Özet
In the recent years, development of wireless communication devices lead to high demand of wireless communication system traffic and this demand is steadily rising day by day. At the same time, energy consumption problem arose in both mobile network's and mobile users' battery life time. Since the fact that development of spectral efficiency has been approaching to theoretical limits, new generation technologies are developed regarding to develop spectral efficiency. To achieve that, heterogonous network architecture is seen as best practice to solve both capacity and energy efficiency problem.
To assess the effects of heterogeneous network usage to performance, scenarios such as shadowing, path loss, interference and noise power are examined and three essential setup configuration are took into consideration. Those are; non-interference setup scenario with randomly distributed small cells, interference setup scenario between formally distributed small cells, and interference setup scenario between macro cells and formally distributed small cells. In these scenarios, mobile user moves at constant speed in the area of 1 km^2. In this thesis, the performance effect of scanning period, cell power output, mobile user speed and small cell density parameters are examined.
According to the results collected in each three scenarios, it is seen that increase of small cell density resulted with gain in power received by mobile users. However, it is also seen that excessive increase in small cell density is not much advantageous because of interference which is revealed during SINR observation. Excessive amount of small cell usage is unfavorable in terms of spectral efficiency and energy efficiency. For this reason, small cells have to be placed very carefully. In case of lack of macro cells or areas where data is highly demanded, setup of small cells could be useful.
Again, in all these scenarios it is seen that increase of scanning period resulted with decrease in signal quality. However, setting scanning period very low drains mobile users' battery life quickly. For this reason, scanning period should be rebalanced according to mobile users' benefit by taking into consideration signal quality.
When examining shadowing scenarios, to avoid negative effects of shadowing, small cell density can be increased or scanning period can be decreased.
In case of there is no macro base station, signal quality received by mobile user is changed in micro scales. At the same time, since the fact that mobile users' transmission power changes in micro scales, increased value of small cell transmit power is resulted with redundantly increased activity cost. On the other hand, in scenarios where macro cells are present, high power output is resulted with positive effect on signal received by mobile users.
Künye
[1] C. Cox, An Introduction to LTE. WILEY, 2012, vol. 24.
[2] T. Zhang, J. Zhao, L. An, and D. Liu, “Energy efficiency of base station deployment
in ultra dense hetnets: A stochastic geometry analysis,” IEEE WIRELESS COMMUNICATIONS
LETTERS, vol. 5, no. 2, pp. 184–187, April 2016.
[3] A. Prasad, O. Tirkkonen, P. Lunden, O. Yılmaz, L. Dalsgaard, and C. Wijting, “Energy
efficient inter-frequency small cell discovery techniques for lte-advanced heterogeneous
network deployments,” IEEE WIRELESS COMMUNICATIONS LETTERS,
vol. 5, no. 2, pp. 184–187, April 2013.
[4] S. Navaratnarajah, A. Saeed, M. Dianati, and M. A. Imran, “Energy efficiency in heterogenous
wireless access networks,” IEEE Wireless Communications, vol. 20,
no. 13914145, pp. 37–43, October 2013.
[5] D. Feng, C. Jiang, D. Mehrdad, G. Lim, L. J. Cimini, G. Feng, and G. Y. Li, “A survey
of energy-efficient wireless communications,” IEEE Communications Surveys &
Tutorials, vol. 15, no. 13914145, pp. 167–178, February 2012.
[6] A. Damnjanovic, J. Montojo, Y. Wei, T. Ji, T. Luo, M. Vajapeyam, T. Yoo, O. Song, and
D. Malladi, “A survey on 3gpp heterogeneous networks,” IEEE Wireless Communications,
vol. 18, no. 12062891, pp. 10–21, June 2011.
[7] S. C. Jha, M. Gupta, A. T. Koc, and R. Vannithamby, “On the impact of small cell
discovery mechanisms on device power consumption over lte networks,” First International
Black Sea Conference on Communications and Networking (BlackSeaCom),
pp. 116–120, 2013.
[8] A. Prasad, P. Lundén, O. Tirkkonen, and C. Wijting, “Enhanced small cell discovery
in heterogeneous networks using optimized rf fingerprints,” IEEE, no. 13916169,
November 2013.
[9] A. Prasad, P. Lundén, O. Tirkkonen, C. Wijting, O. N. Yilmaz, and L. Dalsgaard,
“Energy-efficient inter-frequency small cell discovery techniques for lte-advanced
heterogeneous network deployments,” IEEE, vol. 51, pp. 72–81, May 2013.
[10] W. Chen, H. Li, Z. Li, Z. Xiao, and D. Wang, “Optimization of small cell deployment
in heterogeneous wireless networks,” ETRI Journal, no. 16233151, July 2016.
[11] S. N. K. Marwat, “Lte channel modelling for system level simulations,” Master’s thesis,
University of Bremen, Bremen, 09 2011, master Mini-Project.
[12] A. Prasad, O. Tirkkonen, P. Lunden, O. Yılmaz, L. Dalsgaard, and C. Wijting, “Selection
procedures for the choice of radio transmission technologies of the umts,”
European Telecommunications Standards Institute, vol. 3.2.0, no. 2, pp. 184–187,
April 1998.
[13] M. R. Akdeniz, L. Yuanpeng, M. K. Samimi, S. Sun, S. Rangan, T. S. Rappaport,
and E. Erkip, “Millimeter wave channel modeling and cellular capacity evaluation,”
IEEE Journal on Selected Areas in Communications, vol. 32, no. 14469236, pp.
1164–1179, June 2014.
[14] M. Franceschetti and R. Meester, Random networks for communication: from statistical
physics to information systems. Cambridge University Press, 2007, vol. 24.
[15] S. Lee, S. Lee, K. Kim, and Y. H. Kim, “Base station placement algorithm for largescale
lte heterogeneous networks,” PLoS One, October 2015.
[16] H.-S. Park, Y.-S. Choi, B.-C. Kim, and J.-Y. Lee, “Lte mobility enhancements for evolution
into 5g,” ETRI Journal, vol. 37, no. 6, pp. 1065–1076, December 2015.
[17] H. Holma and A. Toskala, WCDMA for UMTS: HSPA Evolution and LTE. Wiley,
2010, vol. 5.
[18] P. Joshi, D. Colombi, B. Thors, L.-E. Larsson, and C. Törnevik, “Output power levels
of 4g user equipment and implications on realistic rf emf exposure assessments,”
IEEE Access, vol. 5, no. 16811602, pp. 2169–3536, March 2017.
