Efficient space–frequency block coded pilot-aided channel estimation method for multiple-input–multiple-output orthogonal frequency division multiplexing systems over mobile frequency-selective fading channels

Fabien Delestre; Gbenga Owojaiye; Yichuang Sun

Efficient space–frequency block coded pilot-aided channel estimation method for multiple-input–multiple-output orthogonal frequency division multiplexing systems over mobile frequency-selective fading channels

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Author(s): Fabien Delestre ¹ ; Gbenga Owojaiye ¹ ; Yichuang Sun ¹
- Affiliations: 1: School of Engineering and Technology, University of Hertfordshire, Hatfield AL10 9AB, UK
Source: Volume 8, Issue 6, 17 April 2014, p. 841 – 851
DOI: 10.1049/iet-com.2013.0068 , Print ISSN 1751-8628, Online ISSN 1751-8636

Received 27/01/2013, Accepted 06/12/2013, Revised 26/11/2013, Published 26/02/2014

An iterative pilot-aided channel estimation technique for space–frequency block coded (SFBC) multiple-input multiple-output orthogonal frequency division multiplexing systems is proposed. Traditionally, when channel estimation techniques are utilised, the SFBC information signals are decoded one block at a time. In the proposed algorithm, multiple blocks of SFBC information signals are decoded simultaneously. The proposed channel estimation method can thus significantly reduce the amount of time required to decode information signals compared to similar channel estimation methods proposed in the literature. The proposed method is based on the maximum likelihood approach that offers linearity and simplicity of implementation. An expression for the pairwise error probability (PEP) is derived based on the estimated channel. The derived PEP is then used to determine the optimal power allocation for the pilot sequence. The performance of the proposed algorithm is demonstrated in high frequency selective channels, for different number of pilot symbols, using different modulation schemes. The algorithm is also tested under different levels of Doppler shift and for different number of transmit and receive antennas. The results show that the proposed scheme minimises the error margin between slow and high speed receivers compared to similar channel estimation methods in the literature.

