Coverage and Rate Analysis for Millimeter-Wave Cellular Networks

Abstract

Abstract-Millimeter wave (mmWave) holds promise as a carrier frequency for fifth generation cellular networks. Because mmWave signals are sensitive to blockage, prior models for cellular networks operated in the ultra high frequency (UHF) band do not apply to analyze mmWave cellular networks directly. Leveraging concepts from stochastic geometry, this paper proposes a general framework to evaluate the coverage and rate performance in mmWave cellular networks. Using a distancedependent line-of-site (LOS) probability function, the locations of the LOS and non-LOS base stations are modeled as two independent non-homogeneous Poisson point processes, to which different path loss laws are applied. Based on the proposed framework, expressions for the signal-to-noise-and-interference ratio (SINR) and rate coverage probability are derived. The mmWave coverage and rate performance are examined as a function of the antenna geometry and base station density. The case of dense networks is further analyzed by applying a simplified system model, in which the LOS region of a user is approximated as a fixed LOS ball. The results show that dense mmWave networks can achieve comparable coverage and much higher data rates than conventional UHF cellular systems, despite the presence of blockages. The results suggest that the cell size to achieve the optimal SINR scales with the average size of the area that is LOS to a user.

Coverage and rate analysis in the uplink of millimeter wave cellular networks with fractional power control

“…Also using the stochastic blockage process, authors in [11] proposed a framework to analyze the SINR and rate coverage probability of mmWave networks in the downlink channel while considering outdoor mmWave BSs and outdoor users. In [22], a more comprehensive analytic framework for mmWave cellular networks, which further incorporates selfbackhauling but with a simplified blockage model, was presented.…”

“…We model the location of users and BSs as realizations of the PPP. Similar to [11], we introduce the blockage effect by modeling the probability that a link is LOS as a function of the link length. We then model the transmit power of the users based on both FPC schemes.…”

“…The blocking effect is modeled according to [11], and we perform our analysis on a typical outdoor user whose connected BS is termed as the reference BS. An outdoor user can either be LOS or NLOS to the reference BS, as illustrated in Fig.…”

“…1 Visual representation of the uplink of mmWave cellular networks, focusing on the serving user and two interfering users in adjacent cells. Blockages are modeled as random process of rectangles as in [11]. White and red color marked users denotes the LOS and NLOS representation of the same user (1) where I(r) is a Bernoulli random variable with parameter r, C L and C N are the intercepts on the LOS and NLOS pathloss expressions, and α L and α N are the LOS and NLOS pathloss exponents.…”

“…The measurement showed that mmWave signals propagate with pathloss exponent of 2 in LOS paths and a much higher pathloss exponent with additional shadowing in NLOS paths [1,8]. Furthermore, the NLOS pathloss exponent tends to be more dependent on the scattering environment [11], with typical measured values ranging from 3.2 to 5.8 [1,8].…”