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Author:

Mir, Talha (Mir, Talha.) | Waqas, Muhammad (Waqas, Muhammad.) | Tu, Shanshan (Tu, Shanshan.) | Fang, Chao (Fang, Chao.) | Ni, Wei (Ni, Wei.) | MacKenzie, Richard (MacKenzie, Richard.) | Xue, Xuan (Xue, Xuan.) | Han, Zhu (Han, Zhu.)

Indexed by:

EI Scopus SCIE

Abstract:

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.

Keyword:

Massive MIMO Matching pursuit algorithms Autonomous aerial vehicles Optimization massive MIMO Millimeter-wave relay hybrid precoding Precoding unmanned aerial vehicle Relays Complexity theory

Author Community:

  • [ 1 ] [Mir, Talha]Balochistan Univ Informat Technol, Fac Informat & Commun, Dept Elect Engn, Quetta 87300, Pakistan
  • [ 2 ] [Waqas, Muhammad]Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
  • [ 3 ] [Fang, Chao]Beijing Univ Technol, Fac Informat Technol, Beijing 100124, Peoples R China
  • [ 4 ] [Waqas, Muhammad]Univ Bahrain, Coll Informat Technol, Dept Comp Engn, Zallaq 32038, Bahrain
  • [ 5 ] [Waqas, Muhammad]Edith Cowan Univ, Sch Engn, Perth, WA 6027, Australia
  • [ 6 ] [Tu, Shanshan]Beijing Univ Technol, Fac Informat Technol, Engn Res Ctr Intelligent Percept & Autonomous Con, Beijing 100124, Peoples R China
  • [ 7 ] [Fang, Chao]Purple Mt Lab Networking Commun & Secur, Nanjing 211189, Peoples R China
  • [ 8 ] [Ni, Wei]CSIRO, Data61, Marsfield, NSW 2122, Australia
  • [ 9 ] [MacKenzie, Richard]British Telecommun Technol, Adastral Pk, Ipswich IP5 3RE, Suffolk, England
  • [ 10 ] [Xue, Xuan]Xidian Univ, State Key Lab Integrated Serv Networks, Xian 710071, Peoples R China
  • [ 11 ] [Han, Zhu]Univ Houston, Dept Elect & Comp Engn, Houston, TX 77004 USA

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Source :

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS

ISSN: 1536-1276

Year: 2022

Issue: 9

Volume: 21

Page: 7040-7054

1 0 . 4

JCR@2022

1 0 . 4 0 0

JCR@2022

ESI Discipline: COMPUTER SCIENCE;

ESI HC Threshold:46

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count: 11

SCOPUS Cited Count: 15

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 8

Affiliated Colleges:

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