Turn off MathJax
Article Contents
ZHANG Lei, WANG Yu, SHANG Yulong, et al., “Robust Beamforming Design for IRS-Aided Cognitive Radio Networks with Bounded CSI Errors,” Chinese Journal of Electronics, in press, doi: 10.23919/cje.2021.00.254, 2022.
Citation: ZHANG Lei, WANG Yu, SHANG Yulong, et al., “Robust Beamforming Design for IRS-Aided Cognitive Radio Networks with Bounded CSI Errors,” Chinese Journal of Electronics, in press, doi: 10.23919/cje.2021.00.254, 2022.

Robust Beamforming Design for IRS-Aided Cognitive Radio Networks with Bounded CSI Errors

doi: 10.23919/cje.2021.00.254
Funds:  This work is supported by the Open Research Fund of National Mobile Communications Research Laboratory, Southeast University, (No.2021D14), National Natural Science Foundation of China (No.61901196), Future Network Scientific Research Fund Project (No.FNSRFP-2021-YB-35), Changzhou Sci&Tech Program (No.CJ20210070), Natural Science Foundation of the Higher Education Institutions of Jiangsu Province (No.21KJB510029)
More Information
  • Author Bio:

    was born in Zhecheng, Henan province. He received the Ph.D. degree in information and communication engineering from Southeast University, Nanjing, China, in 2016. He has been a Visiting Scholar with Queen Mary University of London, U.K. from 2019 to 2020. He is currently an Associate Professor with the School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou, China. His research interests include cognitive radio and intelligent reflecting surface. (Email: zhlei@jsut.edu.cn)

    (corresponding author) was born in Pingshun, Shanxi province. She received her Ph.D degree in the School of Information Science and Engineering from Southeast University, Nanjing, China, in 2017. She is currently an Associate Professor with the School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou, China. Her research interests lie in the areas of vehicular networks, intelligent reflecting surface, and dynamic spectrum access. She has published several technical papers in journal such as IEEE TVT and conferences such as ICC and GLOBECOM. (Email: yuwang edina@jsut.edu.cn)

    received his B.E. degree in communication engineering from PLA Information Engineering University, Zhengzhou, China, in 2010, and his M.E. degree and Ph.D. in electronic computer engineering from Chonnam National University, Gwangju, Korea in 2014 and 2018, respectively. Since 2018, he lectured at the School of Electrical and Information Engineering at Jiangsu University of Technology, Changzhou, China. His recent research interests include wireless communication, MIMO, digital broadcasting systems and deep learning

    received his Ph.D. degree in electrical and electronic engineering from the University of Auckland, New Zealand, in 2018. He is currently a lecturer with the School of Electrical and Information Engineering at Jiangsu University of Technology, China. His research interests lie in the areas of broadband communication systems, energy efficient cooperative systems in wireless sensor networks and intelligent reflecting surface

    received the B.E. degree from Nanjing University of Posts and Telecommunications, China in 2004, and the M.E. and Dr.Eng. degrees from Shinshu University, Japan in 2007 and 2010, respectively. Since 2011, he has been with Jiangsu University of Technology, China, first as a Lecturer and since 2013 as an Associate Professor. His current research interests include wireless sensor network, cellular networks, wireless ad hoc network, MIMO, OFDM, SC-FDMA, etc

  • Available Online: 2022-07-16
  • In this paper, intelligent reflecting surface (IRS) is introduced to enhance the performance of cognitive radio (CR) systems. The robust beamforming is designed based on combined bounded channel state information (CSI) error for primary user (PU) related channels. The transmit precoding at the secondary user (SU) transmitter and phase shifts at the IRS are jointly optimized to minimize the SU's total transmit power subject to the quality of service of SUs, the limited interference imposed on the PU and unit-modulus of the reflective beamforming. Simulation results verify the efficiency of the proposed algorithm and reveal that the number of phase shifts at IRS should be carefully chosen to obtain a tradeoff between the total minimum transmit power and the feasibility rate of the optimization problem.

