TY - JOUR
T1 - Stochastic Geometric Coverage Analysis in mmWave Cellular Networks With Realistic Channel and Antenna Radiation Models
AU - Rebato, M.
AU - Park, J.
AU - Popovski, P.
AU - Carvalho, E. De
AU - Zorzi, M.
PY - 2019/5
Y1 - 2019/5
N2 - Millimeter-wave (mmWave) bands will play an important role in 5G wireless systems. The system performance can be assessed by using models from stochastic geometry that cater for the directivity in the desired signal transmissions as well as the interference, and by calculating the signal-To-interference-plus-noise ratio ( \mathsf {SINR} ) coverage. Nonetheless, the accuracy of the existing coverage expressions derived through stochastic geometry may be questioned, as it is not clear whether they would capture the impact of the detailed mmWave channel and antenna features. In this paper, we propose an \mathsf {SINR} coverage analysis framework that includes realistic channel model and antenna element radiation patterns. We introduce and estimate two parameters, aligned gain and misaligned gain, associated with the desired signal beam and the interfering signal beam, respectively. The distributions of these gains are used to determine the distribution of the \mathsf {SINR} which is compared with the corresponding \mathsf {SINR} coverage, calculated through the system-level simulations. The results show that both aligned and misaligned gains can be modeled as exponential-logarithmically distributed random variables with the highest accuracy, and can further be approximated as exponentially distributed random variables with reasonable accuracy. These approximations can be used as a tool to evaluate the system-level performance of various 5G connectivity scenarios in the mmWave band.
AB - Millimeter-wave (mmWave) bands will play an important role in 5G wireless systems. The system performance can be assessed by using models from stochastic geometry that cater for the directivity in the desired signal transmissions as well as the interference, and by calculating the signal-To-interference-plus-noise ratio ( \mathsf {SINR} ) coverage. Nonetheless, the accuracy of the existing coverage expressions derived through stochastic geometry may be questioned, as it is not clear whether they would capture the impact of the detailed mmWave channel and antenna features. In this paper, we propose an \mathsf {SINR} coverage analysis framework that includes realistic channel model and antenna element radiation patterns. We introduce and estimate two parameters, aligned gain and misaligned gain, associated with the desired signal beam and the interfering signal beam, respectively. The distributions of these gains are used to determine the distribution of the \mathsf {SINR} which is compared with the corresponding \mathsf {SINR} coverage, calculated through the system-level simulations. The results show that both aligned and misaligned gains can be modeled as exponential-logarithmically distributed random variables with the highest accuracy, and can further be approximated as exponentially distributed random variables with reasonable accuracy. These approximations can be used as a tool to evaluate the system-level performance of various 5G connectivity scenarios in the mmWave band.
KW - 5G mobile communication
KW - antenna radiation patterns
KW - cellular radio
KW - exponential distribution
KW - geometry
KW - radiofrequency interference
KW - stochastic processes
KW - signal transmissions
KW - signal-to-interference-plus-noise ratio coverage
KW - coverage expressions
KW - mmWave band
KW - system-level performance
KW - exponential-logarithmically distributed random variables
KW - system-level simulations
KW - interfering signal beam
KW - misaligned gain
KW - aligned gain
KW - antenna element radiation patterns
KW - realistic channel model
KW - SINR coverage analysis framework
KW - antenna features
KW - system performance
KW - millimeter-wave bands
KW - antenna radiation models
KW - mmWave cellular networks
KW - stochastic geometric coverage analysis
KW - Interference
KW - Antenna radiation patterns
KW - Antenna arrays
KW - Signal to noise ratio
KW - 3GPP
KW - Stochastic processes
KW - Channel models
KW - Millimeter-wave
KW - channel model
KW - antenna radiation pattern
KW - large-scale cellular networks
KW - stochastic geometry
UR - http://www.scopus.com/inward/record.url?scp=85065888944&partnerID=8YFLogxK
U2 - 10.1109/TCOMM.2019.2895850
DO - 10.1109/TCOMM.2019.2895850
M3 - Journal article
SN - 0090-6778
VL - 67
SP - 3736
EP - 3752
JO - IEEE Transactions on Communications
JF - IEEE Transactions on Communications
IS - 5
M1 - 8628991
ER -