TY - JOUR
T1 - Securing Downlink Massive MIMO-NOMA Networks with Artificial Noise
AU - Zeng, Ming
AU - Nguyen, Nam Phong
AU - Dobre, Octavia A.
AU - Poor, H. Vincent
N1 - Funding Information:
Manuscript received September 11, 2018; revised January 22, 2019; accepted February 15, 2019. Date of publication February 22, 2019; date of current version May 22, 2019. This work was supported in part by the Natural Sciences and Engineering Research Council of Canada (NSERC) through its Discovery program, and in part by the U.S. National Science Foundation under Grants CCF-093970 and CCF-1513915. The guest editor coordinating the review of this manuscript and approving it for publication was Prof. Robert Schober. (All authors contributed equally to the article. (Corresponding author: Octavia A. Dobre.) M. Zeng and O. A. Dobre are with the Memorial University, St. John’s, NL A1C 5S7, Canada (e-mail:,mzeng@.mun.ca; odobre@.mun.ca).
Publisher Copyright:
© 2019 IEEE.
PY - 2019/6
Y1 - 2019/6
N2 - In this paper, we focus on securing the confidential information of massive multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) networks by exploiting artificial noise (AN). An uplink training scheme is first proposed with minimum mean-squared-error estimation at the base station. Based on the estimated channel state information, the base station precodes the confidential information and injects the AN. Following this, the ergodic secrecy rate is derived for downlink transmission. An asymptotic secrecy performance analysis is also carried out for a large number of transmit antennas and high-transmit power at the base station, respectively, to highlight the effects of key parameters on the secrecy performance of the considered system. Based on the derived ergodic secrecy rate, we propose the joint power allocation of the uplink training phase and downlink transmission phase to maximize the sum secrecy rates of the system. Besides, from the perspective of security, another optimization algorithm is proposed to maximize the energy efficiency. The results show that the combination of massive MIMO technique and AN greatly benefits NOMA networks in term of the secrecy performance. In addition, the effects of the uplink training phase and clustering process on the secrecy performance are revealed. Besides, the proposed optimization algorithms are compared with other baseline algorithms through simulations, and their superiority is validated. Finally, it is shown that the proposed system outperforms the conventional massive MIMO orthogonal multiple access in terms of the secrecy performance.
AB - In this paper, we focus on securing the confidential information of massive multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) networks by exploiting artificial noise (AN). An uplink training scheme is first proposed with minimum mean-squared-error estimation at the base station. Based on the estimated channel state information, the base station precodes the confidential information and injects the AN. Following this, the ergodic secrecy rate is derived for downlink transmission. An asymptotic secrecy performance analysis is also carried out for a large number of transmit antennas and high-transmit power at the base station, respectively, to highlight the effects of key parameters on the secrecy performance of the considered system. Based on the derived ergodic secrecy rate, we propose the joint power allocation of the uplink training phase and downlink transmission phase to maximize the sum secrecy rates of the system. Besides, from the perspective of security, another optimization algorithm is proposed to maximize the energy efficiency. The results show that the combination of massive MIMO technique and AN greatly benefits NOMA networks in term of the secrecy performance. In addition, the effects of the uplink training phase and clustering process on the secrecy performance are revealed. Besides, the proposed optimization algorithms are compared with other baseline algorithms through simulations, and their superiority is validated. Finally, it is shown that the proposed system outperforms the conventional massive MIMO orthogonal multiple access in terms of the secrecy performance.
KW - Non-orthogonal multiple access (NOMA)
KW - artificial noise (AN)
KW - massive multiple-input multiple-output (MIMO)
KW - physical layer security
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U2 - 10.1109/JSTSP.2019.2901170
DO - 10.1109/JSTSP.2019.2901170
M3 - Article
AN - SCOPUS:85062146987
SN - 1932-4553
VL - 13
SP - 685
EP - 699
JO - IEEE Journal on Selected Topics in Signal Processing
JF - IEEE Journal on Selected Topics in Signal Processing
IS - 3
M1 - 8649584
ER -