MMwave MIMO in 5G Network Analysis for Spectral Efficiency with Beamforming Based Channel Estimation

Main Article Content

Dharmesh Dhabliya


5G network has its high energy efficiency and spectrum efficiency, massive multiple-input and multiple-output (MIMO) has been envisioned as a key technology.This research work is centred on optimal method creation of energy-efficient massive MIMO methods, which is most active research technology in the communication industry.The suggested model, which takes into account a multi-cell model scenario, is a realistic method that improved spectral efficiency (SE) of huge MIMO methods.Base stations (BSs) do channel estimate based on uplink (UL) transmission using least-square (LS), element-wise MMSE, and minimum mean-squared error (MMSE) estimators.This research propose novel technique in MMwaveMIMO 5G network based spectral efficiency and channel estimation. The aim of this research is to enhance the spectral efficiency of MIMO channel using HetNets zero forcing Multiuser propagation models. The channel estimation is carried out based on beamforming using matched filter channel estimation with wide band antenna.Finally, simulation results demonstrate the high channel estimate accuracy and spectrum efficiency that the suggested systems can accomplish.Proposed technique attained sum rate of 85%, spectral efficiency of 93%, DoF of 79%, energy efficiency of 98% and detection accuracy of 96% for number of cells and sum rate of 77%, spectral efficiency of 85%, DoF of 71%, energy efficiency of 92% and detection accuracy of 95% for number of users.

Article Details

How to Cite
Dhabliya, D. . (2022). MMwave MIMO in 5G Network Analysis for Spectral Efficiency with Beamforming Based Channel Estimation. International Journal on Future Revolution in Computer Science &Amp; Communication Engineering, 8(2), 40–50.


Uthansakul, P., &Bialkowski, M. E. (2006). An Adaptive Power and Bit Allocation Algorithm for MIMO OFDM/SDMA System Employing Zero-Forcing Multi-user Detection. African Journal of Information & Communication Technology, 2(2), 63-70.

Yang, H., & Marzetta, T. L. (2013). Performance of conjugate and zero-forcing beamforming in large-scale antenna systems. IEEE Journal on Selected Areas in Communications, 31(2), 172-179.

Gupta, A. K., Dhillon, H. S., Vishwanath, S., & Andrews, J. G. (2014, December). Downlink coverage probability in MIMO HetNets with flexible cell selection. In 2014 IEEE Global Communications Conference (pp. 1534-1539). IEEE.

Brihuega, A., Anttila, L., Abdelaziz, M., Eriksson, T., Tufvesson, F., &Valkama, M. (2020). Digital predistortion for multiuser hybrid MIMO at mmWaves. IEEE Transactions on Signal Processing, 68, 3603-3618.

Qu, F., Zhang, M., Wang, Z., Qian, C., Lu, X., & Wei, Y. (2019). Sparse channel estimation for filtered multi‐tone in time domain and subband domain based on matched filtering demodulation. IET Communications, 13(18), 2889-2894.

Hama, Y., &Ochiai, H. (2019). Performance analysis of matched-filter detector for MIMO spatial multiplexing over Rayleigh fading channels with imperfect channel estimation. IEEE Transactions on Communications, 67(5), 3220-3233.

Nalband, A. H., Sarvagya, M., & Ahmed, M. R. (2021). Spectral efficient beamforming for mmwave miso systems using deep learning techniques. Arabian Journal for Science and Engineering, 46(10), 9783-9795.

Priya, T. S., Manish, K., &Prakasam, P. (2021). Hybrid beamforming for massive MIMO using rectangular antenna array model in 5G wireless networks. Wireless Personal Communications, 120(3), 2061-2083.

Abdullah, Q., Salh, A., MohdShah, N. S., Abdullah, N., Audah, L., Hamzah, S. A., ... &Nordin, S. (2021). A brief survey and investigation of hybrid beamforming for millimeter waves in 5G massive MIMO systems. arXiv preprint arXiv:2105.00180.

Dilli, R. (2021). Performance analysis of multi user massive MIMO hybrid beamforming systems at millimeter wave frequency bands. Wireless Networks, 27(3), 1925-1939.

Kebede, T., Wondie, Y., &Steinbrunn, J. (2021, October). Performance evaluation of MillimeterWave-massive MIMO with beamforming techniques. In 2021 International Symposium on Networks, Computers and Communications (ISNCC) (pp. 1-8). IEEE.

Ahmed, S. A., Ayoob, S. A., & Al Janaby, A. O. (2022). Comparative Performance of mmWave 5G System for many Beamforming Methods.

Du, J., Zhang, Y., Chen, Y., Li, X., Cheng, Y., & Rajesh, M. V. (2021). Hybrid beamforming NOMA for mmWave half-duplex UAV relay-assisted B5G/6G IoT networks. Computer Communications, 180, 232-242.

Jeyakumar, P., Malar, E., Idnani, N., &Muthuchidambaranathan, P. (2021). Large antenna array with hybrid beamforming system for 5G outdoor mobile broadband communication deployments. Wireless Personal Communications, 120(3), 2001-2027.

Alsunbuli, B. N., Ismail, W., &Mahyuddin, N. M. (2021). Convolutional neural network and Kalman filter-based accurate CSI prediction for hybrid beamforming under a minimized blockage effect in millimeter-wave 5G network. Applied Nanoscience, 1-22.

Cui, M., Han, W., Xu, D., Zhao, P., & Zou, W. (2021). Hybrid precoding design based on alternating optimization in mmWave massive MIMO systems aided by intelligent reflecting surface. Computer Communications, 180, 188-196.

Alsunbuli, B. N., Fakhruldeen, H. F., Ismail, W., &Mahyuddin, N. M. (2022). Hybrid beamforming with relay and dual-base stations blockage mitigation in millimetre-wave 5G communication applied in (VIOT). Computers and Electrical Engineering, 100, 107953.

Balti, E., & Evans, B. L. (2021). Joint beamforming and interference cancellation in mmwave wideband full-duplex systems. arXiv preprint arXiv:2110.12266.

Abose, T. A., Olwal, T. O., & Hassen, M. R. (2022). Hybrid Beamforming for Millimeter Wave Massive MIMO under Multicell Multiuser Environment. Indian Journal of Science and Technology, 15(20), 1001-1011.

Wang, J., Zhang, X., Shi, X., & Song, J. (2021). Higher Spectral Efficiency for mmWave MIMO: Enabling Techniques and Precoder Designs. IEEE Communications Magazine, 59(4), 116-122.

Feng, C., Shen, W., An, J., &Hanzo, L. (2022). Joint Hybrid and Passive RIS-Assisted Beamforming for MmWave MIMO Systems Relying on Dynamically Configured Subarrays. IEEE Internet of Things Journal.