References

1. 1)
  - 6. Uthansakul, M., Uthansakul, P.: ‘Experiments with a low-profile beamforming MIMO system for WLAN applications’, IEEE Antennas Propag. Mag., 2011, 53, pp. 56–69 (doi: 10.1109/MAP.2011.6157714).
2. 2)
  - 35. Gao, X., Jiang, B., You, X., Pan, Z., Xue, Y., Schulz, E.: ‘Efficient channel estimation for MIMO single-carrier block transmission with dual cyclic timeslot structure’, IEEE Trans. Commun., 2007, 55, pp. 2210–2223 (doi: 10.1109/TCOMM.2007.908551).
3. 3)
  - F.F. Gao , Y.H. Zeng , A. Nallanathan , T.S. Ng . Robust subspace blind channel estimation for cyclic prefixed MIMO OFDM systems: algorithm, identifiability and performance analysis. IEEE J. Sel. Areas Commun. , 2 , 378 - 388
4. 4)
  - 19. Hammarberg, P., Rusek, F., Edfors, O.: ‘Iterative receivers with channel estimation for multi-user MIMO-OFDM: complexity and performance’, EURASIP J. Wirel. Commun. Netw., 2012, 2012, p. 75 (doi: 10.1186/1687-1499-2012-75).
5. 5)
  - 32. Ahmed, K.I., Tepedelenlioglu, C., Spanias, A.: ‘On the performance of optimal training-based OFDM with channel estimation error’, IEEE Conf. Global Telecommun., 2004, 4, pp. 2404–2408.
6. 6)
  - 20. Minn, H., Kim, D.I., Bhargava, V.K.: ‘A reduced complexity channel estimation for OFDM systems with transmit diversity in mobile wireless channels’, IEEE Trans. Commun., 2002, 50, pp. 799–807 (doi: 10.1109/TCOMM.2002.1006561).
7. 7)
  - 29. ‘IEEE Standard for Local and metropolitan area networks Part 16: air interface for broadband wireless access systems’. IEEE Std 802.16-2009 (Revision of IEEE Std 802.16-2004), 2009, pp. C1–2004.
8. 8)
  - 4. IEEE Standard for Information Technology—Telecommunications and information exchange between systems–Local and metropolitan area networks–Specific requirements. Part 11: Wireless LAN medium access control (MAC) and physical layer (PHY) specifications amendment 5: enhancements for higher throughput’. IEEE Std 802.11n-2009 (Amendment to IEEE Std 802.11-2007 as amended by IEEE Std 802.11 k-2008, IEEE Std 802.11r-2008, IEEE Std 802.11y-2008, and IEEE Std 802.11w-2009), 2009, pp. C1–502.
9. 9)
  - 23. Jiang, M., Akhtman, J., Hanzo, L.: ‘Iterative joint channel estimation and multi-user detection for multiple-antenna aided OFDM systems’, IEEE Trans. Wirel. Commun., 2007, 6, pp. 2904–2914 (doi: 10.1109/TWC.2007.05817).
10. 10)
  - V. Tarokh , H. Jafarkhani , A.R. Calderbank . Space-time block coding for wireless communications: Performance results. IEEE J. Sel. Areas Commun. , 3 , 451 - 460
11. 11)
  - 9. Nee, R.V., Prasad, R.: OFDM for Wireless Multimedia Communications, 2000.
12. 12)
  - 15. Hsiao-Yun, C., Meng-Lin, K., Shyh-Jye, J., Chia-Chi, H.: ‘A robust channel estimator for high-mobility STBC-OFDM systems’, IEEE Trans. Circuits Syst. I: Reg. Pap., 2010, 57, pp. 925–936 (doi: 10.1109/TCSI.2009.2027629).
13. 13)
  - M.F. Rabbi , S. Hou , C.C. Ko . High mobility OFDMA channel estimation using basis expansion model. IET Commun. , 353 - 367
14. 14)
  - 18. Rossi, S., Müller, R., Edfors, O.: ‘Linear MMSE estimation of time-frequency variant channels for MIMO-OFDM systems’, Elsevier Signal Process., 2011, 91, pp. 1157–1167 (doi: 10.1016/j.sigpro.2010.10.017).
15. 15)
  - 34. Ku, M., Huang, C.: ‘A refined channel estimation method for STBC/OFDM systems in high-mobility wireless channels’, IEEE Trans. Wirel. Commun., 2008, 7, pp. 4312–4320 (doi: 10.1109/T-WC.2008.070585).
16. 16)
  - 30. Ahmed, K.I., Tepedelenlioglu, C., Spanias, A.: ‘Optimal training and performance analysis of space–time–frequency coded OFDM’. IEEE Int. Conf. Communications, 2006, vol. 7, pp. 2929–2934.
17. 17)
  - 27. Noble, B., Daniel, J.W.: ‘Applied linear algebra’ (Prentice-Hall International, 1988).
18. 18)
  - 25. Won-Gyu, S., Jong-Tae, L.: ‘Channel estimation and signal detection for MIMO-OFDM with time varying channels’, IEEE Commun. Lett., 2006, 10, pp. 540–542.
19. 19)
