Autonomous Airborne Wireless Networks. Группа авторов
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Название: Autonomous Airborne Wireless Networks

Автор: Группа авторов

Издательство: John Wiley & Sons Limited

Жанр: Отраслевые издания

Серия:

isbn: 9781119751700

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СКАЧАТЬ rel="nofollow" href="#ulink_922b37dd-7ec0-5de2-9a2b-05f107f14d7f">Figure 2.1. For example, aerial surveillance can be a cost‐effective solution to provide access to those terrains that may be difficult to reach by humans in land vehicles. In this case, UAVs equipped with camera and sensors are used to gather video recordings and live images of a specific target on the ground and data from the sensor. Thereafter, the UAV has to coordinate with the ground user via existing cellular infrastructure and transfer the collected information with certain reliability, throughput, and delay while achieving the QoS requirements. The first scenario in Figure 2.1 (left side) requires a better connectivity between the aerial UE and at least one of the BSs installed typically at the ground. However, a performance drop is expected in the presence of aerial BSs acting as interferers. Moreover, the coexistence between the aerial UE, terrestrial UE, and the cellular infrastructure has to be studied.

      In wireless communications, the propagation channel is the free space between the transmitter and the receiver. It is obvious that the performance of wireless networks is influenced by the characteristics of the propagation channel. Therefore, knowledge of wireless channels is pertinent in designing UAV‐enabled networks for future wireless communication. Furthermore, the characterization of radio channel and its modeling for UAV network architecture are crucial for the analysis of network performance.

Schematic illustration of air-to-ground propagation in UAV-assisted cellular network.

      In addition, AA channels between airborne UAVs mostly experience strong LoS similar to the high‐altitude AG channels. However, Doppler shift is higher because UAV mobility is significantly higher and it is difficult to maintain alignment between multiple UAVs.

      Accurate AG and AA propagation channel models are imperative for the optimal deployment and the design of the UAV communication networks. This section will discuss recent efforts in the modeling of AG and AA propagation channels.

      2.4.1 Background

Schematic illustration of multipath air-to-ground propagation in urban setting.

      where PL is the distance‐dependent path loss, normal upper X Subscript normal upper L is the large‐scale fading consisting of power variation on a large scale due to the environment, and normal upper X Subscript normal upper S is the small‐scale fading. Parameters of channel model, such as path loss exponent and LoS probability, are dependent on the altitude level because propagation conditions change at different altitudes. The airspace is often segregated into three propagation echelons or slices as follows:

       Terrestrial channel: For suburban and urban environments, altitude is between 10 and 22.5 m, respectively [7]. In this case, the terrestrial channel models can be used to model AG propagation because the airborne UAV is below the rooftop level. As a result, NLoS is the dominant component in the propagation.

       Obstructed AG channel: For suburban and urban environments, altitude is 10–40 m and 22.5–100 m, respectively. In this case, LoS probability is higher than that of the terrestrial channels.

       High‐altitude AG channel: All channels are in LoS for the altitude ranges between 100 and 300 m or above. Consequently, the propagation is similar to that in the free space case. Moreover, no shadowing is experienced for these channels.

      2.4.1.1 Path Loss and Large‐Scale Fading

      Air‐to‐Air Channel Free space path loss model is the simplest channel model to represent the AA propagation at a relatively high altitude. Thus, the received power is given by [6]