DNA-GA: A new approach of network performance analysis

In this paper, we propose a new approach of network performance analysis, which is based on our previous works on the deterministic network analysis using the Gaussian approximation (DNA-GA). First, we extend our previous works to a signal-to-interference ratio (SIR) analysis, which makes our DNA-GA analysis a formal microscopic analysis tool. Second, we show two approaches for upgrading the DNA-GA analysis to a macroscopic analysis tool. Finally, we perform a comparison between the proposed DNA-GA analysis and the existing macroscopic analysis based on stochastic geometry. Our results show that the DNA-GA analysis possesses a few special features: (i) shadow fading is naturally considered in the DNA-GA analysis; (ii) the DNA-GA analysis can handle non-uniform user distributions and any type of multi-path fading; (iii) the shape and/or the size of cell coverage areas in the DNA-GA analysis can be made arbitrary for the treatment of hotspot network scenarios. Thus, DNA-GA analysis is very useful for the network performance analysis of the 5th generation (5G) systems with general cell deployment and user distribution, both on a microscopic level and on a macroscopic level.

[1]  Jalal Almhana,et al.  Approximating Lognormal Sum Distributions With Power Lognormal Distributions , 2008, IEEE Transactions on Vehicular Technology.

[2]  Hsiao-Hwa Chen,et al.  Statistical Model of OFDMA Cellular Networks Uplink Interference Using Lognormal Distribution , 2013, IEEE Wireless Communications Letters.

[3]  Milton Abramowitz,et al.  Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables , 1964 .

[4]  Athanasios V. Vasilakos,et al.  Dynamic TDD transmissions in homogeneous small cell networks , 2014, 2014 IEEE International Conference on Communications Workshops (ICC).

[5]  Athanasios V. Vasilakos,et al.  Analysis on the SINR performance of dynamic TDD in homogeneous small cell networks , 2014, 2014 IEEE Global Communications Conference.

[6]  Zihuai Lin,et al.  Approximation of Uplink Inter-Cell Interference in FDMA Small Cell Networks , 2014, 2015 IEEE Global Communications Conference (GLOBECOM).

[7]  Jing Xu,et al.  Distribution of uplink inter-cell interference in OFDMA networks with power control , 2014, 2014 IEEE International Conference on Communications (ICC).

[8]  Jeffrey G. Andrews,et al.  Analytical Modeling of Uplink Cellular Networks , 2012, IEEE Transactions on Wireless Communications.

[9]  M. Abramowitz,et al.  Handbook of Mathematical Functions With Formulas, Graphs and Mathematical Tables (National Bureau of Standards Applied Mathematics Series No. 55) , 1965 .

[10]  Jeffrey G. Andrews,et al.  A Tractable Approach to Coverage and Rate in Cellular Networks , 2010, IEEE Transactions on Communications.

[11]  Zihuai Lin,et al.  Microscopic Analysis of the Uplink Interference in FDMA Small Cell Networks , 2015, IEEE Transactions on Wireless Communications.

[12]  Halim Yanikomeroglu,et al.  Fitting the Modified-Power-Lognormal to the Sum of Independent Lognormals Distribution , 2009, GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference.

[13]  Holger Claussen,et al.  Towards 1 Gbps/UE in Cellular Systems: Understanding Ultra-Dense Small Cell Deployments , 2015, IEEE Communications Surveys & Tutorials.

[14]  F. Massey The Kolmogorov-Smirnov Test for Goodness of Fit , 1951 .