Your browser does not support JavaScript!

Massive MIMO: survey and future research topics

Massive MIMO: survey and future research topics

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
IET Communications — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Massive multiple-input multiple-output technology has been considered a breakthrough in wireless communication systems. It consists of equipping a base station with a large number of antennas to serve many active users in the same time–frequency block. Among its underlying advantages is the possibility to focus transmitted signal energy into very short-range areas, which will provide huge improvements in terms of system capacity. However, while this new concept renders many interesting benefits, it brings up new challenges that have called the attention of both industry and academia: channel state information acquisition, channel feedback, instantaneous reciprocity, statistical reciprocity, architectures, and hardware impairments, just to mention a few. This paper presents an overview of the basic concepts of massive multiple-input multiple-output, with a focus on the challenges and opportunities, based on contemporary research.


    1. 1)
      • 32. Boche, H., Schubert, M.: ‘A general duality theory for uplink and downlink beamforming’. IEEE 56th in Vehicular Technology Conf. (VTC-Fall), 2002, vol. 1, pp. 8791.
    2. 2)
      • 52. Zheng, K., Ou, S., Yin, X.: ‘Massive MIMO channel models: a survey’, Int. J. Antennas Propag., 2014, 2014, Article ID 848071.
    3. 3)
    4. 4)
    5. 5)
      • 15. Guo, K., Guo, Y., Ascheid, G.: ‘On the performance of EVD-based channel estimations in MU-Massive-MIMO systems’. Proc. IEEE 24th Int. Symp. on Personal Indoor and Mobile Radio Communications, pp. 13761380.
    6. 6)
      • 9. Jo, M., Maksymyuk, T., Batista, R.L., et al: ‘A survey of converging solutions for heterogeneous mobile networks’, IEEE Wireless Communications, 2014, 21, (8), pp. 5462.
    7. 7)
      • 28. Araujo, D.C., de Almeida, A.L.F., Axnas, J., et al: ‘Channel estimation for millimeter-wave very-large MIMO systems’. Proc. the 22nd European Signal Processing Conf. (EUSIPCO), 2014, pp. 8185.
    8. 8)
    9. 9)
    10. 10)
    11. 11)
    12. 12)
    13. 13)
    14. 14)
    15. 15)
    16. 16)
      • 29. Ramasamy, D., Venkateswaran, S., Madhow, U.: ‘Compressive tracking with 1000-element arrays: A framework for multi-Gbps mm wave cellular downlinks’. Proc. 50th Annual Allerton Conf. on Communication, Control, and Computing, 2012, pp. 690697.
    17. 17)
      • 19. Hur, S., Kim, T., Love, D., et al: ‘Multilevel millimeter wave beamforming for wireless backhaul’. Proc. IEEEGLOBECOM Workshops, December 2011, pp. 253257.
    18. 18)
      • 22. Kouassi, B., Ghauri, I., Deneire, L.: ‘Reciprocity-based cognitive transmissions using a MU massive MIMO approach’. Proc. IEEE Int. Conf. on Communications (ICC'2013), 2013, pp. 27382742.
    19. 19)
    20. 20)
    21. 21)
      • 37. Studer, C., Durisi, G.: ‘Quantized massive MU-MIMO-OFDM uplink’, preprint, 2015. Available at
    22. 22)
      • 8. Liu, W., Han, S., Yang, C., et al: ‘Massive MIMO or small cell network: who is more energy efficient?’. Proc. IEEE Wireless Communications and Networking Conf. Workshops (WCNCW'2013), 2013, pp. 2429.
    23. 23)
    24. 24)
    25. 25)
    26. 26)
      • 20. Kaltenberger, F., Jiang, H., Guillaud, M., et al: ‘Relative channel reciprocity calibration in MIMO/TDD systems’. Proc. Future Network and Mobile Summit, 2010, pp. 110.
    27. 27)
    28. 28)
