An Efficient Algorithm for mmWave MIMO Systems

Khan, Imran; Alsharif, Mohammed H.; Zafar, Mohammad Haseeb; Alassafi, Madini O.; Ashraf, Majid; Huang, Yongming; Kim, Jeong; Kim, Jin Hong

doi:10.3390/sym11060786

Cited by 7 publications

(5 citation statements)

References 27 publications

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“…Large MIMO technology is not only spectrum efficient but energy efficient as well. As the number of BS antennas increases, the received SINR increases linearly [24][25][26]. Figure 6 summarizes the data rate that can be achieved with various numbers of antennas for different BWs at the edge of cell 1 .…”

Section: Resultsmentioning

confidence: 99%

Analyzing and evaluating the energy efficiency based on multi-5G small cells with a mm-waves in the next generation cellular networks

Alsharif¹,

Yahya²,

Chaudhry³

2020

IJECE

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This paper evaluates the impact of multi-5G small cell systems on the energy efficiency (EE) in a Fifth Generation (5G) of cellular networks. Both the proposed model and the analysis of the EE in this study take into account (i) the path losses, fading, and shadowing that affect the received signal at the user equipment (UE) within the same cell, and (ii) the interference effects of adjacent cells. In addition, the concepts of new technologies such as large MIMO in millimeter range communication have also been considered. The simulation results show that the interference from adjacent cells can degrade the EE of a multi-cell cellular network. With the high interference the number of bits that will be transferred per joule of energy is 1.29 Mb/J with a 0.25 GHz bandwidth and 16 transmit antennas. While, with a 1 GHz bandwidth the transfer rate increases to 5.17 Mb/J. Whereas, with 64 transmit antennas the EE improved to 5.17 Mb/J with a 0.25 GHz BW and 20.70 Mb/J with a 1 GHz BW. These results provide insight into the impact of the number of antennas in millimeter range communication and the interference from adjacent cells on achieving real gains in the EE of multi-5G small cells cellular network.

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Section: Resultsmentioning

confidence: 99%

Analyzing and evaluating the energy efficiency based on multi-5G small cells with a mm-waves in the next generation cellular networks

Alsharif¹,

Yahya²,

Chaudhry³

2020

IJECE

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“…A uniform linear array is considered at both the transmitting end and the receiving end. The channel model is shown in Equation (2). To reduce the interference between the beams, the exit angle of the transmitting beam is evenly distributed between − π 2 , π 2 .…”

Section: Simulation Results and Analysismentioning

confidence: 99%

“…Millimeter wave multiple-input multiple-output (MIMO) communication enabling high speed and high quality without line communication transmission has become a hot spot of global attention [1,2]. Due to the short wavelength of millimeter wave, the antenna array can be integrated into a millimeter wave communication system.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Precoding Scheme for Millimeter-Wave Massive MIMO Systems

Alemaishat¹,

Saraereh

Khan

et al. 2019

Electronics

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Aiming at the problem of high computational complexity due to a large number of antennas deployed in mmWave massive multiple-input multiple-output (MIMO) communication systems, this paper proposes an efficient algorithm for optimizing beam control vectors with low computational complexity based on codebooks for millimeter-wave massive MIMO systems with split sub-arrays hybrid beamforming architecture. A bidirectional method is adopted on the beam control vector of each antenna sub-array both at the transmitter and receiver, which utilizes the idea of interference alignment (IA) and alternating optimization. The simulation results show that the proposed algorithm has low computational complexity, fast convergence, and improved spectral efficiency as compared with the state-of-the-art algorithms.2 of 15 constant constraint so the performance achieved by analog beamforming technology will be limited [6]. Simultaneous use of beamforming in the digital domain and the analog domain can reduce the overhead of the system and compensate for the defects of analog beamforming, making hybrid beamforming a first pre-coding technique [7][8][9][10][11][12][13][14][15][16]. It can be seen from literature [5] that the hybrid beamforming architecture includes a separate sub-array architecture and a shared architecture. The signal on each transmit antenna in the shared architecture is a hybrid superposition of signals on all RF links, and one RF link needs to drive all transmitting antenna. Compared with the shared architecture, one RF link in a separate sub-array architecture is connected to only one antenna sub-array, and each RF link only needs to drive a transmit antenna on the sub-array connected thereto, so the separate sub-array architecture system can effectively reduce energy consumption and hardware complexity. Literature [8] analyzed the relationship between digital beamforming and hybrid beamforming and compared its performance. In [9], an algorithm for determining the sub-array analog beam control vector based on the codebook matching beam pair is proposed for the separate sub-array architecture system. However, the algorithm requires more beam training times, so that it has a high degree of complexity. In [10], both the transmitting and receiving ends are shared hybrid beamforming architectures, and an orthogonal matching pursuit (OMP) algorithm for simultaneous beamforming and digital beamforming is proposed for hybrid beamforming architecture. In [12], based on the codebook with the maximum received power as the criterion, the beamforming method is used to solve the analog beamforming, and then the equivalent channel is used to solve the digital beamforming.Applying interference alignment ideas [17][18][19] in wireless networks can achieve higher system capacity. By integrating multiple interfering signals into a small subspace at the receiving end, maximizing the number of non-interfering dimensions remaining in the desired signal minimizes the impact of the interfering signal on the desired signal while maximizing...

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“…The fifth generation of mobile communications (5G) intends to use millimeter-wave frequency bands to provide higher system capacity for users in hot spots [1]. Millimeter-wave is considered as one of the key technologies to solve the capacity demand in the fifth-generation (5G) mobile communication system due to its large number of unused frequency bands [2].…”

Section: Introductionmentioning

confidence: 99%

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

Shahjehan¹,

Ullah²,

Shah³

et al. 2022

Computers, Materials &Amp; Continua

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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-ofservice (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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An Efficient Algorithm for mmWave MIMO Systems

Cited by 7 publications

References 27 publications

Analyzing and evaluating the energy efficiency based on multi-5G small cells with a mm-waves in the next generation cellular networks

Analyzing and evaluating the energy efficiency based on multi-5G small cells with a mm-waves in the next generation cellular networks

An Efficient Precoding Scheme for Millimeter-Wave Massive MIMO Systems

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

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