CLC number: TN92
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2018-05-11
Cited: 0
Clicked: 8022
Shang Liu, Ishtiaq Ahmad, Ping Zhang, Zhi Zhang. Multi-user rate and power analysis in a cognitive radio network with massive multi-input multi-output[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(5): 674-684.
@article{title="Multi-user rate and power analysis in a cognitive radio network with massive multi-input multi-output",
author="Shang Liu, Ishtiaq Ahmad, Ping Zhang, Zhi Zhang",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="19",
number="5",
pages="674-684",
year="2018",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1700081"
}
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Abstract: This paper discusses transmission performance and power allocation strategies in an underlay cognitive radio (CR) network that contains relay and massive multi-input multi-output (MIMO). The downlink transmission performance of a relay-aided massive MIMO network without CR is derived. By using the power distribution criteria, the kth user’s asymptotic signal to interference and noise ratio (SINR) is independent of fast fading. When the ratio between the base station (BS) antennas and the relay antennas becomes large enough, the transmission performance of the whole system is independent of BS-to-relay channel parameters and relates only to the relay-to-users stage. Then cognitive transmission performances of primary users (PUs) and secondary users (SUs) in an underlay CR network with massive MIMO are derived under perfect and imperfect channel state information (CSI), including the end-to-end SINR and achievable sum rate. When the numbers of primary base station (PBS) antennas, secondary base station (SBS) antennas, and relay antennas become infinite, the asymptotic SINR of the kth PU and SU is independent of fast fading. The interference between the primary network and secondary network can be canceled asymptotically. Transmission performance does not include the interference temperature. The secondary network can use its peak power to transmit signals without causing any interference to the primary network. Interestingly, when the antenna ratio becomes large enough, the asymptotic sum rate equals half of the rate of a single-hop single-antenna K-user system without fast fading. Next, the PUs’ utility function is defined. The optimal relay power is derived to maximize the utility function. The numerical results verify our analysis. The relationships between the transmission rate and the antenna number, relay power, and antenna ratio are simulated. We show that the massive MIMO with linear pre-coding can mitigate asymptotically the interference in a multi-user underlay CR network. The primary and secondary networks can operate independently.
[1]Amarasuriya G, Poor HV, 2015. Multi-user relay networks with massive MIMO. IEEE Int Conf on Communications, p.2017-2023.
[2]Boccardi F, Heath R, Lozano A, et al., 2014. Five disruptive technology directions for 5G. IEEE Commun Mag, 52(2):74-80.
[3]Chen C, Wang L, 2007. Performance analysis of scheduling in multiuser MIMO systems with zero-forcing receivers. IEEE J Sel Area Commun, 25(7):1435-1445.
[4]Goldsmith A, Jafar S, Maric I, et al., 2009. Breaking spectrum gridlock with cognitive radios: an information theoretic perspective. Proc IEEE, 97(5):894-914.
[5]Haykin S, 2005. Cognitive radio: brain-empowered wireless communications. IEEE J Sel Area Commun, 23(2):201-220.
[6]Hosseini K, Hoydis J, Ten Brink S, et al., 2013. Massive MIMO and small cells: how to densify heterogeneous networks. IEEE Int Conf on Communications, p.5442-5447.
[7]Li JZ, Ai Bo, He RS, et al., 2017. Indoor massive multiple-input multiple-output channel characterization and performance evaluation. Front Inform Technol Electron Eng, 18(6):773-787.
[8]Li Y, Zhu G, Du X, 2014. Aligning guard zones of massive MIMO in cognitive femtocell networks. IEEE Commun Lett, 18(2):229-232.
[9]Manna R, Louie R, Li Y, et al., 2011. Cooperative spectrum sharing in cognitive radio networks with multiple antennas. IEEE Trans Signal Process, 59(11):5509-5522.
[10]Marzetta T, 2010. Noncooperative cellular wireless with unlimited numbers of base station antennas. IEEE Trans Wirel Commun, 9(11):3590-3600.
[11]Mitola J, Maguire G, 1999. Cognitive radio: making software radios more personal. IEEE Pers Commun, 6(4):13-18.
[12]Ngo H, Larsson E, Marzetta T, 2013. Energy and spectral efficiency of very large multiuser MIMO systems. IEEE Trans Commun, 61(4):1436-1449.
[13]Rusek F, Persson D, Lau BK, et al., 2013. Scaling up MIMO: opportunities and challenges with very large arrays. IEEE Trans Signal Process Mag, 30(1):40-60.
[14]Suraweera H, Ngo H, Duong T, et al., 2013. Multi-pair amplify-and-forward relaying with very large antenna arrays. IEEE Int Conf on Communications, p.4635-4640.
[15]Tao YZ, Wu CY, Huang YZ, et al., 2018. A projected gradient based game theoretic approach for multi-user power control in cognitive radio network. Front Inform Technol Electron Eng, 19(3):367-378.
[16]Wang L, Ngo H, Elkashlan M, et al., 2017. Massive MIMO in spectrum sharing networks: achievable rate and power efficiency. IEEE Syst J, 11(1):20-31.
[17]Zhang Q, Jin S, McKay M, et al., 2015. Power allocation schemes for multicell massive MIMO systems. IEEE Trans Wirel Commun, 14(11):5941-5955.
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