abstract":"The paper studies the joint impact of phase noise (PN) and co-channel interference (CCI) in indoor terahertz (THz) uplink. We formulate the theoretical framework that quantifies the impact of PN on the transceiver antenna directivity by extracting exact closed-form and low-complexity tight approximations for the expected gains. Additionally, by employing stochastic geometry, we model the propagation environment of indoor THz wireless systems and provide the analytical characterization of the CCI in the presence of PN, in terms of its expected value. The analysis is verified through computer simulations that reveal the accuracy of the presented theory with moderate numbers of users. The paper provides readily available tools for analyzing and designing indoor THz networks.","PeriodicalId":254869,"journal":{"name":"2020 IEEE International Conference on Communications Workshops (ICC Workshops)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123199561","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":"A Workflow for Onboarding Verticals on 5G/NFV Experimental Network Facility","authors":"C. Tranoris, S. Denazis","doi":"10.1109/ICCWorkshops49005.2020.9145426","DOIUrl":"https://doi.org/10.1109/ICCWorkshops49005.2020.9145426","url":null,"abstract":"5G is a major technology in creating and enhancing industry use cases such as autonomous driving, immersive gaming, remote robotic surgery and augmented reality. Vertical industries have addressed their connectivity and communication needs with dedicated or industry specific solutions. The European initiative 5G PPP has the vision to “empower the verticals” and thus defined key 5G network KPIs that can be accessed and used by vertical industries. This paper proposes a workflow that prepares a vertical towards seamless onboarding on a target experimental 5G network facility with the goal to access and validate 5G KPIs","PeriodicalId":254869,"journal":{"name":"2020 IEEE International Conference on Communications Workshops (ICC Workshops)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124512551","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}
Phuc Dinh, M. Arfaoui, S. Sharafeddine, C. Assi, A. Ghrayeb
{"title":"A Low-Complexity Approach for Sum-Rate Maximization in Cooperative NOMA Enhanced Cellular Networks","authors":"Phuc Dinh, M. Arfaoui, S. Sharafeddine, C. Assi, A. Ghrayeb","doi":"10.1109/ICCWorkshops49005.2020.9145440","DOIUrl":"https://doi.org/10.1109/ICCWorkshops49005.2020.9145440","url":null,"abstract":"This paper investigates the performance of cooperative non-orthogonal multiple access (C-NOMA) in a cellular downlink system. The system model consists of a base station (BS) serving multiple users, where users that have the capability of full-duplex (FD) communications can assist the transmissions between the BS and users with poor channel quality through device-to-device (D2D) communications. To maximize the achievable sum rate of the whole system while guaranteeing a certain quality of service (QoS) for all users, we formulate and solve a novel optimization problem that jointly determines the optimal D2D user pairing and the optimal power control scheme. The formulated problem is a mixed-integer non-linear program (MINLP), which has extremely high complexity. To overcome this issue, a two-step policy is proposed to solve the problem in polynomial time. First, we derive a closed-form expression of the optimal power control scheme that maximizes the sum rate of a given pair of users with a required QoS. Then, using the derived closed-form in the first step, we employ the Hungarian algorithm as the pairing policy in multi-user settings. Our simulation results show that the proposed scheme prevails some previously proposed heuristic approach for the given problem.","PeriodicalId":254869,"journal":{"name":"2020 IEEE International Conference on Communications Workshops (ICC Workshops)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125055049","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}
Nikita Tafintsev, D. Moltchanov, M. Simsek, Shu-ping Yeh, S. Andreev, Y. Koucheryavy, M. Valkama
{"title":"Reinforcement Learning for Improved UAV-Based Integrated Access and Backhaul Operation","authors":"Nikita Tafintsev, D. Moltchanov, M. Simsek, Shu-ping Yeh, S. Andreev, Y. Koucheryavy, M. Valkama","doi":"10.1109/ICCWorkshops49005.2020.9145423","DOIUrl":"https://doi.org/10.1109/ICCWorkshops49005.2020.9145423","url":null,"abstract":"There is a strong interest in utilizing commercial cellular networks to support unmanned aerial vehicles (UAVs) to send control commands and communicate heavy traffic. Cellular networks are well suited for offering reliable and secure connections to the UAVs as well as facilitating traffic management systems to enhance safe operation. However, for the full-scale integration of UAVs that perform critical and high-risk tasks, more advanced solutions are required to improve wireless connectivity in mobile networks. In this context, integrated access and backhaul (IAB) is an attractive approach for the UAVs to enhance connectivity and traffic forwarding. In this paper, we study a novel approach to dynamic associations based on reinforcement learning at the edge of the network