Channel Estimation Refinement for Tethered Aerial Platform Enabled Multi-User Communication Systems

This paper investigates the three-dimensional (3D) downlink sparse channel estimation for tethered aerial platformenabled multi-user communication systems operating in a frequency division duplexing mode with large-scale antenna arrays. To this end, we design a non-identical Bernoulli-Gaussian distribution-based channel model that reflects the potential common sparsity caused by distant scatterers in a low-altitude environment. A low-complexity channel estimation algorithm without the need for prior knowledge of channel sparsity is proposed. It first applies a greedy pursuit algorithm to roughly estimate the common support set (CSS). Given the initial CSS, multi-user channels are then iteratively estimated and refined using a novel neighborhood-based channel estimation refinement scheme, which includes a decentralized sparse channel estimator to recover sparse channels accurately under non-i.i.d channel sparsity priors with low computation burden. Simulation results indicate that the proposed algorithm outperforms its existing counterparts and approaches the performance limit with perfect knowledge of the CSS.

I. Introduction

The tethered aerial platform (TAP) communication systems play a crucial role in providing responsive (emergency) communication services. A TAP in the systems has a high payload capability (e.g., X-Tower with a payload of 130 kg). It will be a practical and promising proposal of installing large-scale antenna arrays on the TAP to dramatically improve the throughput and efficiency of TAP communication systems. This work focuses on the investigation of accurate estimation of channel state information (CSI) at the transmitter of TAP communication systems with large-scale antenna arrays, which is the fundamental issue of the systems.