Abstract
In this article, using the stochastic geometry, we develop a tractable uplink modeling framework for the outage probability of the multitier millimeter wave (mmWave) cellular networks. Each tier’s mmWave base stations (BSs) are randomly located and they have particular spatial density, antenna gain, receiver sensitivity, blockage parameter, and pathloss exponents. Our model takes account of the maximum power limitation and the per-user power control. More specifically, each user, which could be in line-of-sight (LOS) or non-LOS to its serving mmWave BS, controls its transmit power such that the received signal power at its serving BS is equal to a predefined threshold. Hence, a truncated channel inversion power control scheme is implemented for the uplink of mmWave cellular networks. We derive closed-form expressions for the signal-to-interference-plus-noise-ratio (SINR) outage probability for the uplink of the multitier mmWave cellular networks, which we later degrade to the single-tier network. Furthermore, we analyze the case with a dense network by utilizing the simplified model, where the LOS region is approximated as a fixed LOS disk. The results show that imposing a maximum power constraint on the user significantly affects the SINR outage probability in the uplink of mmWave cellular networks.
Highlights
A FUNDAMENTAL requirement for the 5G-and-beyond mobile networks is the radical increase in data rate
The comparison reveals that our analysis provides several new insights that can be leveraged for designing the millimeter wave (mmWave) networks more accurately
Corollary III.1: In mmWave cellular networks with truncated channel inversion power control and cutoff threshold ρo, the probability distribution function (PDF) of the transmit power of a typical user in the uplink is given by fP (p) =
Summary
A FUNDAMENTAL requirement for the 5G-and-beyond mobile networks is the radical increase in data rate. ONIRETI et al.: OUTAGE PROBABILITY IN THE UPLINK OF MULTITIER mmWAVE CELLULAR NETWORKS be quite involved as compared to the downlink analysis due to the per-user power control and the correlation among the interferers [16]. The former is due to the fact that an interfering user could even be closer to a reference mmWave BS than the user that is tagged to the reference mmWave BS. We present a stochastic geometry framework for modeling and analyzing the uplink of a multitier mmWave cellular network. 1) We present a stochastic geometry framework for the signal-to-interference-plus-noise-ratio (SINR) outage probability in the uplink of the multitier mmWave cellular networks. The asymptotic dense network analysis have been derived for the multitier mmWave cellular networks
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