Pilot contamination reduction can improve the achievable uplink and downlink rates in a multicell massive multiple-input–multiple-output system. To this end, this study first proposes two schemes to mitigate the effect of pilot contamination by implementing uplink training with time-aligned and time-shifted pilot transmissions. Accordingly, these techniques enable the system not only to exploit the advantages of time-shifted training but also to benefit from the use of conventional systems that improve the achievable rates. The authors introduce channel estimation in matrix form by estimating from a near minimum mean square error method. Furthermore, linear detector and precoding methods are used for a base station with a finite number of antennas in order to derive the closed-form lower bounds of the achievable rates with two uplink training schemes for both uplink and downlink transmissions. Finally, numerical results are presented to verify the analysis.

References

1. 1)
  - 18. Kay, S.M.: ‘Fundamentals of statistical signal processing: estimation theory’ (Prentice Hall, Upper Saddle River, NJ USA, 1993).
2. 2)
  - 14. Ngo, H.Q., Larsson, E., Marzetta, T.: ‘Massive MU-MIMO downlink TDD systems with linear precoding and downlink pilots’. Proc. Allerton Conf. Communications, Control & Computing (Allerton), Monticello, IL, USA, October 2013, pp. 293–298.
3. 3)
  - 9. Appaiah, K., Ashikhmin, A., Marzetta, T.: ‘Pilot contamination reduction in multi-user TDD systems’. Proc. IEEE International Conf. Communications (ICC), Cape Town, South Africa, May 2010, pp. 1–5.
4. 4)
  - 3. Rusek, F., Persson, D.: ‘Scaling up MIMO: opportunities and challenges with very large arrays’, IEEE Signal Process. Mag., 2013, 30, (1), pp. 40–60 (doi: 10.1109/MSP.2011.2178495).
5. 5)
  - 34. Jose, J., Ashikhmin, A., Marzetta, T.L., et al: ‘Pilot contamination and precoding in multi-cell TDD systems’, IEEE Trans. Wirel. Commun., 2011, 10, (8), pp. 2640–2651 (doi: 10.1109/TWC.2011.060711.101155).
6. 6)
  - 13. Vu, T., Vu, T.A., Quek, T.Q.S.: ‘Successive pilot contamination elimination in multiantenna multicell networks’, IEEE Wirel. Commun. Lett., 2014, 3, (6), pp. 617–620 (doi: 10.1109/LWC.2014.2361518).
7. 7)
  - 19. Meyer, C.D.: ‘Matrix analysis and applied linear algebra’ (Society for Industrial and Applied Mathematics, Philadelphia, PA USA, 2000).
8. 8)
  - 11. Mahyiddin, W., Martin, P., Smith, P.: ‘Performance of synchronized and unsynchronized pilots in finite massive MIMO systems’, IEEE Trans. Wirel. Commun., 2015, 14, (12), pp. 6763–6776 (doi: 10.1109/TWC.2015.2459702).
9. 9)
  - 10. Fernandes, F., Ashikhmin, A., Marzetta, T.L.: ‘Inter-cell interference in noncooperative TDD large scale antenna systems’, IEEE J. Sel. Areas Commun., 2013, 31, (2), pp. 192–201 (doi: 10.1109/JSAC.2013.130208).
10. 10)
  - 3. Lu, L., Li, G.Y., Swindlehurst, A.L., et al: ‘An overview of massive MIMO: benefits and challenges’, IEEE J. Sel. Topics Signal Process., 2014, 8, (5), pp. 742–758 (doi: 10.1109/JSTSP.2014.2317671).
11. 11)
  - 3. Choi, J., Love, D., Bidigare, P.: ‘Downlink training techniques for FDD massive MIMO systems: open-loop and closed-loop training with memory’, IEEE J. Sel. Top. Signal Process., 2014, 8, (5), pp. 802–814 (doi: 10.1109/JSTSP.2014.2313020).
12. 12)
  - 4. Ngo, H.Q., Larsson, D., Marzetta, T.: ‘Energy and spectral efficiency of very large multiuser MIMO systems’, IEEE Trans. Commun., 2013, 61, (4), pp. 1436–1449 (doi: 10.1109/TCOMM.2013.020413.110848).
13. 13)
  - 12. Nguyen, V.-D., Nguyen, H.V., Shin, O.-S.: ‘Channel estimation based on time-shifted pilots in multicell massive MIMO systems’. Proc. International Conf. Computing, Management & Telecommunications (ComManTel), Danang, Vietnam, December 2015, pp. 1–5.
14. 14)
  - 10. Mahyiddin, W., Martin, P., Smith, P.: ‘Pilot contamination reduction using time-shifted pilots in finite massive MIMO systems’. Proc. IEEE Vehicular Technology Conf. (VTC) Fall, Vancouver, Canada, September 2014, pp. 1–5.
15. 15)
  - 17. Kammoun, A., Muller, A., Bjornson, E., et al: ‘Low-complexity linear precoding for multi-cell massive MIMO systems’. Proc. European Signal Processing Conf. (EUSIPCO), Lisbon, Portugal, September 2014, pp. 2150–2154.
16. 16)
  - 1. Larsson, E., Edfors, O., Tufvesson, F., et al: ‘Massive MIMO for next generation wireless systems’, IEEE Commun. Mag., 2014, 52, (2), pp. 186–195 (doi: 10.1109/MCOM.2014.6736761).
17. 17)
  - 7. Nguyen, T.M., Le, L.B.: ‘Joint pilot assignment and resource allocation in multicell massive MIMO network: throughput and energy efficiency maximization’. Proc. IEEE Wireless Communications & Network Conf. (WCNC), New Orleans, LA, USA, March 2015, pp. 393–398.
18. 18)
  - 6. Bogale, T.E., Le, L.B.: ‘Pilot optimization and channel estimation for multiuser massive MIMO systems’. Proc. Conf. Information Sciences & Systems (CISS), Princeton, NJ, USA, March 2014, pp. 1–6.
19. 19)
  - 16. Park, J., Clerckx, B.: ‘Multi-user linear precoding for multi-polarized massive MIMO system under imperfect CSIT’, IEEE Trans. Wirel. Commun., 2015, 14, (5), pp. 2532–2547 (doi: 10.1109/TWC.2014.2388207).

Uplink training for multicell massive multiple-input–multiple-output systems: a combination of time-shifted and time-aligned pilot approaches

References

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