      • 14. Xu, P., Wang, J., Wang, J.: ‘Effect of pilot contamination on channel estimation in massive MIMO systems’. Proc. Int. Conf. on Wireless Communications Signal Processing (WCSP'2013), 2013, pp. 16.
    29. 29)
      • 46. Zhang, T.-C., Wen, C.-K., Jin, S., et al: ‘Mixed-ADC massive MIMO detectors: performance analysis and design optimization’. IEEE Transactions on Wireless Communications, available online:
    30. 30)
      • 25. Love, D., Choi, J., Bidigare, P.: ‘A closed-loop training approach for massive MIMO beamforming systems’. Proc. 47th Annual Conf. on Information Sciences and Systems (CISS'2013), 2013, pp. 15.
    31. 31)
      • 40. Risi, C., Persson, D., Larsson, E.G.: ‘Massive MIMO with 1-bit ADC’. Available at
    32. 32)
    33. 33)
      • 31. Godara, L.C.: ‘Handbook of antennas in wireless communications of electrical engineering & applied signal processing series’ (Taylor & Francis, 2014).
    34. 34)
    35. 35)
      • 50. Jeon, C., Ghods, R., Maleki, A., et al: ‘Optimality of large MIMO detection via approximate message passing’. IEEE Int. Symp. on Information Theory (ISIT), June 2015, pp. 12271231.
    36. 36)
      • 56. Jo, M., Maksymyuk, T., Strykhalyuk, B., et al: ‘Device-to-device (D2D) based heterogeneous radio access network architecture for mobile cloud computing’, IEEE Wirel. Commun., 2015, 12, (3), pp. 5462.
    37. 37)
      • 47. Fukuda, W., Abiko, T., Nishimura, T., et al: ‘Low-complexity detection based on belief propagation in a massive MIMO system’. IEEE 77th Vehicular Technology Conf. (VTC Spring), June 2013, pp. 15.
    38. 38)
    39. 39)
    40. 40)
      • 35. Obara, T., Suyama, S., Shen, J., et al: ‘Joint fixed beamforming and eigenmode precoding for super high bit rate massive MIMO systems using higher frequency bands’. Proc. IEEE 25th Annual Int. Symp. on Personal, Indoor, and Mobile Radio Communication (PIMRC'2014), 2014, pp. 607611.
    41. 41)
      • 7. Maksymyuk, T., Brych, M., Strykhalyuk, I., et al: ‘Fractal modeling for multi-tier heterogeneous networks with ultra-high capacity demands’, Smart Comput. Rev., 2015, 5, (4), pp. 346355.
    42. 42)
    43. 43)
    44. 44)
    45. 45)
    46. 46)
    47. 47)
    48. 48)
      • 48. Fukuda, W., Abiko, T., Nishimura, T., et al: ‘Complexity reduction for signal detection based on belief propagation in a massive MIMO system’. Int. Symp. on Intelligent Signal Processing and Communications Systems (ISPACS), November 2013, pp. 245250.
    49. 49)
      • 3. Ismail, M., Nordin, R.: ‘Fast networks as a candidate for LTE-advanced networks’, Smart Comput. Rev., 2013, 3, (2), pp. 7485.
    50. 50)
      • 54. Forenza, A., Heath, R.W.Jr., Perlman, S.G., et al: ‘System and method for distributed input distributed output wireless communications’. U.S. Patent No. 8,428,162, U.S. Patent and Trademark Office, Washington, DC, 2013.
    51. 51)
    52. 52)
    53. 53)
    54. 54)
      • 53. Gao, X., Tufvesson, F., Edfors, O., et al: ‘Measured propagation characteristics for very-large MIMO at 2.6 GHz’. Proc. 46th Asilomar Conf. on Signals, Systems and Computers (ASILOMAR), November 2012, pp. 295299.
    55. 55)
      • 41. Jacobsson, S., Durisi, G., Coldrey, M., et al: ‘One-bit massive MIMO: Channel estimation and high-order modulations’. Proc. IEEE Int. Conf. on Communications, June 2015.
    56. 56)
      • 21. Shepard, C., Yu, H., Anand, N., et al: ‘Argos: practical many-antenna base stations’. Proc. the ACM 18th Annual Int. Conf. on Mobile Computing and Networking in Mobicom'12, New York, NY, USA, 2012, pp. 5364.

Related content

This is a required field
Please enter a valid email address