A pilot allocation method for multi-cell multi-user massive MIMO system

doi:10.23919/JSEE.2021.000033

Journal of Systems Engineering and Electronics ›› 2021, Vol. 32 ›› Issue (2): 399-407.doi: 10.23919/JSEE.2021.000033

• ELECTRONICS TECHNOLOGY • Previous Articles Next Articles

A pilot allocation method for multi-cell multi-user massive MIMO system

Yiming LI¹(), Liping DU^1,^2,*(), Yueyun CHEN¹()

¹ School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China
² Wireless and Space Communication Laboratory, Shunde Graduate School of University of Science and Technology Beijing, Foshan 528000, China

Received:2020-02-13 Online:2021-04-29 Published:2021-04-29
Contact: Liping DU E-mail:liyiming95111@126.com;Dlp2001@ies.ustb.edu.cn;chenyy@ustb.edu.cn
About author:|LI Yiming was born in 1995. He is currently pursuing his master’s degree in the information and communication engineering from the School of Computer and Communication Engineering, University of Science and Technology Beijing (USTB). His research interest is wireless communication. E-mail: liyiming95111@126.com||DU Liping was born in 1975. She is a professor in the School of Computer and Communication Engineering, University of Science and Technology Beijing (USTB) and Shunde Graduate School of USTB. Her research interests are wireless communication, signal processing and pattern recognition. E-mail: Dlp2001@ies.ustb.edu.cn||CHEN Yueyun was born in 1966. She is a professor in the School of Computer and Communication Engineering, University of Science and Technology Beijing (USTB). She is an IEEE member. Her research interests are wireless mobile communication system theory, broadband wireless communication technology and wireless resource management. E-mail: chenyy@ustb.edu.cn
Supported by:
This work was supported by the Scientific and Technological Innovation Foundation of Shunde Graduate School, USTB (BK19CF002);This work was supported by the Scientific and Technological Innovation Foundation of Shunde Graduate School, USTB (BK19CF002)

Abstract

Abstract:

Pilot contamination can spoil the accuracy of channel estimation and then has become one of the key problems influencing the performance of massive multiple input multiple output (MIMO) systems. This paper proposes a method based on cell classification and users grouping to mitigate the pilot contamination in multi-cell massive MIMO systems and improve the spectral efficiency. The pilots of the terminals are allocated one-bit orthogonal identifier to diminish the cell categories by the operation of exclusive OR (XOR). At the same time, the users are divided into edge user groups and central user groups according to the large-scale fading coefficients by the clustering algorithm, and different pilot sequences are assigned to different groups. The simulation results show that the proposed method can effectively improve the spectral efficiency of multi-cell massive MIMO systems.

Key words: massive multiple input multiple output (MIMO), pilot allocation, cell classification, users grouping (UG), spectral efficiency

Yiming LI, Liping DU, Yueyun CHEN. A pilot allocation method for multi-cell multi-user massive MIMO system[J]. Journal of Systems Engineering and Electronics, 2021, 32(2): 399-407.