and compare it to alternative association algorithms. Considering the average data rate, our results indicate that the reinforcement learning methods improve the achievable data rate. The optimal parameters of the introduced algorithm are highly sensitive to the donor next generation node base (DgNB) and UAV IAB node densities, and need to be identified beforehand or estimated via a stateful search. However, its performance nearly converges to that of the ideal scheme with a full knowledge of the data rates in dense deployments of DgNBs.","PeriodicalId":254869,"journal":{"name":"2020 IEEE International Conference on Communications Workshops (ICC Workshops)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121717655","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. Karaliopoulos, L. Chatzieleftheriou, George Darzanos, I. Koutsopoulos
{"title":"On the Joint Content Caching and User Association Problem in Small Cell Networks","authors":"M. Karaliopoulos, L. Chatzieleftheriou, George Darzanos, I. Koutsopoulos","doi":"10.1109/ICCWorkshops49005.2020.9145338","DOIUrl":"https://doi.org/10.1109/ICCWorkshops49005.2020.9145338","url":null,"abstract":"Caching at the edge of the radio network is increasingly viewed as a promising countermeasure to the staggering demand for mobile video content. The persistent orientation of newer generations of mobile communication systems towards lower latency and faster radio access speeds only strengthens the arguments in its favor. When content caching is coordinated with other radio resource management functions, in particular, the benefits for the end users and the network operator are significant. In this paper, we investigate these benefits in cache-enabled small cell networks that jointly control (i) the Small-Cell Base Stations (SBSs) that serve as network access points for the mobile users; and (ii) the content that is stored at the SBS co-located caches. Our main contribution is a fast-converging computationally simple heuristic algorithm that iterates between assigning users to small cells and content to SBS caches, to maximize the overall cache hit ratio. The algorithm solutions compete with the optimal assignments at small problem instances and outperform alternative solutions for larger instances, especially when the content demand exhibits spatial locality. Combining good performance with non-prohibitive complexity, the algorithm could become a valuable tool for small cell network operators seeking to optimize the use of radio network resources.","PeriodicalId":254869,"journal":{"name":"2020 IEEE International Conference on Communications Workshops (ICC Workshops)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122585391","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":"Context-Based Forwarding for Mobile ICNs","authors":"Luís Gameiro, Carlos R. Senna, Miguel Luís","doi":"10.1109/ICCWorkshops49005.2020.9145144","DOIUrl":"https://doi.org/10.1109/ICCWorkshops49005.2020.9145144","url":null,"abstract":"Over the last couple of decades, mobile ad-hoc networks (MANETs) have been at the forefront of research, yet still are afflicted by high network fragmentation, due to their continuous node mobility and geographical dispersion. To address these concerns, a new paradigm was proposed, Information-Centric Networks (ICN), whose focus is the delivery of Content based on names. This article aims to use ICN concepts towards the delivery of both urgent and non-urgent information in urban mobile environments. In order to do so, a context-based forwarding strategy was proposed, with a very clear goal: to take advantage of both packet Names and Data, and node's neighborhood analysis in order to successfully deliver content into the network in the shortest period of time, and without worsening network congestion. The design, implementation and validation of the proposed strategy was performed using the ndnSIM platform along with real mobility traces from communication infrastructure of the Porto city. The results show that the proposed context-based forwarding strategy presents a clear improvement regarding the Data resolution, while maintaining network overhead at a constant.","PeriodicalId":254869,"journal":{"name":"2020 IEEE International Conference on Communications Workshops (ICC Workshops)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122912132","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":"Secure Backhauling over Adaptive Parallel mmWave/FSO Link","authors":"Mai Kafafy, Y. Fahmy, M. Khairy, M. Abdallah","doi":"10.1109/ICCWorkshops49005.2020.9145354","DOIUrl":"https://doi.org/10.1109/ICCWorkshops49005.2020.9145354","url":null,"abstract":"FSO and MmWave are regarded as complimentary technologies for 5G backhaul links in order to avoid communication interruption in low visibility conditions. This paper secures the communication over two parallel FSO and MmWave links by optimizing the power and rate allocated to each link. The transmitter aims to maximize its transmission rate over the two links while satisfying a constraint on the security of the communication, represented by the secrecy outage probability, and a constraint on its power budget. Results show that transmission over the MmWave link increases when