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Decentralized transceiver optimization for multi-relay aided multiuser MIMO networks

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Abstract

In this paper, the decentralized transceivers and corresponding channel state information (CSI) signaling concepts are proposed for weighted sum rate (WSR) maximization, via linear downlink transceiver optimization in multi-relay aided multiuser multiple-input multiple-output (MIMO) networks. Three decentralized algorithms are proposed with the local CSI requirements at the base station (BS) and the relay nodes. In the first proposed algorithm, the generalized channel inversion precoding is used at the BS to avoid the second hop channel sharing requirements among the relay nodes, and decentralized transceiver optimization of the relay nodes and users are developed to maximize the WSR. A minimum mean square error (MMSE)-based enhanced method is proposed as well. To further improve the performance, we provide a novel structure of the precoding matrix of the BS. The decentralized joint BS, relay and user transceiver optimization problem is formulated and solved. Also, the CSI signaling and decentralized processing in the time division duplex (TDD) system are analyzed. Simulation results show the effectiveness of the decentralized transceiver design compared to the existing algorithms.

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References

  1. Tang X, Hua Y. Optimal design of non-regenerative MIMO wireless relays. IEEE Trans Wirel Commun, 2007, 6: 1398–1407

    Article  Google Scholar 

  2. Rong Y, Tang X, Hua Y. A unified framework for optimizing linear nonregenerative multicarrier MIMO relay communication systems. IEEE Trans Signal Process, 2009, 57: 4837–4851

    Article  MathSciNet  Google Scholar 

  3. YU J, Liu D, Yin C, et al. Relay-assisted MIMO multiuser precoding in fixed relay networks. In: Proceedings of International Conference on Wireless Communications, Networking and Mobile Computing, Shanghai, 2007. 881–884

    Google Scholar 

  4. Li G, Wang Y, Wu T, et al. Joint linear filter design in multi-user non-regenerative MIMO-relay systems. In: Proceedings of IEEE International Conference on Communications, Dresden, 2009. 1–6

    Google Scholar 

  5. Jang S, Yang J, Kim D K. Minimum MSE design for multiuser MIMO relay. IEEE Commun Lett, 2010, 14: 812–814

    Article  Google Scholar 

  6. Liu J, Qiu Z. Robust sum-MSE transceiver optimisation for multi-user non-regenerative MIMO relay downlink systems. Electron Lett, 2011, 47: 411–412

    Article  Google Scholar 

  7. Xing C, Ma S, Xia M, et al. Cooperative beamforming for dual-hop amplify-and-forward multi-antenna relaying cellular networks. Signal Process, 2012, 92: 2689–2699

    Article  Google Scholar 

  8. Wang H, Chen W. Joint source and relay design for multiuser MIMO nonregenerative relay networks With direct links. IEEE Trans Veh Technol, 2012, 61: 2871–2876

    Article  Google Scholar 

  9. Li C, Iwanami Y. Comparative study of transmit weight designs for nonregenerative Multiuser MIMO downlink relay system. In: 6th International Conference on Signal Processing and Communication Systems. Piscataway: IEEE, 2012. 1–6

    Google Scholar 

  10. Shi H, Abe T, Asai T, et al. Relaying schemes using matrix triangularization for MIMO wireless networks. IEEE Trans Commun, 2007, 55: 1683–1688

    Article  Google Scholar 

  11. Oyman O, Paulraj A J. Design and analysis of linear distributed MIMO relaying algorithms. IEEE Proc Commun, 2006, 153: 565–572

    Article  Google Scholar 

  12. Rong Y, Xiang Y. Multiuser multi-hop MIMO relay systems with correlated fading channels. IEEE Trans Wirel Commun, 2011, 10: 2835–2840

    Article  Google Scholar 

  13. Lzi Y A, Falahati A. Amplify-forward relaying for multiple-antenna multiple relay networks under individual power constraint at each relay. EURASIP J Wirel Commun Network, 2012, 1: 1–10

    Article  Google Scholar 

  14. Ma S, Xing C, Fan Y, et al. Iterative transceiver design for MIMO AF relay networks with multiple sources. In: Procedings of IEEE Military Communications Conference, San Jose, 2010. 369–374

    Google Scholar 

  15. Xing C, Ma S, Fei Z, et al. How to understand linear minimum mean square error transceiver design for multiple input multiple output systems from quadratic matrix programming. IET Commun, 2013, 7: 1231–1242

    Article  Google Scholar 

  16. Chalise B K, Zhang Y D, Amin M G. Successive convex approximation for system performance optimization in a multiuser network with multiple MIMO relays. In: Proceedings of 4th IEEE International Computational Advances in Multi-Sensor Adaptive Processing Workshop, San Juan, 2011. 229-232

  17. Truong K T, Heath R W. Interference alignment for the multiple-antenna amplify-and-forward relay interference channel. In: Proceedings of 45th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, 2011. 1288–1292

    Google Scholar 

  18. Cho Y M, Jang S, Kim D K, et al. Minimum sum-MSE design for distributed multi-relay aided multi-user MIMO network. In: Proceedings of IEEE 54th International Midwest Symposium on Circuits and Systems, Seoul, 2011. 1–4

    Google Scholar 

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

    Book  MATH  Google Scholar 

  20. Christensen S S, Agarwal R, Carvalho E, et al. Weighted sum-rate maximization using weighted MMSE for MIMO-BC beamforming design. IEEE Trans Wirel Commun, 2008, 7: 4792–4799

    Article  Google Scholar 

  21. Lee K J, Sung H, Park E, et al. Joint optimization for one and two-way MIMO AF multiple-relay systems. IEEE Trans Wirel Commun, 2010, 9: 3671–3681

    Article  Google Scholar 

  22. Shin J, Moon J. Weighted sum rate maximizing transceiver design in MIMO interference channel. In: Proceedings of IEEE Global Telecommunications Conference, Huston, 2011. 1–5

    Google Scholar 

  23. Sung H, Lee S R, Lee I. Generalized channel inversion methods for multiuser MIMO systems. IEEE Trans Commun, 2009, 57: 3489–3499

    Article  Google Scholar 

  24. Shen H, Li B, Tao M, et al. MSE-based transceiver designs for the MIMO interference channel. IEEE Trans Wirel Commun, 2010, 9: 3480–3489

    Article  Google Scholar 

  25. Zhang Z, Zhang W, Tellambura C. MIMO-OFDM channel estimation in the presence of frequency offsets. IEEE Trans Wirel Commun, 2008, 7: 2329–2339

    Article  Google Scholar 

  26. Zhang Z, 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 

  27. Zhang Z, Zhang W, Tellambura C. OFDM uplink frequency offset estimation via cooperative relaying. IEEE Trans Wirel Commun, 2009, 8: 4450–4456

    Article  Google Scholar 

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Authors and Affiliations

  1. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, China

    Qi Sun & LiHua Li

  2. China Unicom Research Institute, Beijing, 100032, China

    JunLing Mao

Authors
  1. Qi Sun
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  2. LiHua Li
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  3. JunLing Mao
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Correspondence to LiHua Li.

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Sun, Q., Li, L. & Mao, J. Decentralized transceiver optimization for multi-relay aided multiuser MIMO networks. Sci. China Inf. Sci. 57, 1–13 (2014). https://doi.org/10.1007/s11432-014-5088-6

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  • DOI: https://doi.org/10.1007/s11432-014-5088-6

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