Skip to main content Accessibility help
×
Hostname: page-component-7c8c6479df-ph5wq Total loading time: 0 Render date: 2024-03-19T10:46:44.889Z Has data issue: false hasContentIssue false

8 - Distributed Massive MIMO in Cellular Networks

from Part II - Physical Layer Communication Techniques

Published online by Cambridge University Press:  28 April 2017

Michail Matthaiou
Affiliation:
Queen's University Belfast, United Kingdom
Shi Jin
Affiliation:
Southeast University, China
Vincent W. S. Wong
Affiliation:
University of British Columbia, Vancouver
Robert Schober
Affiliation:
Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
Derrick Wing Kwan Ng
Affiliation:
University of New South Wales, Sydney
Li-Chun Wang
Affiliation:
National Chiao Tung University, Taiwan
Get access

Summary

Introduction

Wireless communications, together with its underlying applications, is among today's most active areas of technology development, with the demand for data rates expected to grow to unprecedented levels by 2020. Cisco's latest report predicts a monthly mobile traffic of 24.3 exabytes (260 bytes) in 2019, which represents a 57% compound annual growth rate compared with 2014 [1]. The catalyst for this seminal development is 5G, the fifth generation of wireless systems, which denotes the next major phase of mobile telecommunications standards beyond the current fourth generation (4G) International Mobile Telecommunications-Advanced (IMT-Advanced) standards and promises speeds far beyond what the current 4G can offer. This represents a radically new paradigm in the field of wireless communications and promises to substantially improve the area spectral efficiency (measured in bit/s/Hz/km2) and energy efficiency (EE) (measured in bit/J). According to [2], there are three symbiotic technologies that can support the required “data-rate boom”:

  1. 1. extreme densification and offloading to serve more active nodes per unit area and Hz, also known as massive multiple-input multiple-output (MIMO);

  2. 2. increased bandwidth, primarily by moving toward and into the millimeter wave spectrum (from 30 to 300 GHz);

  3. 3. increased spectral efficiency, primarily through advances in MIMO, to support more bits/s/Hz per node.

In this chapter, we will elaborate exclusively on item 1 above, namely massive MIMO, which represents a disruptive technological paradigm and is considered by many experts as the “next big thing in wireless” [3, 4]. We will first delineate the basic principles behind the operation of massive MIMO and then review some of its applications. Finally, we will conclude this chapter by presenting some directions for future work along with open challenges in the general field of massive MIMO. Table 8.1 lists the nomenclature used in this chapter.

Massive MIMO: Basic Principles

The massive MIMO technology originates from the seminal paper of Marzetta [5], and since then has been at the forefront of wireless communications research, with numerous papers reported in the literature along with huge industrial investments. Generally speaking, in a massive MIMO topology, a number K of user terminals (UTs) communicate simultaneously with a base station (BS) over the same time–frequency resources.

Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2017

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

[1] Cisco, “Cisco visual networking index: Global mobile data traffic forecast update, 2014–2019,” White paper.
[2] J. G., Andrews, S., Buzzi, W., Choi, S. V., Hanly, A., Lozano, A. C. K., Soong, and J. C., Zhang “What will 5G be?” IEEE J. Sel. Areas Commun., vol. 32, no. 6, pp. 1065–1082, Jun. 2014.Google Scholar
[3] A. L., Swindlehurst, E., Ayanoglu, P., Heydari, and F., Capolino, “Millimeter-wave massive MIMO: The next wireless revolution?” IEEE Commun. Mag., vol. 52, no. 9, pp. 56–62, Sep. 2014.Google Scholar
[4] M., Matthaiou, G. K., Karagiannidis, E. G., Larsson, T. L., Marzetta, and R., Schober, “Guest editorial: Large-scale multiple antenna wireless systems,” IEEE J. Sel. Areas Commun., vol. 31, no. 2, pp. 113–116, Feb. 2013.Google Scholar
[5] T. L., Marzetta, “Noncooperative cellular wireless with unlimited numbers of base station antennas,” IEEE Trans. Wireless Commun., vol. 9, no. 11, pp. 3590–3600, Nov. 2010.Google Scholar
[6] F., Rusek, D., Persson, B. K., Lau, E. G., Larsson, T. L., Marzetta, O., Edfors, and F., Tufvesson, “Scaling up MIMO: Opportunities and challenges with very large arrays,” IEEE Signal Process. Mag., vol. 30, pp. 40–60, Jan. 2013.Google Scholar
[7] E. G., Larsson, O., Edfors, F., Tufvesson, and T. L., Marzetta, “Massive MIMO for next generation wireless systems,” IEEE Commun. Mag., vol. 52, pp. 186–195, Feb. 2014.Google Scholar
[8] M., Matthaiou, C., Zhong, M. R., McKay, and T., Ratnarajah, “Sum rate analysis of ZF receivers in distributed MIMO systems,” IEEE J. Sel. Areas Commun., vol. 31, no. 2, pp. 180–191, Feb. 2013.Google Scholar
[9] H. Q., Ngo, E. G., Larsson, and T. L., Marzetta, “Aspects of favorable propagation in massive MIMO,” in Proc. of European Signal Processing Conf. (EUSIPCO), Sep. 2014.
[10] T. L., Marzetta and B. M., Hochwald, “Capacity of a mobile multiple-antenna communication link in Rayleigh flat fading,” IEEE Trans. Inf. Theory, vol. 45, no. 1, pp. 139–157, Jan. 1999.Google Scholar
[11] H. Q., Ngo, E. G., Larsson, and T. L., Marzetta, “Energy and spectral efficiency of very large multiuser MIMO systems,” IEEE Trans. Commun., vol. 61, no. 4, pp. 1436–1449, Apr. 2013.Google Scholar
[12] P. A., Dighe, R. K., Mallik, and S. S., Jamuar, “Analysis of transmit–receive diversity in Rayleigh fading,” IEEE Trans. Commun., vol. 51, no. 4, pp. 694–703, Apr. 2003.Google Scholar
[13] H. Q., Ngo, M., Matthaiou, and E. G., Larsson, “Massive MIMO with optimal power and training duration allocation,” IEEE Wireless Commun. Lett., vol. 3, no. 6, pp. 606–608, Dec. 2014.Google Scholar
[14] M., Matthaiou, C., Zhong, and T., Ratnarajah, “Novel generic bounds on the sum rate of MIMO ZF receivers,” IEEE Trans. Signal Process., vol. 59, no. 9, pp. 4341–4353, Sep. 2011.Google Scholar
[15] M. R., McKay, I. B., Collings, and A. M., Tulino, “Achievable sum rate of MIMO MMSE receivers: A general analytic framework,” IEEE Trans. Inf. Theory, vol. 56, no. 1, pp 396–410, Jan. 2010.Google Scholar
[16] T., Guess and M. K., Varanasi, “An information-theoretic framework for deriving canonical decision-feedback receivers in Gaussian channels,” IEEE Trans. Inf. Theory, vol. 51, no. 1, pp. 173–187, Jan. 2005.Google Scholar
[17] B., Hassibi and B. M., Hochwald, “How much training is needed in multiple-antenna wireless links?” IEEE Trans. Inf. Theory, vol. 49, no. 4, pp. 951–963, Apr. 2003.Google Scholar
[18] J., Hoydis, S., ten Brink, and M., Debbah, “Comparison of linear precoding schemes for downlink massive MIMO,” in Proc. of IEEE International Conf. on Communications (ICC), Jun. 2012.
[19] H. Q., Ngo, “Massive MIMO: Fundamentals and system designs,” Ph.D. dissertation, Department of Electronic Engineering, Linköping University, Linköping, Sweden, 2015.
[20] J., Jose, A., Ashikhmin, T. L., Marzetta, and S., Vishwanath, “Pilot contamination and precoding in multi-cell TDD systems,” IEEE Trans. Wireless Commun., vol. 10, no. 8, pp. 2640–2651, Aug. 2011.Google Scholar
[21] H. Q., Ngo and E. G., Larsson, “Blind estimation of effective downlink channel gains in massive MIMO,” in Proc. of IEEE International Conf. on Acoustics, Speech, and Signal Processing (ICASSP), Apr. 2015.
[22] H. Q., Ngo, H. A., Suraweera, M., Matthaiou, and E. G., Larsson, “Multipair full-duplex relaying with massive arrays and linear processing,” IEEE J. Sel. Areas Commun., vol. 32, no. 9, pp. 1721–1737, Oct. 2014.Google Scholar
[23] F., Yuan, S., Jin, Y., Huang, K.-K., Wong, Q. T., Zhang, and H., Zhu, “Joint wireless information and energy transfer in massive distributed antenna systems,” IEEE Commun. Mag., vol. 53, no. 6, pp. 109–116, Jun. 2015.Google Scholar
[24] J., Choi, D. J., Love, and P., Bidigare, “Downlink training techniques for FDD massive MIMO systems: Open-loop and closed-loop training with memory,” IEEE J. Sel. Top. Signal Process., vol. 8, no. 5, pp. 802–814, Mar. 2014.Google Scholar
[25] J., Nam, A., Adhikary, J. Y., Ahn, and G., Caire, “Joint spatial division and multiplexing: Opportunistic beamforming, user grouping and simplified downlink scheduling,” IEEE J. Sel. Top. Signal Process., vol. 8, no. 5, pp. 876–890, Mar. 2014.Google Scholar
[26] C., Sun, X., Gao, S., Jin, M., Matthaiou, Z., Ding, and C., Xiao, “Beam division multiple access transmission for massive MIMO communications,” IEEE Trans. Commun., vol. 63, no. 6, pp. 2170–2184, Jun. 2015.Google Scholar
[27] C., Masouros and M., Matthaiou, “Space-constrained massive MIMO: Hitting the wall of favorable propagation,” IEEE Commun. Lett., vol. 19, no. 5, pp. 771–774, May. 2015.Google Scholar
[28] X., Gao, O., Edfors, F., Rusek, and F., Tufvesson, “Massive MIMO performance evaluation based on measured propagation data,” IEEE Trans. Wireless Commun., vol. 14, no. 7, pp. 3899–3911, Jul. 2015.Google Scholar
[29] C. H., Doan, S., Emami, D. A., Sobel, A. M., Niknejad, and R. W., Brodersen, “Design considerations for 60 GHz CMOS radios,” IEEE Commun. Mag., vol. 42, no. 12, pp. 132–140, Dec. 2004.Google Scholar
[30] S., Hur, T., Kim, D. J., Love, J. V., Krogmeier, T. A., Thomas, and A., Ghosh, “Millimeter wave beamforming for wireless backhaul and access in small cell networks,” IEEE Trans. Commun., vol. 61, no. 10, pp. 4391–4403, Oct. 2013.Google Scholar
[31] O. E., Ayach, S., Rajagopal, S., Abu-Surra, Z., Pi, and R. W., Heath, Jr., “Spatially sparse precoding in millimeter wave MIMO systems,” IEEE Trans. Wireless Commun., vol. 13, no. 3, pp. 1499–1513, Mar. 2014.Google Scholar
[32] T. E., Bogale and L. B., Le, “Beamforming for multiuser massive MIMO systems: Digital versus hybrid analog–digital,” in Proc. of IEEE Global Communications Conf. (GLOBECOM), Dec. 2014.

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×