  • loading
  • [1]
    C.H. Pan, H. Ren, K.Z. Wang, W. Xu, M. Elkashlan, A. Nallanathan and L. Hanzo, “Multicell MIMO communications relying on intelligent reflecting surfaces,” IEEE Transactions on Wireless Communications, vol.19, no.8, pp.5218–5233, 2020. doi: 10.1109/TWC.2020.2990766
    [2]
    C.H. Pan, H. Ren, K.Z. Wang, W. Xu, M. Elkashlan, A. Nallanathan, J.Z. Wang and L. Hanzo, “Intelligent reflecting surface aided MIMO broadcasting for simultaneous wireless information and power transfer,” IEEE Journal on Selected Areas in Communications, vol.38, no.8, pp.1719–1734, 2020. doi: 10.1109/JSAC.2020.3000802
    [3]
    G. Zhou, C.H. Pan, H. Ren, K.Z. Wang and A. Nallanathan, “Intelligent reflecting surface aided multigroup multicast MISO communication systems,” IEEE Transactions on Signal Processing, vol.68, pp.3236–3251, 2020. doi: 10.1109/TSP.2020.2990098
    [4]
    Y. Han, W. Tang, S. Jin, C. Wen and X. Ma, “Large intelligent surface-assisted wireless communication exploiting statistical CSI,” IEEE Transactions on Vehicular Technology, vol.68, no.8, pp.8238–8242, 2019. doi: 10.1109/TVT.2019.2923997
    [5]
    J. Chen, Y.C. Liang, Y. Pei and H. Guo, “Intelligent reflecting surface: A programmable wireless environment for physical layer security,” IEEE Access, vol.7, pp.82599–82612, 2019. doi: 10.1109/ACCESS.2019.2924034
    [6]
    H. Shen, W. Xu, S. Gong, Z. He and C. Zhao, “Secrecy rate maximization for intelligent reflecting surface assisted multi-antenna communications,” IEEE Communications Letters, vol.23, no.9, pp.1488–1492, 2019. doi: 10.1109/LCOMM.2019.2924214
    [7]
    X.H. Yu, D.F. Xu and R. Schober, “Enabling secure wireless communications via intelligent reflecting surfaces”, IEEE Global Communications Conference (GLOBECOM), Waikoloa, HI, USA, pp.1–9, 2019.
    [8]
    G. Zhou, C.H. Pan, H. Ren, K.Z. Wang, M.D. Renzo and A. Nallanathan, “Robust beamforming design for intelligent reflecting surface aided MISO communication systems,” IEEE Wireless Communications Letters, vol.9, no.10, pp.1658–1622, 2020. doi: 10.1109/LWC.2020.3000490
    [9]
    X.M. Hong, J. Wang, C.X. Wang and J.H. Shi, “Cognitive radio in 5G: a perspective on energy-spectral efficiency trade-off,” IEEE Communications Magazine, vol.52, no.7, pp.46–53, 2014. doi: 10.1109/MCOM.2014.6852082
    [10]
    H. Al-Hraishawi and G.A.A. Baduge, “Wireless energy harvesting in cognitive massive MIMO systems with underlay spectrum sharing,” IEEE Wireless Communications Letters, vol.6, no.1, pp.134–137, 2017.
    [11]
    D. Hamza, P. Ki-Hong, M.S. Alouini and S. Aissa, “Throughput maximization for cognitive radio networks using active cooperation and superposition coding,” IEEE Transactions on Wireless Communications, vol.14, no.6, pp.3322–3336, 2015. doi: 10.1109/TWC.2015.2403852
    [12]
    Q. Zhao, S. Geirhofer, L. Tong and B.M. Sadler, “Opportunistic spectrum access via periodic channel sensing,” IEEE Transactions on Signal Processing, vol.56, no.2, pp.785–796, 2008. doi: 10.1109/TSP.2007.907867
    [13]
