Low-Complexity Robust Transmission Algorithm for IRS-Enhanced Cognitive Satellite-Aerial Networks

This paper proposes a downlink transmission scheme for intelligent reflecting surface (IRS) enhanced cognitive-satellite-aerial-network to support massive access of Internet-of-Things devices (IoTDs). By sharing the same frequency band with satellite network, the aerial network offers services for I...

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Veröffentlicht in:IEEE International Conference on Communications (2003) S. 6145 - 6150
Hauptverfasser: Zhao, Bai, Lin, Min, Xiao, Shengjie, Cheng, Ming, Wang, Jun-Bo, Cheng, Julian
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 28.05.2023
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ISSN:1938-1883
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Abstract This paper proposes a downlink transmission scheme for intelligent reflecting surface (IRS) enhanced cognitive-satellite-aerial-network to support massive access of Internet-of-Things devices (IoTDs). By sharing the same frequency band with satellite network, the aerial network offers services for IoTDs having line-of-sight links through space division multiple access, and for IoTDs locating in blocked area via IRS-enhanced non-orthogonal multiple access. Assuming that only the imperfect channel state information is available, we formulate a transmit power minimization problem subject to the probabilistic constraints of the quality-of-service requirements for IoTDs, the co-channel interference power limitation, and unit-modulus requirement for IRS. To tackle this mathematically intractable problem, we propose a generalized zero-forcing based low-complexity robust transmission algorithm, integrating the second-order Taylor expansion and Bernstein-type inequality, to obtain a satisfactory performance while reducing the computational load. Finally, simulation results validate the effectiveness and superiority of the proposed robust algorithms compared to existing algorithms.
AbstractList This paper proposes a downlink transmission scheme for intelligent reflecting surface (IRS) enhanced cognitive-satellite-aerial-network to support massive access of Internet-of-Things devices (IoTDs). By sharing the same frequency band with satellite network, the aerial network offers services for IoTDs having line-of-sight links through space division multiple access, and for IoTDs locating in blocked area via IRS-enhanced non-orthogonal multiple access. Assuming that only the imperfect channel state information is available, we formulate a transmit power minimization problem subject to the probabilistic constraints of the quality-of-service requirements for IoTDs, the co-channel interference power limitation, and unit-modulus requirement for IRS. To tackle this mathematically intractable problem, we propose a generalized zero-forcing based low-complexity robust transmission algorithm, integrating the second-order Taylor expansion and Bernstein-type inequality, to obtain a satisfactory performance while reducing the computational load. Finally, simulation results validate the effectiveness and superiority of the proposed robust algorithms compared to existing algorithms.
Author Zhao, Bai
Cheng, Ming
Xiao, Shengjie
Lin, Min
Wang, Jun-Bo
Cheng, Julian
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  givenname: Bai
  surname: Zhao
  fullname: Zhao, Bai
  organization: College of Communication and Information Engineering, Nanjing University of Posts and Telecommunications,Nanjing,China
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  givenname: Min
  surname: Lin
  fullname: Lin, Min
  organization: College of Communication and Information Engineering, Nanjing University of Posts and Telecommunications,Nanjing,China
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  givenname: Shengjie
  surname: Xiao
  fullname: Xiao, Shengjie
  organization: College of Communication and Information Engineering, Nanjing University of Posts and Telecommunications,Nanjing,China
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  givenname: Ming
  surname: Cheng
  fullname: Cheng, Ming
  organization: College of Communication and Information Engineering, Nanjing University of Posts and Telecommunications,Nanjing,China
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  givenname: Jun-Bo
  surname: Wang
  fullname: Wang, Jun-Bo
  organization: Southeast University,National Mobile Communications Research Laboratory,Nanjing,China
– sequence: 6
  givenname: Julian
  surname: Cheng
  fullname: Cheng, Julian
  organization: School of Engineering, University of British Columbia,Kelowna,Canada
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Snippet This paper proposes a downlink transmission scheme for intelligent reflecting surface (IRS) enhanced cognitive-satellite-aerial-network to support massive...
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StartPage 6145
SubjectTerms Cognitive-satellite-aerial-network
Intelligent reflecting surface
Low complexity algorithm
Minimization
NOMA
Non-orthogonal multiple access
Quality of service
Robust beam-forming
Satellites
Simulation
System performance
Taylor series
Title Low-Complexity Robust Transmission Algorithm for IRS-Enhanced Cognitive Satellite-Aerial Networks
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