Robust capacity maximization transceiver design for MIMO OFDM systems



In this paper, we investigated capacity maximization problem for Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing systems with imperfect channel state information (CSI). To the best of our knowledge, the considered problem is still an open problem. However, the transceiver designs for MIMO OFDM systems have been extensively studied. It seems nobody gives closed-form solutions for resource allocation for MIMO OFDM systems with statistical channel estimation errors up to date. In our work, based on practical channel estimation algorithm, the channel estimation errors are first derived and then the robust resource allocation problem has been formulated. The structure of the optimal robust precoder is first derived, based on which the optimization problem will be simplified significantly. Furthermore, based on the Lagrangian dual method, a robust power allocation algorithm is proposed. The proposed power allocation can be considered as a variant of water-filling solution named cluster water-filling solution. Finally, simulation results show that our proposed robust design outperforms the non-robust design in terms of channel capacity.



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  1. 1

    Larsson E G, Stoica P. Space-Time Block Coding for Wireless Communications. Cambridge: Cambridge University Press, 2003

    Book  MATH  Google Scholar 

  2. 2

    Tse D, Viswanath P. Fundamentals of Wireless Communication. Cambridge: Cambridge University Press. 2005

    Book  MATH  Google Scholar 

  3. 3

    Bolcskei H, Gesbert D, Papadias C B, et al. Space-Time Wireless Systems: From Array Processing to MIMO Communications. Cambridge: Cambridge University Press. 2006

    Book  MATH  Google Scholar 

  4. 4

    Luan T X, Gao F F, Zhang X D. Joint resource scheduling for relay-assisted broadband cognitive radio networks. IEEE Trans Wirel Commun, 2012, 11: 3090–3100

    Article  Google Scholar 

  5. 5

    Zhu F C, Gao F F, Yao M L, et al. Joint information-and Jamming-beamforming for physical layer security with full duplex base station. IEEE Trans Signal Process, 2014, 62: 6391–6401

    MathSciNet  Article  Google Scholar 

  6. 6

    Zhang Z S, Long K P, Wang J P, et al. On swarm intelligence inspired self-organized networking: its bionic mechanisms, designing principles and optimization approaches. IEEE Commun Surv Tut, 2014, 16: 513–537

    Article  Google Scholar 

  7. 7

    Zhang Z S, Long K P, Wang J P. Self-organization paradigms and optimization approaches for cognitive radio technologies: a survey. IEEE Trans Wirel Commun, 2013, 20: 36–42

    Article  Google Scholar 

  8. 8

    Dietrich F A. Robust Signal Processing for Wireless Communications. Foundations in Signal Processing, Communications and Networking. Berlin: Springer Press, 2007

    Google Scholar 

  9. 9

    Zheng G, Wong K-K, Paulraj A, et al. Robust collaborative-relay beamforming. IEEE Trans Signal Process, 2009, 57: 3130–3143

    MathSciNet  Article  Google Scholar 

  10. 10

    Sampath H, Stoica P, Paulraj A. Generalized linear precoder and decoder design for MIMO channels using the weighted MMSE criterion. IEEE Trans Commun, 2001, 49: 2198–2206

    Article  Google Scholar 

  11. 11

    Palomar D P, Cioffi J M, Lagunas M A. Joint Tx-Rx beamforming design for multicarrier MIMO channels: a unified framework for convex optimization. IEEE Trans Signal Process, 2003, 51: 2381–2399

    Article  Google Scholar 

  12. 12

    Joham M, Utschick W, Nossek J A. Linear transmit processing in MIMO communications systems. IEEE Trans Signal Process, 2005, 53: 2700–2712

    MathSciNet  Article  Google Scholar 

  13. 13

    Serbetli S, Yener A. Transceiver optimization for mutiuser MIMO systems. IEEE Trans Signal Process, 2004, 52: 214–226

    MathSciNet  Article  MATH  Google Scholar 

  14. 14

    Zhang X, Palomar D P, Ottersten B. Statistically robust design of linear MIMO transceivers. IEEE Trans Signal Process, 2008, 56: 3678–3689

    MathSciNet  Article  Google Scholar 

  15. 15

    Ding M H, Blostein S D. MIMO minimum total MSE transceiver design with imperfect CSI at both ends. IEEE Trans Signal Process, 2009, 57: 1141–1150

    MathSciNet  Article  Google Scholar 

  16. 16

    Xing C W, Ma S D, Wu Y C, et al. Transceiver design for dual-hop nonregenerative MIMO-OFDM relay systems under channel uncertainties. IEEE Trans Signal Process, 2010, 58: 6325–6339

    MathSciNet  Article  Google Scholar 

  17. 17

    Xing C W, Fei Z S, Ma S D. Maximum mutual information design for amplify-and-forward multi-hop MIMO relaying systems under channel uncertainties. In: Wireless Communications and Networking Conference (WCNC), Paris, 2012. 781–786

    Google Scholar 

  18. 18

    Xing C W, Ma S D, Fei Z S. A general robust linear transceiver design for multi-hop amplify-and-forward MIMO relaying systems. IEEE Trans Signal Process, 2013, 61: 1196–1209

    MathSciNet  Article  Google Scholar 

  19. 19

    Rey F, Lamarca M, Vazquez G. Robust power allocation algorithms for MIMO OFDM systems with imperfect CSI. IEEE Trans Signal Process, 2005, 53: 1070–1085

    MathSciNet  Article  Google Scholar 

  20. 20

    Xing C W, Li D, Ma S D. Robust transceiver design for MIMO-OFDM systems based on cluster water-filling. IEEE Commun Lett, 2013, 17: 1451–1454

    Article  Google Scholar 

  21. 21

    Zhang Z S, Zhang W, Tellambura C. Cooperative OFDM channel estimation in the presence of frequency offsets. IEEE Trans Veh Technol, 2009, 58: 3447–3459

    Article  Google Scholar 

  22. 22

    Kay S M. Fundamentals of Statistical Signal Processing: Estimation Theory. Upper Saddle River: Prentice Hall PTR, 1993

    Google Scholar 

  23. 23

    Yuen C, Hochwald B M. Achieving near-capacity at low SNR on a multiple-antenna multiple-user channel. IEEE Trans Commun, 2009, 57: 69–74

    Article  Google Scholar 

  24. 24

    Bertsekas D P, Nedic A, Ozdaglar A E. Convex Analysis and Optimization. Nashua: Athena Scientific, 2003

    MATH  Google Scholar 

  25. 25

    Conejo A J, Castillo E, Mínguez R, et al. Decomposition Techniques in Mathematical Programming. Berlin: Springer, 2006

    MATH  Google Scholar 

  26. 26

    Bertsekas D P. Constrained Optimization and Lagrange Multiplier Methods. Nashua: Athena Scientific, 1996

    MATH  Google Scholar 

  27. 27

    Boyd S, Vandenberghe L. Convex Optimization. Cambridge: Cambridge University Press, 2004

    Book  MATH  Google Scholar 

  28. 28

    Bertsekas D P. Nonlinear Programming. Nashua: Athena Scientific, 1999

    MATH  Google Scholar 

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Correspondence to Chengwen Xing.

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Guo, S., Xing, C., Fei, Z. et al. Robust capacity maximization transceiver design for MIMO OFDM systems. Sci. China Inf. Sci. 59, 062301 (2016).

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  • capacity maximization
  • water-filling
  • channel uncertainty
  • robust design


  • 多天线正交频分复用
  • 容量最大化
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  • 信道不确定性
  • 鲁棒性设计