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Multi-band Strategy for Cooperative Communication Networking with Unmatched Carrier Frequencies

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Abstract

In this paper, we consider the cooperative networking with the presence of multiple carrier frequency offsets at different relays, which is difficult to be handled. Such an imperfect networking is inevitable due to the distributed nature of the relay system and unmatched central frequencies at different relays. We propose a multi-band scheme for cooperative communications and provide theoretical analysis of the proposed cooperative networking based on the analytical upper bound of the channel orthogonality deficiency. Theoretical analysis and simulation results show that the proposed scheme achieves the full cooperative diversity and improves the system capacity, only adopting linear equalizers such as zero-forcing and minimum mean square error equalizers. Such advatange is normlly only enjoyed by a non-linear equalizers like maximum-likelihood equalizer, whose huge complexity is however usually unacceptable.

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Notes

  1. If the channel matrix of the MIMO users is an \(m\) by \(n\hbox { matrix }{\mathbb H}\), Full rank means that the minimum number of independent rows and column of \({\mathbb H}\), i.e., \(\hbox {rank}\left( {\mathbb H} \right) =\min \left( {m,n} \right) \).

  2. The threshold is \({\left( {\hbox {2}^{B}-1} \right) }/{h_{S,Q_r } }\); where \(B\) is the target rate and \(h_{S,Q_r } \) denotes the power gain from source to relay \(Q_r \).

  3. A QR decomposition (also called a QR factorization) of a matrix is a decomposition of a matrix A into a product A = QR of an orthogonal matrix Q and an upper triangular matrix R.

  4. \(O\left( \cdot \right) \), the Landau notation describes the limiting behavior of a function when the argument tends towards a particular value or infinity, usually in terms of simpler functions.

References

  1. Liu, K. J. R., Sadek, A. K., Su, W., & Kwasinski, A. (2009). Cooperative communications and networks. Cambridge: Cambridge University Press.

    Google Scholar 

  2. Nosratinia, A., Hunter, T. E., & Hedayat, A. (2004). Cooperative communication in wireless networks. IEEE Communications Magazine, 42, 74–80.

    Article  Google Scholar 

  3. Cover, T. M., & El Gamal, A. A. (1979). Capacity theorems for the relay channel. IEEE Transactions on Information Theory, IT–25, 572–584.

    Article  MathSciNet  Google Scholar 

  4. Kramer, G., Gastpar, M., & Gupta, P. (2005). Cooperative strategies and capacity theorems for relay networks. IEEE Transactions on Information Theory, 51, 3037–3063.

    Article  MATH  MathSciNet  Google Scholar 

  5. Laneman, J. N., Tse, D. N. C., & Wornell, G. W. (2004). Cooperative diversity in wireless networks: Efficient protocols and outage behavior. IEEE Transactions on Information Theory, 50(12), 3062–3080.

    Article  MATH  MathSciNet  Google Scholar 

  6. Sendonaris, A., Erkip, E., & Aazhang, B. (2003). User cooperation diversity—Part I: System description. IEEE Transactions on Communications, 51(11), 1927–1938.

    Article  Google Scholar 

  7. Sendonaris, A., Erkip, E., & Aazhang, B. (2003). User cooperation diversity—Part II: Implementation aspects and performance analysis. IEEE Transactions on Communications, 51(11), 1939–1948.

    Article  Google Scholar 

  8. Letaief, K. B., & Zhang, W. (2009). Cooperative communications for cognitive radio networks. Proceedings of IEEE, 97, 878–893.

    Article  Google Scholar 

  9. Oyman, O., Laneman, J. N., & Sandhu, S. (2007). Multihop relaying for broadband wireless mesh networks: From theory to practice. IEEE Communications Magazine, 45, 116–122.

    Article  Google Scholar 

  10. Salim, O., Nasir, A., Xiang, W., & Kennedy, R. (2014). Joint channel, phase noise, and carrier frequency offset estimation in cooperative OFDM systems. In Proceedings of the IEEE ICC’14, Sydney, Australia.

  11. Batra, A. (2004). Design of a multiband OFDM system for realistic UWB channel environments. IEEE Transactions on Microwave Theory and Techniques, 52, 2123–2138.

    Article  Google Scholar 

  12. Batra, A. (Sept. 2004). Multi-band OFDM physical layer proposal for IEEE 802.15Task Group 3a IEEE P802.15-04/0493r1.

  13. Standard ECMA-368 high rate ultra wideband PHY and MAC Standard, 3rd ed., Dec. 2008.

  14. Hassibi, B., & Vikalo, H. (2005). On the sphere-decoding algorithm I. Expected complexity. IEEE Transactions on Signal Processing, 53(8), 2806–2818.

    Article  MathSciNet  Google Scholar 

  15. Giannakis, G. B., Liu, Z., Ma, X., & Zhou, S. (2007). Space-time coding for broadband wireless communications. New York: Wiley.