the secrecy requirement is not strict or when the eavesdropper moves farther from the transmitter, or when the fog becomes thick. Results also show that power and rate optimization improves the rates compared to the cases when the transmitter uses the FSO link only or the MmWave link only.","PeriodicalId":254869,"journal":{"name":"2020 IEEE International Conference on Communications Workshops (ICC Workshops)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123934078","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":"Blockchain-Based Wi-Fi Offloading Platform for 5G","authors":"Pramitha Fernando, Lasitha Gunawardhana, Wishva Rajapakshe, Mahesh Dananjaya, Tharindu D. Gamage, Madhusanka Liyanage","doi":"10.1109/ICCWorkshops49005.2020.9145369","DOIUrl":"https://doi.org/10.1109/ICCWorkshops49005.2020.9145369","url":null,"abstract":"The advent of 5G has sparked interest in Wi-Fi offloading techniques that enable efficient resource sharing and congestion management of wireless communication spectrum. However, offloading data between multiple networks (i.e. service providers) requires costly inter-provider communication which has a substantial overhead as well as high offloading latency. Moreover, involvement of the profit-oriented decision making of service providers has an inherent weakness of unfair scheduling among users and networks. To overcome those problems, this research work proposes a holistic framework similar to an online data market place where existing infrastructure can be used to set up Wi-Fi zones that everyone can use from their own data plan irrespective of the network operators they belong to. First, our proposed architecture improves the efficacy of offloading by using decentralized nature of the emerging Software-Defined Networking (SDN) to set up an operator-assisted data offloading platform, resulting in efficient inter-provider communication. Second, our proposal strengthens the fair scheduling of offloading resources by using blockchain technology to initiate unbiased and independent decision making. The resulting service is a rating system for the sellers to make reliable transactions for payments.","PeriodicalId":254869,"journal":{"name":"2020 IEEE International Conference on Communications Workshops (ICC Workshops)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124229080","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":"Complex-Valued Convolutions for Modulation Recognition using Deep Learning","authors":"J. Krzyston, R. Bhattacharjea, A. Stark","doi":"10.1109/ICCWorkshops49005.2020.9145469","DOIUrl":"https://doi.org/10.1109/ICCWorkshops49005.2020.9145469","url":null,"abstract":"Natural signals are inherently comprised of two components, real and imaginary components. Due to recent successes and progress in Deep Learning, specifically Convolutional Neural Networks (CNNs), this field of machine learning has become extremely popular when handling a wide variety of data, including natural signals. However, deep learning frameworks have been developed to deal with exclusively real-valued data and are unable to compute convolutions for complex-valued data. In this work, we present a linear combination that enables deep learning architectures to compute complex convolutions and learn features across the real and imaginary components of natural signals. When implemented into existing I/Q modulation classification architectures, this small change increases classification accuracy across a range of SNR levels by up to 35%.","PeriodicalId":254869,"journal":{"name":"2020 IEEE International Conference on Communications Workshops (ICC Workshops)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125902733","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":"High-Performance and Range-Supported Packet Classification Algorithm for Network Security Systems in SDN","authors":"Ling Zheng, Jing Jiang, Weitao Pan, Huan Liu","doi":"10.1109/ICCWorkshops49005.2020.9145461","DOIUrl":"https://doi.org/10.1109/ICCWorkshops49005.2020.9145461","url":null,"abstract":"Packet classification is a key function in network security systems in SDN, which detect potential threats by matching the packet header bits and a given rule set. It needs to support multi-dimensional fields, large rule sets, and high throughput. Bit Vector-based packet classification methods can support multi-field matching and achieve a very high throughput, However, the range matching is still challenging. To address issue, this paper proposes a Range Supported Bit Vector (RSBV) algorithm for processing the range fields. RSBV uses specially designed codes to store the pre-computed results in memory, and the result of range matching is derived through pipelined Boolean operations. Through a two-dimensional modular architecture, the RSBV can operate at a high clock frequency and line-rate processing can be guaranteed. Experimental results show that for a 1K and 512-bit OpenFlow rule set, the RSBV can sustain a throughput of 520 Million Packets Per Second.","PeriodicalId":254869,"journal":{"name":"2020 IEEE International Conference on Communications Workshops (ICC Workshops)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128391298","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}