Autocorrelation and Coherence Time of Interference in Poisson Networks

This article takes an analytical approach to investigate the temporal dynamics of interference in wireless networks. We propose a framework to calculate the autocorrelation of interference in Poisson networks and derive closed-form expressions for the case of Nakagami fading. The framework takes three correlation sources into account: the location of interferers, the wireless channel, and the data traffic. We introduce the interference coherence time—in analogy to the well-established channel coherence time—and show how its basic qualitative behavior depends on the source of correlation. The insights gained can be useful in the design of medium access control and retransmission protocols.

[1]  Jeffrey G. Andrews,et al.  Modeling and Analyzing Millimeter Wave Cellular Systems , 2016, IEEE Transactions on Communications.

[2]  Martin Haenggi,et al.  Managing Interference Correlation Through Random Medium Access , 2013, IEEE Transactions on Wireless Communications.

[3]  R. Clarke A statistical theory of mobile-radio reception , 1968 .

[4]  Jeffrey G. Andrews,et al.  Effect of Spatial Interference Correlation on the Performance of Maximum Ratio Combining , 2013, IEEE Transactions on Wireless Communications.

[5]  Stavros Toumpis,et al.  How does interference dynamics influence packet delivery in cooperative relaying? , 2013, MSWiM.

[6]  Martin Haenggi,et al.  Temporal Correlation of the Interference in Mobile Random Networks , 2011, 2011 IEEE International Conference on Communications (ICC).

[7]  David Tse,et al.  Fundamentals of Wireless Communication , 2005 .

[8]  Martin Haenggi,et al.  Spatial and temporal correlation of the interference in ALOHA ad hoc networks , 2009, IEEE Communications Letters.

[9]  Stavros Toumpis,et al.  Interference Functionals in Poisson Networks , 2016, IEEE Transactions on Information Theory.

[10]  Christian Bettstetter,et al.  Semi-Blind Interference Prediction in Wireless Networks , 2017, MSWiM.

[11]  Stavros Toumpis,et al.  Cooperative Relaying Under Spatially and Temporally Correlated Interference , 2013, IEEE Transactions on Vehicular Technology.

[12]  Jeffrey G. Andrews,et al.  Dual-Branch MRC Receivers Under Spatial Interference Correlation and Nakagami Fading , 2013, IEEE Transactions on Communications.

[13]  Martin Haenggi,et al.  Interference and Outage in Mobile Random Networks: Expectation, Distribution, and Correlation , 2014, IEEE Transactions on Mobile Computing.

[14]  Christian Bettstetter,et al.  Temporal Correlation of Interference: Cases with Correlated Traffic , 2013 .

[15]  仲上 稔,et al.  The m-Distribution As the General Formula of Intensity Distribution of Rapid Fading , 1957 .

[16]  Martin Haenggi Diversity Loss Due to Interference Correlation , 2012, IEEE Communications Letters.

[17]  Christian Bettstetter,et al.  Temporal Correlation of Interference in Wireless Networks with Rayleigh Block Fading , 2012, IEEE Transactions on Mobile Computing.

[18]  Tony Q. S. Quek,et al.  Toward a Tractable Delay Analysis in Ultra-Dense Networks , 2017, IEEE Communications Magazine.

[19]  Martin Haenggi,et al.  Diversity Polynomials for the Analysis of Temporal Correlations in Wireless Networks , 2013, IEEE Transactions on Wireless Communications.

[20]  Martin Haenggi,et al.  Stochastic Geometry for Wireless Networks , 2012 .

[21]  Paolo Santi,et al.  The Node Distribution of the Random Waypoint Mobility Model for Wireless Ad Hoc Networks , 2003, IEEE Trans. Mob. Comput..

[22]  Qimei Cui,et al.  The SIR Meta Distribution in Poisson Cellular Networks With Base Station Cooperation , 2018, IEEE Transactions on Communications.

[23]  Xiaohu Ge,et al.  Heterogeneous Cellular Networks With Spatio-Temporal Traffic: Delay Analysis and Scheduling , 2016, IEEE Journal on Selected Areas in Communications.

[24]  B. Sklar,et al.  Rayleigh fading channels in mobile digital communication systems Part I: Characterization , 1997, IEEE Commun. Mag..

[25]  Angel Lozano,et al.  Ergodic Spectral Efficiency in MIMO Cellular Networks , 2016, IEEE Transactions on Wireless Communications.

[26]  Jeffrey G. Andrews,et al.  Stochastic geometry and random graphs for the analysis and design of wireless networks , 2009, IEEE Journal on Selected Areas in Communications.