    Google Scholar 

  16. Su, W., Safar, Z., & Liu, K. J. R. (2005). Towards maximum achievable diversity in space, time, and frequency: Performance analysis and code design. IEEE Transactions on Wireless Communications, 4(4), 1847–1857.

    Article  Google Scholar 

  17. Su, W., Safar, Z., & Liu, K. J. R. (2005). Full-rate full-diversity space-frequency codes with optimum coding advantage. IEEE Transactions on Information Theory, 51(1), 229–249.

    Article  MATH  MathSciNet  Google Scholar 

  18. Zhang, W., & Letaief, K. B. (2007). Space-time/frequency coding for MIMO-OFDM in next generation broadband wireless systems. IEEE Wireless Communications Magazine, 14(3), 32–43.

    Article  Google Scholar 

  19. Ma, X., & Giannakis, G. B. (2005). Space-time-multipath coding using digital phase sweeping or block circular delay diversity. IEEE Transactions on Signal Processing, 53(3), 1121–1131.

    Article  MathSciNet  Google Scholar 

  20. Fang, K., & Leus, G. (2010). Space-time block coding for doubly-selective channels. IEEE Transactions on Signal Processing, 58(3), 1934–1940.

    Article  MathSciNet  Google Scholar 

  21. Ma, X., & Zhang, W. (2008). Fundamental limits of linear equalizers: Diversity, capacity, and complexity. IEEE Transactions on Information Theory, 54(8), 3442–3456.

    Article  MATH  Google Scholar 

  22. Zhang, W., Ma, X., Gestner, B., & Anderson, D. V. (2009). Designing low-complexity equalizers for wireless systems. IEEE Communications Magazine, 47(1), 56–64.

    Article  Google Scholar 

  23. Lu, H., Nikookar, H., & Lian, X. (2010). Performance evaluation of hybrid DF-AF OFDM cooperation in Rayleigh channel. In Proceedings of the wireless technology conference (EuWIT).

  24. Sanna, M., & Murroni, M. (2011). Optimization of non-convex multiband cooperative sensing with genetic algorithms. IEEE Selected Topics in Signal Processing, 5(1), 87–96.

    Article  Google Scholar 

  25. Song, Z., Zhou, Z., Sun, X., & Qin, Z. (2010). Cooperative spectrum sensing for multiband under noise uncertainty in cognitive radio networks. In Proceedings of the IEEE ICC’10, South Africa .

  26. Lu, H., Xu, T., & Nikookar, H. (2010). Performance analysis of the STFC for cooperative ZP-OFDM diversity, capacity and complexity. In Proceedings of the WPMC’10, 11–14 Oct. 2011, Recife, Brazil.

  27. Zhang, J.K., Liu, J., & Wong, K.M. (Sept. 2005). Linear Toeplitz space time block codes. In Proceedings of the IEEE ISIT’05, Adelaide, Australia.

  28. Shang, Y., & Xia, X. G. (2008). On space-time block codes achieving full diversity with linear receivers. IEEE Transactions on Information Theory, 54, 4528–4547.

    Article  MathSciNet  Google Scholar 

  29. Wang, H., Xia, X. G., & Yin, Q. (2009). Distributed space-frequency codes for cooperative communication system with multiple carrier frequency offsets. IEEE Transactions on Wireless Communication, 8, 1045–1055.

    Article  Google Scholar 

  30. Avestimehr, A. S., & Tse, D. N. C. (2007). Outage capacity of the fading relay channel in the low-SNR regime. IEEE Transactions on Information Theory, 53(4), 1401–1415.

    Article  MathSciNet  Google Scholar 

  31. Telatar, I. E. (1999). Capacity of multi-antenna Gaussian channels. European Transactions on Telecommunications, 10(6), 585–595.

    Article  Google Scholar 

  32. Pammer, V., Delignon, Y., Sawaya, W., & Boulinguez, D. (2003). A low complexity suboptimal MIMO receiver: The combined ZF-MLD algorithm. In Proceedings of the personal, indoor and mobile radio communications (Vol. 3, pp, 2271–2275), Beijing, China.

  33. Windpassinger, C., Lampe, L., Fischer, R. F. H., & Hehn, T. (2006). A performance study of MIMO detectors. IEEE Transactions on Wireless Communications, 5(8), 2004–2008.

    Article  Google Scholar 

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Acknowledgments

This work is performed in part at Tianjin 712 Communication & Broadcasting Corp under the University–Enterprise Joint Postdoctoral program between Tsinghua University and Tianjin Zhonghuan Electronic & Information (Group) Co., Ltd. and supported in part by National Natural Science Foundation of China (NSFC, Project 61302140).

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Correspondence to Tao Xu.

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Guan, Y., Xu, T., Ding, W. et al. Multi-band Strategy for Cooperative Communication Networking with Unmatched Carrier Frequencies. Wireless Pers Commun 80, 1159–1173 (2015). https://doi.org/10.1007/s11277-014-2078-3

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