Figures/Tables 10

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References 36

1	ASAAD S, RABIEI A M, MULLER R R Massive MIMO with antenna selection: fundamental limits and applications. IEEE Trans. on Wireless Communications, 2018, 17 (12): 8502- 8516. doi: 10.1109/TWC.2018.2877992
2	MARZETTA T L Noncooperative cellular wireless with unlimited numbers of base station antennas. IEEE Trans. on Wireless Communications, 2010, 9 (11): 3590- 3600. doi: 10.1109/TWC.2010.092810.091092
3	BJORNSON E, WYMEERSCH H, SANGUINETTI L, et al Massive MIMO is a reality? What is next? Five promising research directions for antenna arrays. Digital Signal Processing, 2019, 94 (1): 3- 20.
4	CHIH-LIN I, HAN S, XU Z, et al 5G: rethink mobile communications for 2020+. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2016, 374 (2062): 20140432. doi: 10.1098/rsta.2014.0432
5	LARSSON E G, EDFORS O, TUFVESSON F, et al Massive MIMO for next generation wireless systems. IEEE Communications Magazine, 2013, 52 (2): 186- 195.
6	TAN W J, FENG X A, LIU G Y, et al Spectral efficiency of massive MIMO systems with multiple sub-arrays antenna. IEEE Access, 2018, 6, 31213- 31223. doi: 10.1109/ACCESS.2018.2845666
7	KAMGA G N, XIA M H, AISSA S, et al Spectral-efficiency analysis of massive MIMO systems in centralized and distributed schemes. IEEE Trans. on Communications, 2016, 64 (5): 1930- 1941. doi: 10.1109/TCOMM.2016.2519513
8	NGO H Q, LARSSON E G, MARZETTA T L Energy and spectral efficiency of very large multiuser MIMO systems. IEEE Trans. on Communications, 2013, 61 (4): 1436- 1449. doi: 10.1109/TCOMM.2013.020413.110848
9	NEUMANN D, WIESE T, JOHAM M, et al A bilinear equalizer for massive MIMO systems. IEEE Trans. on Signal Processing, 2018, 66 (14): 3740- 3751. doi: 10.1109/TSP.2018.2838577
10	BJORNSON E, LARSSON E G, DEBBAH M Optimizing multi-cell massive MIMO for spectral efficiency: how many users should be scheduled? Proc. of the IEEE Global Conference on Signal and Information, 2014, 612- 616.
11	HOYDIS J, TEN BRINK S, DEBBAH M Massive MIMO in the UL/DL of cellular networks: how many antennas do we need. IEEE Journal on Selected Areas in Communications, 2013, 31 (2): 160- 171. doi: 10.1109/JSAC.2013.130205
12	ZHANG X Q, WU S B, YU S S, et al Spectral efficiency of massive MIMO networks with pilot contamination and channel covariance matrix estimation. IET Communications, 2019, 13 (1): 59- 65. doi: 10.1049/iet-com.2018.5032
13	LU L, LI G Y, SWINDLEHURST A L, et al An overview of massive MIMO: benefits and challenges. IEEE Journal of Se-lected Topics in Signal Processing, 2014, 8 (5): 742- 758. doi: 10.1109/JSTSP.2014.2317671
14	MORALES J L L, ROY S Channel estimation using time-shifted pilot sequences in non-cooperative cellular TDD networks with large antenna arrays. Proc. of the Asilomar Conference on Signals, Systems and Computers, 2013, 1258- 1262.
15	WEI T, FENG W, SHI R, et al. Coordinated multi-cell multi-user pilot allocation in massive MIMO systems with time-shifted pilots. Proc. of the International Conference on Wireless Communications & Signal Processing, 2015. DOI: 10.1109/WCSP.2015.7341265.
16	JIN S, WANG X T, LI Z, et al On massive MIMO zero-forcing transceiver using time-shifted pilots. IEEE Trans. on Vehicular Technology, 2016, 65 (1): 59- 74. doi: 10.1109/TVT.2015.2391192
17	CHANG W, HUA Y K, LIAO S F Partial overlapped time-shifted pilots for massive MIMO systems. IEEE Communications Letters, 2017, 21 (11): 2480- 2483. doi: 10.1109/LCOMM.2017.2734766
18	YANG X, ZHANG S M, GAO B, et al. A low complexity joint user grouping and resource allocation algorithm in massive MIMO systems. Proc. of the 19th IEEE International Conference on Communication Technology, 2019: 914−919.
19	WANG Z Y, ZHOU T, XU T H, et al. Joint user grouping and power control of virtual MIMO in fog computing. Proc. of the IEEE Globecom Workshops, 2019. DOI: 10.1109/GCWshps45667.2019.9024447.
