The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Spectral and energy efficiency of ultra-dense networks under different deployment strategies
Abstract
To tackle the 1000× mobile data challenge, the research towards the 5th generation of mobile cellular networks is currently ongoing. One clear enabler toward substantially improved network area capacities is the increasing level of network densification at different layers of the overall heterogeneous radio access system. Ultra-dense deployments, or DenseNets, seek to take network densification to a whole new level, where extreme spatial reuse is deployed. This article looks into DenseNets from the perspectives of different deployment strategies, covering the densification of the classical macro layer, extremely dense indoor femto layer, as well as outdoor distributed antenna system (DAS), which can be dynamically configured as a single microcell or multiple independent microcells. Also, the potential of a new indoor-to-outdoor service provisioning paradigm is examined. The different deployment solutions are analyzed from the network area spectral and network energy efficiency perspectives, with extreme densification levels, including both indoor and outdoor use scenarios. The obtained results indicate that dedicated indoor solutions with densely deployed femtocells are much more spectrumand energy-efficient approaches to address the enormous indoor capacity demands compared to densifying the outdoor macro layer, when the systems are pushed to their capacity limits. Furthermore, the dynamic outdoor DAS concept offers an efficient and capacity-adaptive solution to provide outdoor capacity, on demand, in urban areas.
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“Cooperative relay communications and network densification would also help to reduce the transmit power of mobile device by reducing the per-hop signal propagation distance [64], [65].”
From What should 6G be? (2020) · cites this paper as [65]
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Cites
Massive MIMO for next generation wireless systems
Larsson, E. G., Edfors, O., Tufvesson, F., & Marzetta, T. L. (2014) · IEEE Communications Magazine · doi:10.1109/mcom.2014.6736761 · Cited by 6,797
Network densification: the dominant theme for wireless evolution into 5G
Bhushan, N., Li, J., Malladi, D., Gilmore, R., Brenner, D. E., Damnjanovic, A., Sukhavasi, R., Patel, C., & Geirhofer, S. (2014) · IEEE Communications Magazine · doi:10.1109/mcom.2014.6736747 · Cited by 1,180
Challenges and enabling technologies for energy aware mobile radio networks
Correia, L. M., Zeller, D., Blume, O., Ferling, D., Jading, Y., Gódor, I., Auer, G., & der Perre, L. V. (2010) · IEEE Communications Magazine · doi:10.1109/mcom.2010.5621969 · Cited by 572
Networks and devices for the 5G era
Bangerter, B., Talwar, S., Arefi, R., & Stewart, K. (2014) · IEEE Communications Magazine · doi:10.1109/mcom.2014.6736748 · Cited by 471
CROWD: An SDN Approach for DenseNets
Ali-Ahmad, H., Cicconetti, C., de la Oliva, A., Dräxler, M., Gupta, R. K., Mancuso, V., Roullet, L., & Sciancalepore, V. (2013) · European Workshop on Software Defined Networks (EWSDN) · doi:10.1109/ewsdn.2013.11 · Cited by 91
Cellular Mobile Network Densification Utilizing Micro Base Stations
Richter, F., & Fettweis, G. P. (2010) · International Conference on Communications · doi:10.1109/icc.2010.5502299 · Cited by 80
Impact of densification on energy efficiency in wireless access networks
Tombaz, S., Sung, K. W., & Zander, J. (2012) · IEEE Globecom Workshops (GC Wkshps) · doi:10.1109/glocomw.2012.6477544 · Cited by 35
The Inter-Cell Interference Dilemma in Dense Outdoor Small Cell Deployment
Polignano, M., Mogensen, P., Fotiadis, P., Gimenez, L. C., Viering, I., & Zanier, P. (2014) · IEEE Vehicular Technology Conference · doi:10.1109/vtcspring.2014.7023122 · Cited by 20
Ergodic capacity analysis of downlink distributed antenna systems using stochastic geometry
Lin, Y., & Yu, W. (2013) · International Conference on Communications · doi:10.1109/icc.2013.6655062 · Cited by 20
Asp, A., Sydorov, Y., Keskikastari, M., Valkama, M., & Niemelä, J. (2014) · IEEE Vehicular Technology Conference · doi:10.1109/vtcspring.2014.7022939 · Cited by 19
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Research works printed but not linked: 4
- 2013, Neighborhood Small Cells for Hyper Dense Deployments: Taking HetNets to the Next Level, White Paper
- 2011, C-RAN: The Road Towards Green RAN, white paper v 2 5
- yunas, 0, spectrum efficiency of Dynamic DAS with Extreme Downtilt Antenna Configuration, Proc IEEE PIMRC, 2183
- 2013, The 1000× Mobile Data Challenge, White Paper
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Items 201–209 of 209
Ge, X., Yang, J., & Ye, J. (2022) · Lecture notes in networks and systems · doi:10.1007/978-3-030-87049-2_13
On Energy Efficiency and Spectral Efficiency Joint Optimization of Ultra Dense Networks
Su, L., Yang, C., & Chih‐Lin, I. (2014) · Globecom · doi:10.1109/glocom.2014.7417555
Sustainable Ultra-Dense Heterogeneous Networks
An, J., Yang, K., Gao, X., & Ye, N. (2022) · Springer eBooks · doi:10.1007/978-981-19-0448-6_2
An, J., Yang, K., Gao, X., & Ye, N. (2022) · Springer eBooks · doi:10.1007/978-981-19-0448-6_1
Energy-Efficient User Scheduling and Power Control for Multi-Cell OFDMA Networks Based on CDI
An, J., Yang, K., Gao, X., & Ye, N. (2022) · Springer eBooks · doi:10.1007/978-981-19-0448-6_9
Wang, Y., Dong, Y., Zhang, Y., Zhou, J., Fang, Z., & Li, H. (2026) · International Conference on Communication, Remote Sensing and Information Technology (CRSIT) · doi:10.1109/crsit69981.2026.11605355
Metadata
- Authors
- Yunas, S., Valkama, M., & Niemelä, J.
- Affiliations
- Tampere University of Technology (FI)
- Elisa (Finland) (FI)
- Venue
- IEEE Communications Magazine
- Published
- 2015-01
- Volume
- 53
- Issue
- 1
- Pages
- 90-100
- ISSN
- 0163-6804 (ISSN-L)
- OpenAlex
- W2043827481
- Cited by
- 209
- References
- 13
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 5 · 2023: 5 · 2022: 9 · 2021: 18 · 2020: 19 · 2019: 31 · 2018: 37 · 2017: 36 · 2016: 38 · 2015: 7
- FWCI
- 18.97
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Communications Magazine (publishedVersion)
- Funders
- Tekes
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced MIMO Systems Optimization
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Millimeter-Wave Propagation and Modeling
- Physical Sciences › Engineering › Aerospace Engineering › UAV Applications and Optimization
- Keywords
- ultra-dense networks, network densification, spectral efficiency, energy efficiency, femtocells, distributed antenna systems, microcells, heterogeneous cellular networks, 5G
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