Data set for A Beamforming Aided Full-Diversity Scheme for Low-Altitude Air-to-Ground Communication Systems Operating with Limited Feedback

Abstract

Unmanned aerial vehicles (UAV) have gained 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, WiFi is used as the access technology for establishing communication between the ground stations and the UAVs. Although WiFi is known to perform well in most of the scenarios, it is important to note that WiFi has been mainly designed for indoor communication in rich scattering environments, whereas the air-to-ground (A2G) channel is characterised by sparse scattering. Considering this important difference in the channel characteristics, we revisit some of the WiFi features and propose efficient design alternatives. Firstly, 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 802.11n/ac standard, the proposed TDQ exploits the time-domain sparsity in the channel and requires about fifteen times lesser quantization bits than FDQ. Secondly, we propose a beamforming 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 beamforming (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 to the popular geometric mean decomposition based beamforming scheme, when operating at an elevation angle of $7.5^o$.

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