Near-Optimal Design for Hybrid Beamforming in mmWave Massive Multi-User MIMO Systems

Zhang, Yang; Du, Jianhe; Chen, Yuanzhi; Li, Xingwang; Rabie, Khaled M.; Kharel, Rupak

doi:10.1109/access.2020.3009238

Cited by 26 publications

(19 citation statements)

References 45 publications

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“…But, SIC based HB algorithms outperforms in terms of SE at the cost of higher computational complexity [13]. The joint design of Tx and Rx in mmWave MU-mMIMO HB system for DL reduces the computational complexity where "piecewise dual joint iterative approximation" method is used which can provide closed form solutions in the analog beamforming and "baseband piecewise successive approximation" in designing digital beamforming that maximizes the number of simultaneous users served [14,15].…”

Section: Literature Reviewmentioning

confidence: 99%

Hybrid Beamforming in 5G NR Networks Using Multi User Massive MIMO at FR2 Frequency Bands

Dilli

2022

Wireless Pers Commun

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The current Sub 6 GHz band is highly occupied and unable to meet the demands of future wireless data traffic. As the millimeter wave technology is a promising way of enhancing the performance of next-generation wireless networks, it is essential to explore FR2 frequency bands. Massive Multiple-Input Multiple Output (mMIMO) technology has been introduced to improve the capacity and coverage of 5G wireless networks. Hybrid beamforming (HB) is an efficient technique to improve the channel gain and minimize the interference at reasonable complexity. The aim of HB in mMIMO systems is to maximize the sum rate that can approach the fully-digital beamforming system performance. Combination of mMIMO systems, mmWave, and HB techniques achieve higher data rates and cell coverage in 5G wireless networks. It mitigates the hardware complexity, energy consumption, and cost as number of required radio-frequency chains at base station gets minimized. In this paper, we have investigated the performance of a multi user-mMIMO HB system at 28, 39 GHz of FR2 frequency bands as well as at 66 GHz by analyzing the effect of changing variables that include the number of users, transmitting and receiving antennas, and the type of modulation. Simulation results include RMS values of error vector magnitude (EVM) that gives quantitative analysis and receive constellation of the equalized symbols that shows qualitative analysis. EVM is computed for different scenarios and it is used as an indicator of performance to assess the suitable design configuration of mMIMO system.

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Section: Literature Reviewmentioning

confidence: 99%

Hybrid Beamforming in 5G NR Networks Using Multi User Massive MIMO at FR2 Frequency Bands

Dilli

2022

Wireless Pers Commun

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“…The papers [11] and [12] describes the design of hybrid precoding and combining for mmWave MU MIMO systems. [13] and [14] describes the design of hybrid beamforming in multi-cell scenario without using SIC method where each cell has one BS and some users, and compared them in 3GPP and NYUSIM channel models, where NYUSIM and 3GPP are 2 popular channel models for 5G [15], [16], such that both are stochastic channel models.…”

Section: A Hybrid Precoding Architecturesmentioning

confidence: 99%

Performance Analysis of SIC based hybrid precoding for multi-user case in 3D scenario

Myadar

Vanidevi

2021

Preprint

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Massive MIMO (multiple input multiple output) systems are best suitable for mmWave communications improving throughput and spectral efficiency in 5G. Beamforming is a wireless technique adopted by massive MIMO and used in 4G & 5G to increase the directivity and energy efficiency by focusing the signal in specific direction supporting only single user transmission with one data stream. Precoding is a generalized form of beamforming to support multi-stream transmission in multi-antenna wireless communication, such that combination of analog and digital precoding forms the hybrid precoding which shows good performance with less complexity. Successive Interference Cancelation (SIC) is a technique in which optimization of different antenna arrays will be done one by one such that while optimizing the capacity of specific array contribution of earlier optimized array is removed from the total capacity and precoder of that specific optimizing array will be computed. In this paper we have designed the SIC based hybrid precoding using sub-connected and fully-connected structures for multi-user (MU) case and compared them with the optimal precoding for mmWave massive MIMO systems in a 3D scenario, where both azimuth and elevation angles are taken into account in the channel. The proposed algorithms are simulated in the MATLAB and compared their performance with different parameters and shown that SIC-based scheme is near-optimal for multi-user case.

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“…Efficient beamforming is used to suppress the problems of interference with high data rates. Three types of beamforming techniques are available in MIMO, such as digital, analog and hybrid beamforming [14] [15] [16]. Massive MIMO is implemented in beamforming for multiple SUs to provide efficient transmission and high spectrum efficiency in an environment with high mobility.…”

Section: Introductionmentioning

confidence: 99%

BlockCRN-IoCV: Secure Spectrum Access and Beamforming for Defense Against Attacks in mmWave Massive MIMO CRN in 6G Internet of Connected Vehicles

Pari

Jaisankar

2022

IEEE Access

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Cognitive Radio (CR) is a wireless communication system that is used for intelligent vehicles to solve spectrum scarcity and improve the utilization of the spectrum. However, spectrum sensing and data sharing are difficult due to the presence of malicious nodes which degrades the performance. To overcome these issues, we proposed the BlockCRN-IoCV method which includes authentication, density aware clustering, dual agent based spectrum access and secure beamforming. Here, authentication is performed for both Primary Users (PUs) and Secondary Users (SUs) using the Hybrid Advanced Encryption Standard and Hyper-elliptic Curve Cryptography (AES-HCC) algorithm by considering ID, PUF and location which ensures the legitimacy of the users. To address the mobility of the vehicle we perform density aware clustering using Density aware Dynamic Radius Clustering (DADRC) by considering location, distance and direction for increasing throughput. After completing clustering, we perform efficient spectrum access by using the Dual Agent based Twin Delayed (DA-TD3) algorithm which includes two agents, the first agent performs spectrum sensing by considering SNR, noise level and trust, and the second agent performs spectrum allocation by considering Channel State Information (CSI), in which the CSI is predicted by Quasi-Newton Iterative Unscented Kalman Filter (QNIUKF) algorithm for effective data transmission. Finally, secure beamforming is performed using Bi-Gated Recurrent Neural Network (BiGRU-CapsNet) by considering CSI, beam score, array factor, and direction of angle. The simulation is carried out by OMNET++ and SUMO simulation tools and the performance of this work is evaluated by throughput, packet delivery ratio, SNR, detection accuracy, BER, and delay. The simulation result shows that the proposed work achieves superior performance compared to existing work for secure spectrum sensing and beamforming.

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Near-Optimal Design for Hybrid Beamforming in mmWave Massive Multi-User MIMO Systems

Cited by 26 publications

References 45 publications

Hybrid Beamforming in 5G NR Networks Using Multi User Massive MIMO at FR2 Frequency Bands

Hybrid Beamforming in 5G NR Networks Using Multi User Massive MIMO at FR2 Frequency Bands

Performance Analysis of SIC based hybrid precoding for multi-user case in 3D scenario

BlockCRN-IoCV: Secure Spectrum Access and Beamforming for Defense Against Attacks in mmWave Massive MIMO CRN in 6G Internet of Connected Vehicles

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