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A Sparse Optimization Approach for Beyond 5G mmWave Massive MIMO Networks

Waleed Shahjehan1, Abid Ullah1, Syed Waqar Shah1, Imran Khan1, Nor Samsiah Sani2, Ki-Il Kim3,*

1 Department of Electrical Engineering, University of Engineering and Technology Peshawar, Pakistan
2 Center for Artificial Intelligence Technology, Faculty of Information Science & Technology, Universiti Kebangsaan, Kajang, 43000, Malaysia
3 Department of Computer Science and Engineering, Chungnam National University, Daejeon, 34134, Korea

* Corresponding Author: Ki-Il Kim. Email: email

Computers, Materials & Continua 2022, 72(2), 2797-2810. https://doi.org/10.32604/cmc.2022.026185

Abstract

Millimeter-Wave (mmWave) Massive MIMO is one of the most effective technology for the fifth-generation (5G) wireless networks. It improves both the spectral and energy efficiency by utilizing the 30–300 GHz millimeter-wave bandwidth and a large number of antennas at the base station. However, increasing the number of antennas requires a large number of radio frequency (RF) chains which results in high power consumption. In order to reduce the RF chain's energy, cost and provide desirable quality-of-service (QoS) to the subscribers, this paper proposes an energy-efficient hybrid precoding algorithm for mmWave massive MIMO networks based on the idea of RF chains selection. The sparse digital precoding problem is generated by utilizing the analog precoding codebook. Then, it is jointly solved through iterative fractional programming and successive convex optimization (SCA) techniques. Simulation results show that the proposed scheme outperforms the existing schemes and effectively improves the system performance under different operating conditions.

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Cite This Article

APA Style
Shahjehan, W., Ullah, A., Shah, S.W., Khan, I., Sani, N.S. et al. (2022). A sparse optimization approach for beyond 5G mmwave massive MIMO networks. Computers, Materials & Continua, 72(2), 2797-2810. https://doi.org/10.32604/cmc.2022.026185
Vancouver Style
Shahjehan W, Ullah A, Shah SW, Khan I, Sani NS, Kim K. A sparse optimization approach for beyond 5G mmwave massive MIMO networks. Comput Mater Contin. 2022;72(2):2797-2810 https://doi.org/10.32604/cmc.2022.026185
IEEE Style
W. Shahjehan, A. Ullah, S.W. Shah, I. Khan, N.S. Sani, and K. Kim "A Sparse Optimization Approach for Beyond 5G mmWave Massive MIMO Networks," Comput. Mater. Contin., vol. 72, no. 2, pp. 2797-2810. 2022. https://doi.org/10.32604/cmc.2022.026185



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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