Review paper on Beamforming Design for Massive MIMO Systems with Channel State Information
Keywords:
Massive MIMO, Channel State Information, Square Root-Recursive Least Square (QR-RLS)Abstract
In a cellular network, the demand for high throughput and reliable transmission is increasing in large scale. One of the architectures proposed for 5G wireless communication to satisfy the demand is Massive MIMO system. The massive system is equipped with the large array of antennas at the Base Station (BS) serving multiple single antenna users simultaneously i.e., number of BS antennas are typically more compared to the number of users in a cell. The advantages of massive MIMO can be achieved only if Channel State Information (CSI) is known at BS uplink and downlink operate on orthogonal channels - TDD and FDD modes. Depending on slow/fast channel fading conditions, several authors suggested adaptive LMS, RLS and NLMS based channel estimators, which either require statistical information of the channel or are not efficient enough in terms of performance or computations. In order to overcome the above effects, the work focuses on the QR-RLS based channel estimation method for Massive MIMO systems.
References
Ganesan Thiagarajan and Sanjeev Gurugopinath, “A Novel Hybrid Beamformer Design for Massive MIMO Systems in 5G,” 3rd 5G World Forum (5GWF), PP. NO. 436-441, IEEE 2020.
Supriya Edurn and Nakkeeran Rangasamy, “BER Analysis of Massive MIMO Systems under Correlated Rayleigh Fading Channel”, 9th ICCCNT IEEE 2018, IISc, Bengaluru, India.
H. Q. Ngo A. Ashikhin H. Yang E. G. Larsson T. L. Marzetta “Cell-free massive MIMO versus small cells” IEEE Trans. Wireless Comm. vol. 16 no. 3 pp. 1834-1850 Mar. 2017.
Huang A. Burr “Compute-and-forward in cell-free massive MIMO: Great performance with low backhaul load” Proc. IEEE Int. Conf. Commun. (ICC) pp. 601-606 May 2017.
H. Al-Hraishawi, G. Amarasuriya, and F. R. Schaefer, “Secure communication in underlay cognitive massive MIMO systems with pilot contamination,” in Proc. IEEE Global Commun. Conf. (Globecom), pp. 1–7, Dec. 2017.
V. D. Nguyen et al., “Enhancing PHY security of cooperative cognitive radio multicast communications,” IEEE Trans. Cognitive Communication And Networking, vol. 3, no. 4, pp. 599–613, Dec. 2017.
R. Zhao, Y. Yuan, L. Fan, and Y. C. He, “Secrecy performance analysis of cognitive decode-and-forward relay networks in Nakagami fading channels,” IEEE Trans. Communication, vol. 65, no. 2, pp. 549–563, Feb. 2017.
W. Zhu, J. Ji, and N. Wang, “Secure massive MIMO systems with limited RF chains,” IEEE Trans. Veh. Technol., vol. 66, no. 6, pp. 5455–5469, Jun. 2017.
R. Zhang, X. Cheng, and L. Yang, “Cooperation via spectrum sharing for physical layer security in device-to-device communications under laying cellular networks,” IEEE Trans. Wireless Communication, vol. 15, no. 8, pp. 5651–5663, Aug. 2016.
K. Tourki and M. O. Hasna, “A collaboration incentive exploiting the primary-secondary systems cross interference for PHY security enhancement,” IEEE J. Sel. Topics Signal Process., vol. 10, no. 8, pp. 1346–1358, Dec. 2016.
T. Zhang et al., “Secure transmission in cognitive MIMO relaying networks with outdated channel state information,” IEEE Access, vol. 4, pp. 8212–8224, Sep. 2016.
Y. Huang et al., “Secure transmission in spectrum sharing MIMO channels with generalized antenna selection over Nakagami-m channels,” IEEE Access, vol. 4, pp. 4058–4065, Jul. 2016.
M. Jian, A. Ghazali, J. Cai, Y. Rui, “Joint spectrum optimization for massive MIMO systems underlaying D2D networks,” IEEE Trans. Communication, vol. 64, no. 5, pp. 2116–2129, May 2016.
Downloads
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
