Kateřina Dufková
ABSTRACT
We study the energy consumptions of two strategies that increase the capacity of an LTE network: (1) the deployment of redundant macro and micro base stations by the operator at locations where the traffic is high, and (2) the deployment of publicly accessible femto base stations by home users. Previous studies show the deployment of publicly accessible residential femto base stations is considerably more energy efficient; however, the results are proposed using an abstracted model of LTE networks, where the coverage constraint was neglected in the study, as well as some other important physical and traffic layer specifications of LTE networks. We study a realistic scenario where coverage is provided by a set of non-redundant macro-micro base stations and additional capacity is provided by redundant macro-micro base stations or by femto base stations. We quantify the energy consumption of macro-micro and femto deployment strategies by using a simulation of a plausible LTE deployment in a mid-size metropolitan area, based on data obtained from an operator and using detailed models of heterogeneous devices, traffic, and physical layers. The metrics of interest are operator-energy-consumption/total-energy-consumption per unit of network capacity.
For the scenarios we studied, we observe the following: (1) There is no significant difference between operator energy consumption of femto and macro-micro deployment strategies. From the point of view of society, i.e. total energy consumption, macro-micro deployment is even more energy efficient in some cases. This differs from the previous findings, which compared the energy consumption of femto and macro-micro deployment strategies, and found that femto deployment is considerably more energy efficient. (2) The deployment of femto base stations has a positive effect on mobile-terminal energy consumption; however, it is not significant compared to the macro-micro deployment strategy. (3) The energy saving that could be obtained by making macro and micro base stations more energy proportional is much higher than that of femto deployment.
- H.-O. Scheck. ICT & wireless networks and their impact on global warming. In European Wireless Conference, 2010.Google Scholar
- Cisco. Cisco visual networking index: Global mobile data traffic forecast update, 2009--2014. White paper, 2010.Google Scholar
- S. R. Saunders, S. Carlaw, A. Giustina, R. R. Bhat, V. S. Rao, and R. Siegberg. Femtocells: Opportunities and Challenges for Business and Technology. Wiley, 2009.Google Scholar
- H. Claussen, L. T. W. Ho, and F. Pivit. Leveraging advances in mobile broadband technology to improve environmental sustainability. Telecommunications Journal of Australia, 59(1), 2009.Google ScholarCross Ref
- Benyuan Liu and Don Towsley. A study of the coverage of large-scale sensor networks. In In Proceeding of MASS04.Google Scholar
- A. J. Fehske, F. Richter, and G. P. Fettweis. Energy efficiency improvements through micro sites in cellular mobile radio networks. In GLOBECOM Workshops, 2009.Google ScholarCross Ref
- P. Somavat, S. Jadhav, and V. Namboodiri. Accounting for the energy consumption of personal computing including portable devices. In Proceedings of e-Energy 2010, April 2010. Google ScholarDigital Library
- Ericsson. Sustainable energy use in mobile communications. White paper, 2007.Google Scholar
- Femto Forum. http://www.femtoforum.org.Google Scholar
- 3GPP Technical Specification Group Radio Access Network. Further advancements for E-UTRA physical layer aspects (Release 9). Technical report, 2010.Google Scholar
- OFCOM. Radio transmitters locations in Switzerland. http://www.funksender.ch/webgis/bakom.php, July 2010.Google Scholar
- HNB and HNB-Macro Propagation Models. Technical report, Qualcomm Europe, 2007.Google Scholar
- 3GPP Technical Specification Group Radio Access Network. Spatial channel model for multiple input multiple output (MIMO) simulations (Release 9). Technical report, 2009.Google Scholar
- T. Bonald and N. Hegde. Capacity gains of some frequency reuse schemes in ofdma networks. In GLOBECOM, 2009. Google ScholarDigital Library
- Jean-Yves Le Boudec. Performance evaluation of computer and communication systems. EPFL Press, 2010.Google Scholar
- Thomas Bonald. Insensitive queueing models for communication networks. In VALUETOOLS, 2006. Google ScholarDigital Library
- T. Bonald and A. Proutière. On performance bounds for the integration of elastic and adaptive streaming flows. SIGMETRICS Perform. Eval. Rev., 32, 2004. Google ScholarDigital Library
- M. Chiang, P Hande, T Lan, and CW Tan. Power control in wireless cellular networks. now Publishers Inc., 2008.Google Scholar
- G. Miao, N. Himayat, G. Y. Li, A. T. Koc, and S. Talwar. Interference-aware energy-efficient power optimization. In ICC, 2009. Google ScholarDigital Library
- Y. M. Kwon, O. K. Lee, J. Y. Lee, and M. Y. Chung. Power control for soft fractional frequency reuse in ofdma system. In ICCSA, 2010. Google ScholarDigital Library
- C. Y. Wong, R. S. Cheng, K. B. Letaief, and R. D. Murch. Multiuser ofdm with adaptive subcarrier, bit, and power allocation. IEEE JSAC, 17, 1999. Google ScholarDigital Library
- G. J. Fochini, K. Karakayali, and R. A. Valenzuela. Coordinating multiple antenna cellular networks to achieve enormous spectral efficiency. IEEE Proc.-Commun., 153(4), 2009.Google Scholar
- Jean-Yves Le Boudec and Milan Vojnovic. The random trip model: Stability, stationary regime, and perfect simulation. IEEE/ACM Transactions on Networking, 14, 2006. Google ScholarDigital Library
Index Terms
- Energy consumption comparison between macro-micro and public femto deployment in a plausible LTE network
Recommendations
Energy saving and capacity gain of micro sites in regular LTE networks: downlink traffic layer analysis
PM2HW2N '11: Proceedings of the 6th ACM workshop on Performance monitoring and measurement of heterogeneous wireless and wired networksWe study the effect of deployment of low cost, low power micro base stations along with macro base stations on energy consumption and capacity of downlink LTE. [1] studied this problem, using spectral area efficiency as the performance metric. We show ...
Mitigating Uplink Interference in Femto---Macro Coexisted Heterogeneous Network by Using Power Control
In the femto---macro coexisted heterogeneous network, the uplink transmission of femtocell user equipment (FUE) interferes with the macrocell base station (MBS) and deteriorates the capacity of macrocell user equipments (MUEs). To mitigate the cross-...
A collaborative power control and resources allocation for D2D (device-to-device) communication underlaying LTE cellular networks
Device-to-device (D2D) communication under long term evolution-advanced (LTE-A) system is a promising technology that can realize end-to-end communication through the reuse of cellular user resources within a cell. D2D communication can effectively ...
Comments