Pub Date : 2019-02-01DOI: 10.1002/9781119473756.CH4
D. Korpi, T. Riihonen, M. Valkama
Traditionally, the backhauling of data in cellular networks has been handled by connecting the base station (BS) or access node (AN) to a core network via a physical cable. This ensures high data rates for the backhaul link, but requires the installing of cables that entails a high cost. This is an especially significant issue in the ultra-dense networks, where the number of ANs is too high for a physical backhaul link to be commercially feasible. To this The authors are with Laboratory of Electronics and Communications Engineering, Tampere University of Technology, Finland.
{"title":"Inband Full-duplex Self-backhauling in Ultra-dense Networks","authors":"D. Korpi, T. Riihonen, M. Valkama","doi":"10.1002/9781119473756.CH4","DOIUrl":"https://doi.org/10.1002/9781119473756.CH4","url":null,"abstract":"Traditionally, the backhauling of data in cellular networks has been handled by connecting the base station (BS) or access node (AN) to a core network via a physical cable. This ensures high data rates for the backhaul link, but requires the installing of cables that entails a high cost. This is an especially significant issue in the ultra-dense networks, where the number of ANs is too high for a physical backhaul link to be commercially feasible. To this The authors are with Laboratory of Electronics and Communications Engineering, Tampere University of Technology, Finland.","PeriodicalId":188440,"journal":{"name":"Ultra-dense Networks for 5G and Beyond","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122187481","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}
Pub Date : 2019-02-01DOI: 10.1002/9781119473756.CH3
M. Mkiramweni, Chungang Yang, Zhu Han
{"title":"Mean Field Games for 5G Ultra-dense Networks: A Resource Management Perspective","authors":"M. Mkiramweni, Chungang Yang, Zhu Han","doi":"10.1002/9781119473756.CH3","DOIUrl":"https://doi.org/10.1002/9781119473756.CH3","url":null,"abstract":"","PeriodicalId":188440,"journal":{"name":"Ultra-dense Networks for 5G and Beyond","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126314673","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}
Pub Date : 2019-02-01DOI: 10.1002/9781119473756.CH1
M. Kountouris, V. Nguyen
Mobile traffic has significantly increased over the last decade, mainly due to the stunning expansion of smart wireless devices and bandwidth-demanding applications. This trend is forecast to be maintained, especially with the deployment of fifth generation (5G) and beyond networks and machine-type communications. A major part of the mobile throughput growth during the past few years has been enabled by the so-called network densification, i.e. adding more base stations (BSs) and access points and exploiting spatial reuse of the spectrum. Emerging 5G cellular network deployments are envisaged to be heterogeneous and dense, primarily through the provisioning of small cells such as picocells and femtocells. Ultra-dense networks (UDNs) will remain among the most promising solutions to boost capacity and to enhance coverage with low-cost and power-efficient infrastructure in 5G networks. The underlying foundation of this expectation is the presumed linear capacity scaling with the number of small cells deployed in the network. In other words, doubling the number of BSs doubles the capacity the network supports in a given area and this can be done indefinitely. Nevertheless, in this context, several important questions arise: how close are we to fundamental limits of network densification? Can UDNs indefinitely bring higher overall data throughput gains in the network by just adding more infrastructure? If the capacity growth arrives to a plateau, what will cause this saturation and how the network should be optimized to push this saturation point further? These are the questions explored in this chapter. The performance of wireless networks relies critically on their spatial configuration upon which inter-node distances, fading characteristics, received signal power, and interference are dependent. Cellular networks have been traditionally modeled by placing the base stations on a regular grid (usually on a hexagonal lattice), with mobile users either randomly scattered or placed deterministically. Tractable analysis can sometimes be achieved for a fixed user location with a small number of interfering BSs and Monte Carlo simulations are usually performed for accurate performance evaluation. As cellular networks have become denser, they have also become increasingly irregular. This is particularly true for small cells, which are deployed opportunistically and in hotspots and dense heterogeneous networks (HetNets). As a result, the widely used deterministic grid model has started showing its limitations and cannot be used for general and
