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Unmanned aerial vehicles (UAVs) have gained a significant popularity in the recent past owing to their easy deployability and wide range of applications. In most of the short- and medium-range applications, Wi-Fi is used as the access technology for establishing communication between the ground stations and the UAVs. Although Wi-Fi is known to perform well in most of the scenarios, it is important to note that Wi-Fi has been mainly designed for indoor communication in rich scattering environments, whereas the air-to-ground (A2G) channel is characterized by sparse scattering. Considering this important difference in the channel characteristics, we revisit some of the Wi-Fi features and propose efficient design alternatives. First, we provide a statistical model for the sparse A2G channel and design an optimal time-domain quantizer (TDQ) for its feedback. In contrast to the frequency-domain quantizer (FDQ) of the IEEE 802.11n/ac Standard, the proposed TDQ exploits the time-domain sparsity in the channel and requires about 15 times lesser quantization bits than FDQ. Second, we propose a beamforming (BF) scheme with the aid of full-diversity rotation (FDR) matrices and analytically evaluate its symbol error probability in order to quantify the attainable diversity order. Our numerical simulations demonstrate that the proposed FDR-BF scheme outperforms the relevant benchmark schemes in both coded as well as uncoded scenarios. Specifically, the proposed FDR-BF scheme was observed to attain a signal-to-noise ratio gain as high as 6dB compared with the popular geometric mean decomposition-based BF scheme, when operating at an elevation angle of 7.5°.
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Rajashekar et al. (2018) studied this question.
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