20	KONG Q, FENG W J. Pilot allocation algorithm based on user grouping in massive MIMO systems. Proc. of the 5th IEEE International Conference on Computer and Communications, 2019: 1120−1125.
21	LAGO L A, ZHANG Y, HE Z, et al. Pilot decontamination based on superimposed pilots in massive MIMO systems. Proc. of the 88th IEEE Vehicular Technology Conference, 2018. DOI: 10.1109/VTCFall.2018.8690763.
22	WANG Z C, GAO Z, DAI L L Structured compressive sensing based superimposed pilot design in downlink large-scale MIMO systems. Electronics Letters, 2014, 50 (12): 896- 898. doi: 10.1049/el.2014.0985
23	GHAZANFARI A, CHENG H V, BJORNSON E, et al Enhanced fairness and scalability of power control schemes in multi-cell massive MIMO. IEEE Trans. on Communications, 2020, 68 (5): 2878- 2890. doi: 10.1109/TCOMM.2020.2970058
24	WANG J T Joint MMSE equalization and power control for MIMO system under multi-user interference. IEEE Communi-cations Letters, 2012, 16 (1): 54- 56. doi: 10.1109/LCOMM.2011.111011.112134
25	ZHENG X R, ZHANG H, XU W, et al. Optimized pilot power allocation for heterogeneous users in massive MIMO downlinks. Proc. of the International Conference on Information and Communication Technology Convergence, 2014: 246−250.
26	ZHANG Y, ZHU W P, OUYANG J. Energy efficient pilot and data power allocation in multi-cell multi-user massive MIMO communication systems. Proc. of the 84th IEEE Vehicular Technology Conference, 2016. DOI: 10.1109/VTCFall.2016.7880987.
27	LIU P, JIN S, JIANG T, et al Pilot power allocation through user grouping in multi-cell massive MIMO systems. IEEE Trans. on Communications, 2017, 65 (4): 1561- 1574. doi: 10.1109/TCOMM.2016.2645767
28	WANG H R Pilot contamination reduction in very large MIMO multi-cell TDD systems. Journal of Signal Processing, 2013, 29 (2): 171- 180.
29	WANG H R, WANG Y H, HANG Y M, et al Pilot contamination reduction in very large MIMO cellular network. Journal on Communications, 2014, 35 (1): 24- 33.
30	XU Y H, WU Y. An approach of pilot contamination reduction based on power control and orthogonal identification. Proc. of the 3rd IEEE International Conference on Cloud Computing and Big Data Analysis, 2018: 476−480.
31	SHAFIN R, LIU L J Superimposed pilot for multi-cell multi-user massive FD-MIMO systems. IEEE Trans. on Wireless Communications, 2020, 19 (5): 3591- 3606. doi: 10.1109/TWC.2020.2975551
32	VERENZUELA D, BERGSTROM A, BJORNSON E. Optimal power control for superimposed pilots in uplink massive MIMO systems. Proc. of the 52nd Asilomar Conference on Signals, Systems, and Computers, 2018: 499−503.
33	BAO D, QIN G D, DONG Y Y A superimposed pilot-based integrated radar and communication system. IEEE Access, 2020, 8, 11520- 11533. doi: 10.1109/ACCESS.2020.2965153
34	FANG X, ZHANG J F, CAO H Y, et al Dynamic pilot assignment in large scale MIMO systems. Journal of Electronics & Information Technology, 2016, 38 (8): 1901- 1907.
35	WU Y C, LIU T, CAO M, et al. Pilot contamination reduction in massive MIMO systems based on pilot scheduling. EURASIP Journal on Wireless Communications and Networking, 2018, 1: 21. DOI: 10.1186/s13638-018-1029-1.
36	ALEXEI A, LIANGBIN L, MARZETTA T L Interference reduction in multi-cell massive MIMO systems with large-scale fading precoding. IEEE Trans. on Information Theory, 2018, 64 (9): 6340- 6361. doi: 10.1109/TIT.2018.2853733

Parameter	Value
Number of cells L	7
Cell radius R/m	500
Number of BS antennas M	16?256
Number of users in each cell K	10?40
Path loss $\kappa $	3.8
Signal-to-noise ratio (SNR)/dB	0?20
Log normal shadowing fading ${\sigma _{{\rm{shadow}}}}$ /dB	8

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A pilot allocation method for multi-cell multi-user massive MIMO system

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