mmWave Channel Measurements for 3-D Path Loss Analysis and Model Design in Stadiums

Abstract

A stadium is a multiuser scenario where the wireless system should be able to support real-time service delivery when the stadium is at full capacity during an event. To address radio propagation design for this type of challenging scenario, theoretical and empirical method is needed. Extensive open-space static measurements and research have been conducted at 28 and 60 GHz frequencies in an empty seating area of a stadium with a capacity of 60000 seats. The findings of this work lay a good foundation towards a greater understanding of mmWave channel propagation in a stadium, where a sectorization approach is considered to characterize the path loss behavior in 3D and predict it at unmeasured locations through the Kriging-aided model proposed with only 1 dB RMSE.

Generalizable Machine-Learning-Based Modeling of Radiowave Propagation in Stadiums

“…A variety of different sectorizations has been used in the literature for propagation in stadiums [14]. In elevation sectorization (also called level or concourse sectorization), different sectors are formed on the elevation plane of the stadium and mapped to different stadium levels [8], [10], [11]. In the azimuthal sectorization, the stadium is divided into sectors on the azimuthal plane [10], [15].…”

“…In elevation sectorization (also called level or concourse sectorization), different sectors are formed on the elevation plane of the stadium and mapped to different stadium levels [8], [10], [11]. In the azimuthal sectorization, the stadium is divided into sectors on the azimuthal plane [10], [15]. Then, the transmitting antenna points towards the line connecting the center of the stadium to the location of the sector [11], [13].…”

“…In the literature, all these aforementioned approaches have been employed for propagation modeling in stadiums. Measurement campaigns were undertaken in [2]- [10], RT simulations were used in [11]- [14], and propagation models were derived in [4], [8], [15]. Moreover, the geometry of the stadiums also varied, from small, open-track soccer stadiums [3] and closed basketball courts [9], to larger venues, such as multi-level stadiums, with capacities of tens of thousands of spectators [6], [7], [10].…”

“…Measurement campaigns were undertaken in [2]- [10], RT simulations were used in [11]- [14], and propagation models were derived in [4], [8], [15]. Moreover, the geometry of the stadiums also varied, from small, open-track soccer stadiums [3] and closed basketball courts [9], to larger venues, such as multi-level stadiums, with capacities of tens of thousands of spectators [6], [7], [10]. However, the role of parameters such as the transmitter (Tx) configuration (position, orientation and pattern) and the geometry of the stadium have not been included in existing models.…”

“…However, the role of parameters such as the transmitter (Tx) configuration (position, orientation and pattern) and the geometry of the stadium have not been included in existing models. Few papers derived propagation models to predict RSS at different locations within the same stadium, under a pre-defined Tx configuration [4], [8], [10], [15]. However, resource planning tasks, such as optimal placement of APs, require models that can generate fast and accurate predictions under multiple Tx configurations.…”