    L. Zhang, Y. Wang, W.G. Tao, Z.Y. Jia, T.C. Song and C.H. Pan, “Intelligent reflecting surface aided MIMO cognitive radio systems,” IEEE Transactions on Vehicular Technology, vol.20, no.10, pp.11445–11457, 2020.
    [14]
    A.U. Makarfi, R. Kharel, K.M. Rabie, O. Kaiwartya, X. Li and D.T. Do, “Reconfigurable intelligent surfaces based cognitive radio networks”, IEEE Wireless Communications and Networking Conference Workshop (WCNCW), Nanjing, Jiangsu, China, pp.1–6, 2021.
    [15]
    J.L. He, K.Q. Yu, Y. Zhou, Y.M. Shi, “Reconfigurable intelligent surface enhanced cognitive radio networks”, IEEE 92nd Vehicular Technology Conference (VTC2020-Fall), Victoria, BC, Canada, pp.1–5, 2020.
    [16]
    F. Zhou, Z. Li, J. Cheng, Q. Li and J. Si, “Robust AN-aided beamforming and power splitting design for secure MISO cognitive radio with SWIPT,” IEEE Transactions on Wireless Communications, vol.16, no.4, pp.2450–2464, 2017. doi: 10.1109/TWC.2017.2665465
    [17]
    B. Li, Z. Fei, Z. Chu, F. Zhou, K. -K. Wong and P. Xiao, “Robust chance-constrained secure transmission for cognitive satellite-terrestrial networks,” IEEE Transactions on Vehicular Technology, vol.67, no.5, pp.4208–4219, 2018. doi: 10.1109/TVT.2018.2791859
    [18]
    G. Zheng, S. Ma, K. Wong and T. Ng, “Robust beamforming in cognitive radio,” IEEE Transactions on Wireless Communications, vol.9, no.2, pp.570–576, 2010. doi: 10.1109/TWC.2010.5403537
    [19]
    D.F. Xu, X.H. Yu, Y. Sun, D.W.K. Ng and R. Schober, “Resource allocation for IRS-assisted full-duplex cognitive radio systems,” IEEE Transactions on Communications, vol.68, no.12, pp.7376–7394, 2020. doi: 10.1109/TCOMM.2020.3020838
    [20]
    J. Yuan, Y.C. Liang, J. Joung, G. Feng and E.G. Larsson, “Intelligent reflecting surface-assisted cognitive radio system,” IEEE Transactions on Communications, vol.69, no.1, pp.675–687, 2021. doi: 10.1109/TCOMM.2020.3033006
    [21]
    L. Zhang, Y.C. Liang, Y. Xin and H.V. Poor, “Robust cognitive beamforming with partial channel state information,” IEEE Transactions on Wireless Communications, vol.8, no.8, pp.4143–4153, 2009. doi: 10.1109/TWC.2009.080698
    [22]
    G. Zheng, S. Ma, K. Wong and T. Ng, “Robust cognitive beamforming in cognitive radio,” IEEE Transactions on Wireless Communications, vol.9, no.2, pp.570–576, 2010. doi: 10.1109/TWC.2010.5403537
    [23]
    H. Du and T. Ratnarajah, “Robust utility maximization and admission control for a MIMO cognitive radio network,” IEEE Transactions on Vehicular Technology, vol.62, no.4, pp.1707–1718, 2013. doi: 10.1109/TVT.2012.2231103
    [24]
    G. Zhou, C.H. Pan, H. Ren, K.Z. Wang and A. Nallanathan, “A framework of robust transmission design for IRS-aided MISO communications with imperfect cascaded channels,” IEEE Transactions on Signal Processing, vol.68, pp.5092–5106, 2020. doi: 10.1109/TSP.2020.3019666
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(7)

    Article Metrics

    Article views (423) PDF downloads(40) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return