{"title":"Fundamental Limits of Ultra-dense Networks","authors":"M. Kountouris, V. Nguyen","doi":"10.1002/9781119473756.CH1","DOIUrl":"https://doi.org/10.1002/9781119473756.CH1","url":null,"abstract":"Mobile traffic has significantly increased over the last decade, mainly due to the stunning expansion of smart wireless devices and bandwidth-demanding applications. This trend is forecast to be maintained, especially with the deployment of fifth generation (5G) and beyond networks and machine-type communications. A major part of the mobile throughput growth during the past few years has been enabled by the so-called network densification, i.e. adding more base stations (BSs) and access points and exploiting spatial reuse of the spectrum. Emerging 5G cellular network deployments are envisaged to be heterogeneous and dense, primarily through the provisioning of small cells such as picocells and femtocells. Ultra-dense networks (UDNs) will remain among the most promising solutions to boost capacity and to enhance coverage with low-cost and power-efficient infrastructure in 5G networks. The underlying foundation of this expectation is the presumed linear capacity scaling with the number of small cells deployed in the network. In other words, doubling the number of BSs doubles the capacity the network supports in a given area and this can be done indefinitely. Nevertheless, in this context, several important questions arise: how close are we to fundamental limits of network densification? Can UDNs indefinitely bring higher overall data throughput gains in the network by just adding more infrastructure? If the capacity growth arrives to a plateau, what will cause this saturation and how the network should be optimized to push this saturation point further? These are the questions explored in this chapter. The performance of wireless networks relies critically on their spatial configuration upon which inter-node distances, fading characteristics, received signal power, and interference are dependent. Cellular networks have been traditionally modeled by placing the base stations on a regular grid (usually on a hexagonal lattice), with mobile users either randomly scattered or placed deterministically. Tractable analysis can sometimes be achieved for a fixed user location with a small number of interfering BSs and Monte Carlo simulations are usually performed for accurate performance evaluation. As cellular networks have become denser, they have also become increasingly irregular. This is particularly true for small cells, which are deployed opportunistically and in hotspots and dense heterogeneous networks (HetNets). As a result, the widely used deterministic grid model has started showing its limitations and cannot be used for general and","PeriodicalId":188440,"journal":{"name":"Ultra-dense Networks for 5G and Beyond","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123476421","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}
Pub Date : 2019-02-01DOI: 10.1002/9781119473756.CH2
A. Jafari, Ming Ding, D. López-Pérez
{"title":"Performance Analysis of Dense Small Cell Networks with Line of Sight and Non-Line of Sight Transmissions under Rician Fading","authors":"A. Jafari, Ming Ding, D. López-Pérez","doi":"10.1002/9781119473756.CH2","DOIUrl":"https://doi.org/10.1002/9781119473756.CH2","url":null,"abstract":"","PeriodicalId":188440,"journal":{"name":"Ultra-dense Networks for 5G and Beyond","volume":"55 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124866454","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}
Pub Date : 2019-02-01DOI: 10.1002/9781119473756.CH11
S. Gautam, T. Vu, S. Chatzinotas, B. Ottersten
{"title":"Simultaneous Wireless Information and Power Transfer in UDNs with Caching Architecture","authors":"S. Gautam, T. Vu, S. Chatzinotas, B. Ottersten","doi":"10.1002/9781119473756.CH11","DOIUrl":"https://doi.org/10.1002/9781119473756.CH11","url":null,"abstract":"","PeriodicalId":188440,"journal":{"name":"Ultra-dense Networks for 5G and Beyond","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134485082","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}
Pub Date : 2019-02-01DOI: 10.1002/9781119473756.CH9
Weisi Guo, Maria Liakata, Guillem Mosquera, Weijie Qi, Jie Deng, Jie Zhang
Wireless communications technology enables us to seamlessly access many multimedia services, e.g., stored multimedia (e.g., video on-demand), live streaming (e.g., Internet live sport networks, Internet radio stations), and real-time interactive streaming (e.g., online games, video conference, e-education), etc. As such, wireless communications technology has rapidly gained a crucial role and become an important aspect of life. Of most concern, however, is the increase in wireless/mobile devices and the huge demand in data rates associated with this. The future 5G cellular network is expected to achieve as much as 1000 times data rate relative to its current 4G counterpart. Data rates are projected to increase by a factor of ten every five years, and with the emerging Internet of Things (IoT) predicted to wirelessly connect trillions of devices across the globe, without novel approaches, future mobile networks (5G) will grind to a halt unless more capacity is created. One of the solutions is the implementation of ultra-dense networks, combining macro-cells and small-cells and exploiting the emerging technologies of millimetre wave (mm-wave) frequency bands and large-scale antennas arrays. The aim of this book is to present new research related to theory or practice of all aspects of ultra-dense networks.
