Modeling and analysis of K-tier downlink heterogeneous cellular networks
IEEE Journal on Selected Areas in Communications, 2012•ieeexplore.ieee.org
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 …
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 …
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.
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