  - 12. Dogan, H., Cirpan, H.A., Panayirci, E.: ‘Iterative channel estimation and decoding of turbo coded SFBC-OFDM systems’, IEEE Trans. Wirel. Commun., 2007, 6, pp. 3090–3101 (doi: 10.1109/TWC.2007.06006).
20. 20)
  - 24. Lu, S., Narasimhan, B., Al-Dhahir, N.: ‘A novel SFBC-OFDM scheme for doubly selective channels’, IEEE Trans. Veh. Technol., 2009, 58, (5), pp. 2573–2578 (doi: 10.1109/TVT.2008.2006271).
21. 21)
  - 17. Deneire, L., Vandenameele, P., van der Perre, L., Gyselinckx, B., Engels, M.: ‘A low complexity ML channel estimator for OFDM’. IEEE Int. Conf. Communications, 2001, vol. 5, pp. 1461–1465.
22. 22)
  - S.M. Alamouti . A simple transmitter diversity scheme for wireless communications. IEEE J. Sel. Areas Commun. , 8 , 1451 - 1458
23. 23)
  - 11. Chih-Peng, L., Sen-Hung, W., Kuei-Cheng, C.: ‘Low complexity transmitter architectures for SFBC MIMO-OFDM systems’, IEEE Trans. Commun., 2012, 60, pp. 1712–1718 (doi: 10.1109/TCOMM.2012.041212.100613).
24. 24)
  - Y. Li , N. Seshadri , S. Arivavisitakul . Channel estimation for OFDM systems with transmitter diversity in mobile wireless channels. IEEE J. Sel. Areas Commun. , 461 - 471
25. 25)
  - 1. Oborina, A., Moisio, M., Koivunen, V.: ‘Performance of mobile MIMO OFDM systems with application to UTRAN LTE downlink’, IEEE Trans. Wirel. Commun., 2012, 11, pp. 2696–2706.
26. 26)
  - W. Zhang , X.G. Xia , K. Ben Letaief . Space-time/frequency coding for MIMO-OFDM in next generation broadband wireless systems. IEEE Wirel. Commun. , 32 - 43
27. 27)
  - P. Garg , R.K. Mallik , H.M. Gupta . Exact error performance of square orthogonal space–time block coding with channel estimation. IEEE Trans. Commun. , 3 , 430 - 437
28. 28)
  - 10. Jung, Y., Kim, J., Lee, S., Yoon, H., Kim, J.: ‘Design and implementation of MIMO-OFDM baseband processor for high-speed wireless LANs’, IEEE Trans. Circuits Syst. II: Express Briefs, 2007, 54, pp. 631–635 (doi: 10.1109/TCSII.2007.895330).
29. 29)
  - 33. Torabi, M., Aissa, S., Soleymani, M.R.: ‘On the BER performance of space-frequency block coded OFDM systems in fading MIMO channels’, IEEE Trans. Wirel. Commun., 2007, 6, pp. 1366–1373 (doi: 10.1109/TWC.2007.348333).
30. 30)
  - 21. Liu, T., Wang, M., Liang, Y., Shu, F., Wang, J., Sheng, W., Chen, Q.: ‘A minimum-complexity high-performance channel estimator for MIMO-OFDM communications’, IEEE Trans. Veh. Technol., 2010, 59, pp. 4634–4639 (doi: 10.1109/TVT.2010.2081694).
31. 31)
  - 16. Muruganathan, S.D., Sesay, A.B.: ‘A low-complexity decision-directed channel-estimation scheme for OFDM systems with space–frequency diversity in doubly selective fading channels’, IEEE Trans. Veh. Technol., 2009, 58, pp. 4277–4291 (doi: 10.1109/TVT.2009.2021600).
32. 32)
  - 22. Pena-Campos, F., Carrasco-Alvare, R., Longoria-Gandara, O., Parra-Michel, R.: ‘Estimation of fast time-varying channels in OFDM systems using two-dimensional prolate’, IEEE Trans. Wirel. Commun., 2013, 12, pp. 898–907 (doi: 10.1109/TWC.2013.010413.120624).
33. 33)
  - 7. Yuejie, C., Gomaa, A., Al-Dhahir, N., Calderbank, A.R.: ‘Training signal design and tradeoffs for spectrally-efficient multi-user MIMO-OFDM systems’, IEEE Trans. Wirel. Commun., 2011, 10, pp. 2234–2245 (doi: 10.1109/TWC.2011.042211.101100).
34. 34)
  - 2. Wu, Z., Gao, G.: ‘Improved MIMO-OFDM scheme for the next generation WLAN’, IEEE J. Syst. Eng. Electron., 2013, 24, pp. 52–59.
35. 35)
  - 5. Diggavi, S.N., Al-Dhahir, N., Stamoulis, A., Calderbank, A.R.: ‘Great expectations: the value of spatial diversity in wireless networks’, Proc. IEEE, 2004, 92, pp. 219–270 (doi: 10.1109/JPROC.2003.821914).

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Efficient space–frequency block coded pilot-aided channel estimation method for multiple-input–multiple-output orthogonal frequency division multiplexing systems over mobile frequency-selective fading channels

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