{"title":"Big Data Methods for Ultra-dense Network Deployment","authors":"Weisi Guo, Maria Liakata, Guillem Mosquera, Weijie Qi, Jie Deng, Jie Zhang","doi":"10.1002/9781119473756.CH9","DOIUrl":"https://doi.org/10.1002/9781119473756.CH9","url":null,"abstract":"Wireless communications technology enables us to seamlessly access many multimedia services, e.g., stored multimedia (e.g., video on-demand), live streaming (e.g., Internet live sport networks, Internet radio stations), and real-time interactive streaming (e.g., online games, video conference, e-education), etc. As such, wireless communications technology has rapidly gained a crucial role and become an important aspect of life. Of most concern, however, is the increase in wireless/mobile devices and the huge demand in data rates associated with this. The future 5G cellular network is expected to achieve as much as 1000 times data rate relative to its current 4G counterpart. Data rates are projected to increase by a factor of ten every five years, and with the emerging Internet of Things (IoT) predicted to wirelessly connect trillions of devices across the globe, without novel approaches, future mobile networks (5G) will grind to a halt unless more capacity is created. One of the solutions is the implementation of ultra-dense networks, combining macro-cells and small-cells and exploiting the emerging technologies of millimetre wave (mm-wave) frequency bands and large-scale antennas arrays. The aim of this book is to present new research related to theory or practice of all aspects of ultra-dense networks.","PeriodicalId":188440,"journal":{"name":"Ultra-dense Networks for 5G and Beyond","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126733478","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}
Pub Date : 2019-02-01DOI: 10.1002/9781119473756.CH8
Quang-Doanh Vu, M. Juntti, E. Hong, Le-Nam Tran
part is to demonstrate how these methods can be applied to dense networks with shared spectrum and small-cell dense networks being the case studies.
部分是演示如何将这些方法应用于以共享频谱和小蜂窝密集网络为案例研究的密集网络。
{"title":"Energy Efficiency Optimization for Dense Networks","authors":"Quang-Doanh Vu, M. Juntti, E. Hong, Le-Nam Tran","doi":"10.1002/9781119473756.CH8","DOIUrl":"https://doi.org/10.1002/9781119473756.CH8","url":null,"abstract":"part is to demonstrate how these methods can be applied to dense networks with shared spectrum and small-cell dense networks being the case studies.","PeriodicalId":188440,"journal":{"name":"Ultra-dense Networks for 5G and Beyond","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125125689","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}
Pub Date : 2019-02-01DOI: 10.1002/9781119473756.ch5
Qi Zhang, H. Yang, Tony Q. S. Quek
{"title":"The Role of Massive MIMO and Small Cells in Ultra-dense Networks","authors":"Qi Zhang, H. Yang, Tony Q. S. Quek","doi":"10.1002/9781119473756.ch5","DOIUrl":"https://doi.org/10.1002/9781119473756.ch5","url":null,"abstract":"","PeriodicalId":188440,"journal":{"name":"Ultra-dense Networks for 5G and Beyond","volume":"304 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131029439","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}
Pub Date : 2019-02-01DOI: 10.1002/9781119473756.CH7
A. García‐Rodríguez, Giovanni Geraci, Lorenzo Galati-Giordano, D. López-Pérez
{"title":"Massive MIMO for High-performance Ultra-dense Networks in the Unlicensed Spectrum","authors":"A. García‐Rodríguez, Giovanni Geraci, Lorenzo Galati-Giordano, D. López-Pérez","doi":"10.1002/9781119473756.CH7","DOIUrl":"https://doi.org/10.1002/9781119473756.CH7","url":null,"abstract":"","PeriodicalId":188440,"journal":{"name":"Ultra-dense Networks for 5G and Beyond","volume":"175 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125342117","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}
Pub Date : 2019-02-01DOI: 10.1002/9781119473756.index
{"title":"Index","authors":"","doi":"10.1002/9781119473756.index","DOIUrl":"https://doi.org/10.1002/9781119473756.index","url":null,"abstract":"","PeriodicalId":188440,"journal":{"name":"Ultra-dense Networks for 5G and Beyond","volume":"65 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132827853","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}
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