Deep double-pilot-based hybrid precoding in UAV-enabled mmWave massive MIMO

Ziyao Hong,Fei Li,Ting Li

doi:10.1186/s13638-020-01854-7

Abstract

Unmanned aerial vehicle (UAV)-enabled communication system provides flexibility and reliability compared to conventional ones. Millimeter wave (mmWave) and massive multiple-input–multiple-output (MIMO) have widely been researched since recent years, which are promising techniques for the next and even the later generation communication system. Hybrid precoding, as a method to reduce the high cost in hardware and power brought by massive antenna array, develops fiercely and is often combined to deep learning, a kind of popular optimization tool, which brings an overwhelming performance. On the other hand, there are not so many attentions about the hybrid precoding in time-varying mmWave massive MIMO, which is necessary to be considered in a UAV-enabled communication scenario because the performance will degrade seriously if the channel changed while the transmitter and receiver use the precoding matrix corresponding to the expired channel, yet. In this paper, we propose a double-pilot-based hybrid precoding system, which completes analog precoding and digital precoding separately—predicting the previous one using deep learning structure and updating equivalent channel frequently for the post one by enhancing the frequency of equivalent channel estimation.

Highlights

With the development of remote controlling technique and the emergence of demand in wireless communications, Unmanned aerial vehicle (UAV) is considered to play an important role in and beyond next-generation communication system, which brings the possibility of broadband seamless connectivity and flexibility of deployment equipped with multiple antennas and working in millimeter wave band [1]
We propose a double-pilot-based time-varying hybrid precoding system based on the analysis that analog precoding and digital precoding vary in different speeds and the size of them is totally distinct, which determines the separate methods for them
We present the achievable rate of beamforming index prediction net (BIP-Net) with the research of the influence of time relevance length L in the network

Summary

Introduction

With the development of remote controlling technique and the emergence of demand in wireless communications, UAV is considered to play an important role in and beyond next-generation communication system, which brings the possibility of broadband seamless connectivity and flexibility of deployment equipped with multiple antennas and working in millimeter wave band [1]. References [2, 3] summarize three primary kinds of UAV-aided wireless communications, i.e., UAV-aided ubiquitous coverage, UAV-aided relaying, and UAV-aided information dissemination and data collection. The second one is typically used in areas where there are large blocks like mountains or something else to shadow wireless signal significantly, which degrades the performance of mmWave-based communication system [4]. UAVs are used to exchange data with a large number of distributed UEs or sensors, in which time delay can be tolerated on a certain level

Methods

Results

Conclusion