Modeling and Analysis of K-Tier Downlink Heterogeneous Cellular Networks

By Harpreet S. Dhillon, Radha Krishna Ganti, François Baccelli, Jeffrey G. Andrews. IEEE Journal on Selected Areas in Communications, 2011

1,597 citations recorded by the source corpus.

Cellular networks are in a major transition from a carefully planned set of large tower-mounted base-stations (BSs) to an irregular deployment of heterogeneous infrastructure elements that often additionally includes micro, pico, and femtocells, as well as distributed antennas. In this paper, we develop a tractable, flexible, and accurate model for a downlink heterogeneous cellular network (HCN) consisting of K tiers of randomly located BSs, where each tier may differ in terms of average transmit power, supported data rate and BS density. Assuming a mobile user connects to the strongest candidate BS, the resulting Signal-to-Interference-plus-Noise-Ratio (SINR) is greater than 1 when in coverage, Rayleigh fading, we derive an expression for the probability of coverage (equivalently outage) over the entire network under both open and closed access, which assumes a strikingly simple closed-form in the high SINR regime and is accurate down to -4 dB even under weaker assumptions. For external validation, we compare against an actual LTE network (for tier 1) with the other K-1 tiers being modeled as independent Poisson Point Processes. In this case as well, our model is accurate to within 1-2 dB. We also derive the average rate achieved by a randomly located mobile and the average load on each tier of BSs. One interesting observation for interference-limited open access networks is that at a given \sinr, adding more tiers and/or BSs neither increases nor decreases the probability of coverage or outage when all the tiers have the same target-SINR.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/4dfa91a88cdeb82b5d810212bbbb92dc2f425c4e

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Citations in the corpus

Stochastic Geometry for Modeling, Analysis, and Design of Multi-Tier and Cognitive Cellular Wireless Networks: A Survey (2013, methodology): “extended the model in [54] and [55] to include FFR in single and multi-tier cellular networks.”
Seven ways that HetNets are a cellular paradigm shift (2013, background): “A high-level introduction and summary of the model and results in [5] is given in [6] and so not repeated here.”
Coverage and Rate Analysis for Millimeter-Wave Cellular Networks (2014, background): “whereT̄ = mrmtT MrMt , (b) is obtained from (27), (c) is from the union bound, (d) follows from the fact that the upper bound in (27) has the same distribution as in the Rayleigh-fading network in [18], and the similar algebra in [18, Appendix B, Eqn (15)-(17)], and (e) is from the fact that ∫∞ 0 1 ”
User Association in 5G Networks: A Survey and an Outlook (2015, methodology): “Dual connectivity can significantly improve the mobility resilience and increase the attainable user throughp t due to its potential of extending the CA and coordinated multi-point (CoMP) to multiple BSs, which allows users to be simultaneously associated with both macro BSs and small cell BSs.”
A Primer on Cellular Network Analysis Using Stochastic Geometry (2016, methodology): “As demonstrated first in [3], the analysis greatly simplifies for τi > 1 (0 dB) for all tiers.”
What Will 5G Be? (2014, background): “In the remainder of this section, these are distilled in some detail.”
Smart radio environments empowered by reconfigurable AI meta-surfaces: an idea whose time has come (2019, background): “Since then, their application to the modeling and analysis of wireless networks has been relent-less [110–112].”
Analytical Modeling of Uplink Cellular Networks (2012, background): “A major arena for future work is to understand how these dynamics are enhanced or differ for heterogeneous network topologies [18], [45].”
Spatio-Temporal Analysis for SINR Coverage in Small Cell Networks (2019, background): “The intrinsic elegance in modeling and analysis has popularized its application in evaluating performance among various wireless systems, including ad-hoc networks [5], cellular networks [9], or more advanced heterogeneous networks [10], even with device-to-device (D2D) communication [11] and multip”
Analysis of Blockage Effects on Urban Cellular Networks (2013, background): “The results of [8] were extended to multi-tier networks in [9].”
On Stochastic Geometry Modeling of Cellular Uplink Transmission With Truncated Channel Inversion Power Control (2014, background): “2316519 a randomized topology with uncertainties in the locations of the BSs [1], [2].”
User Association for Load Balancing in Heterogeneous Cellular Networks (2012, background): “With FUA, the indicators xij can take on any real value in [0, 1].”
Modeling heterogeneous network interference (2012, background): “For example [21] extends [12] to provide some results on the signal-to-interference ratio in multi-tier networks while [22] extends [5] to provide remarkable simple expressions for the success probability in multi-tier networks.”
Analytical Modeling of Mode Selection and Power Control for Underlay D2D Communication in Cellular Networks (2014, background): “Therefore, the shared spectrum assignment (also called underlay spectrum access) for D2D devices is generally preferred over the disjoint spectrum assignment approach [3].”
Heterogeneous Cellular Networks with Flexible Cell Association: A Comprehensive Downlink SINR Analysis (2011, background): “In the context of the heterogeneous deployments of interest in the present paper, a tractable model for SINR in a general K-tier downlink HCN has recently been found under certain assumptions [24], [25].”