TY - JOUR
T1 - Cooperative Scheduling for Pilot Reuse in Massive MIMO Systems
AU - Hua, Yun Kuei
AU - Chang, Wenson
AU - Su, Szu Lin
N1 - Funding Information:
Manuscript received October 11, 2019; revised April 2, 2020 and May 30, 2020; accepted June 28, 2020. Date of publication August 4, 2020; date of current version November 12, 2020. This work was supported by Qualcomm Taiwan University Research Project under the contracts of Research Collaboration Agreements NAT-408931 and NAT-435536, respectively. The review of this article was coordinated by Dr. Huiling Zhu. (Corresponding author: Wenson Chang.) Yun-Kuei Hua is with the Department of Artificial Intelligence, CTBC Business School, Tainan City 709, Taiwan (e-mail: g901305@hotmail.com).
Publisher Copyright:
© 1967-2012 IEEE.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/11
Y1 - 2020/11
N2 - To be differentiated from the literature, in this paper, we aim to alleviate the impact of pilot contamination (PC) on the massive MIMO systems by cooperatively scheduling users (rather than just assigning) among neighboring cells to share the limited orthogonal pilots. To this end, we develop the multi-cell cooperative scheduling (MCCS) algorithm together with the cooperative scheduling indexes (COSIs) for maximizing the data rate, maximizing the Jain's fairness index and reaching a better tradeoff in-between. For convenience, they are denoted by the COSIs for the CMDR, CMMF and CPF schedulers, respectively. However, its high computational complexity may somehow resists its from practical applications. Thus, a low-complexity cooperative proportional fairness (LC-CPF) algorithm is designed to well approach the MCCS algorithm using the CPF COSI; and at the meantime, the order of computational complexity can be significantly reduced. Moreover, its ability to reach a better tradeoff can still be maintained under the impact of high spectrum-sharing interference. In addition, it is interesting to find that using the proposed cooperative scheduling methods, the open-loop power control mechanism is no longer required for compensating the differences of received signal quality between users.
AB - To be differentiated from the literature, in this paper, we aim to alleviate the impact of pilot contamination (PC) on the massive MIMO systems by cooperatively scheduling users (rather than just assigning) among neighboring cells to share the limited orthogonal pilots. To this end, we develop the multi-cell cooperative scheduling (MCCS) algorithm together with the cooperative scheduling indexes (COSIs) for maximizing the data rate, maximizing the Jain's fairness index and reaching a better tradeoff in-between. For convenience, they are denoted by the COSIs for the CMDR, CMMF and CPF schedulers, respectively. However, its high computational complexity may somehow resists its from practical applications. Thus, a low-complexity cooperative proportional fairness (LC-CPF) algorithm is designed to well approach the MCCS algorithm using the CPF COSI; and at the meantime, the order of computational complexity can be significantly reduced. Moreover, its ability to reach a better tradeoff can still be maintained under the impact of high spectrum-sharing interference. In addition, it is interesting to find that using the proposed cooperative scheduling methods, the open-loop power control mechanism is no longer required for compensating the differences of received signal quality between users.
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U2 - 10.1109/TVT.2020.3014118
DO - 10.1109/TVT.2020.3014118
M3 - Article
AN - SCOPUS:85096330558
VL - 69
SP - 12857
EP - 12869
JO - IEEE Transactions on Vehicular Technology
JF - IEEE Transactions on Vehicular Technology
SN - 0018-9545
IS - 11
M1 - 9158553
ER -