Relay Hybrid Precoding in UAV-Assisted Wideband Millimeter-Wave Massive MIMO System

Millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) offers a promising technique to fulfil the high data demand and connectivity of the Internet-of-Things (IoT) and 5G communications because it owns valuable and unknown spectrum resources. Using massive antennas with recently intr...

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Bibliographic Details
Published in:IEEE transactions on wireless communications 2022-09, Vol.21 (9), p.7040-7054
Main Authors: Mir, Talha, Waqas, Muhammad, Tu, Shanshan, Fang, Chao, Ni, Wei, MacKenzie, Richard, Xue, Xuan, Han, Zhu
Format: Article
Language:English
Subjects:
Algorithms
Autonomous aerial vehicles
Complexity
Complexity theory
Drone aircraft
Drone vehicles
Energy consumption
Internet of Things
Massive MIMO
Matching pursuit algorithms
Millimeter waves
Millimeter-wave
MIMO communication
Optimization
Polynomials
Precoding
relay hybrid precoding
Relays
unmanned aerial vehicle
Unmanned aerial vehicles
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Summary:Millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) offers a promising technique to fulfil the high data demand and connectivity of the Internet-of-Things (IoT) and 5G communications because it owns valuable and unknown spectrum resources. Using massive antennas with recently introduced drone-enabled aerial computing platforms, named unmanned aerial vehicles (UAVs), can cast high energy consumption if fully-digital precoding is employed at the UAVs. Using hybrid precoding at a UAV can reduce hardware complexity and energy consumption but is challenging with a need for joint optimization of three precoding matrices at the UAV (sixth-order polynomial objective function). In this paper, we propose to decompose the original UAV hybrid precoding challenge into three subproblems and develop a coordinated descent optimization (CDO) algorithm to solve the three problems recursively. In addition, the convergence and complexity of this new technique are analyzed. Numerical studies indicate the improved effectiveness of the proposed solution over existing solutions.
ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2022.3154290