DFT codebook-based hybrid precoding for multiuser mmWave massive MIMO systems

Huang, Yu; Liu, Chen; Song, Yunchao; Yu, Xiaolei

doi:10.1186/s13634-020-00669-4

Cited by 17 publications

(10 citation statements)

References 22 publications

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“…As far as mmWave channel modeling is concerned, an extended Saleh-Valenzuela model is commonly used. This model is used in our research because of the high antenna correlation, and low spatial selectivity [83]. The use of a geometric channel model with L k scatters is applied for the channel of the k th user.…”

Section: B Millimeter Wave Channel Modelmentioning

confidence: 99%

Precoding and Beamforming Techniques in mmWave-Massive MIMO: Performance Assessment

et al. 2022

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Massive MIMO and mmWave communication are the technologies for achieving 5G design goals. Fortunately, these two technologies share a symbiotic integration. As a result, amalgamating mmWave communications with massive MIMO forms, "mmWave-massive MIMO," which significantly improves spectral and energy efficiency. It also achieves high multiplexing gains and increases mobile network capacity. However, massive MIMO, mmWave communications, and mmWave-massive MIMO systems have been studied independently. Consequently, this article explores the ideas, performances, comparisons, and discussions of these three 5G technologies jointly, considering their precoding and beamforming methods. On the other hand, the complexity of these technologies increases when a large number of antennas and radio frequencies (RFs) are used. Thus, several investigations are going on to search for the appropriate precoding and beamforming strategies with low cost, power, and complexity. Therefore, massive MIMO linear precoding techniques such as zero-forcing, maximum ratio transmission, regularized zero-forcing, truncated polynomial expansion and phased zero forcing are addressed in this work. In addition, the most common non-linear precoding schemes: dirty-paper coding, Tomlinson-Harashima, and vector perturbation, are presented. Furthermore, a detailed discussion of the beamforming techniques called analog, digital, and hybrid analog-digital beamforming schemes is included. We also examine the potential of hybrid analog-digital beamforming with its fully-connected and sub-connected architecture approaches in making mmWave massive MIMO a reality. We evaluate their performance with the parameters: bit error rate, signal to noise ratio, complexity, spectral efficiency, and energy efficiency. According to the analytical and simulation results, the partially-connected hybrid analog/digital beamforming architecture offers better allover performance for mmWave-Massive MIMO communications by compromising: power consumption, cost, complexity, and performance. Finally, the potential future directions in mmWave-massive MIMO precoding and beamforming challenges are addressed.

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Section: B Millimeter Wave Channel Modelmentioning

confidence: 99%

Precoding and Beamforming Techniques in mmWave-Massive MIMO: Performance Assessment

et al. 2022

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“…Massive MIMO advantages of low computational complexity and high energy efficiency can be achieved. A hybrid precoding based on codebook with separately analog/digital precoders for multiuser mmWave massive systems is presented in [10]. An efficient conflicting-well known beam-column choice is also studied.…”

Section: A Prior Workmentioning

confidence: 99%

Performance Enhancement of MmWave MIMO Systems Using Deep Learning Framework

2021

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In order to obtain beamforming gains and prevent high pathloss in millimeter wave (mmWave) systems, large number of antennas is employed. Digital precoders are difficult to implement with many antennas because of hardware constraints, while analog precoders have limited performance. In this paper, hybrid precoding based on a deep learning framework, HybridPrecodingNet, is proposed, which uses largescale information to predict the parameters of hybrid precoders and decoders. The statistics of the channel covariance matrix are applied to design the hybrid precoders and decoders. The proposed HybridPrecodingNet at the receiver is applied for the channel estimation and design of hybrid decoders. In our proposed framework, the structure of HybridPrecodingNet is trained to learn how to optimize the hybrid precoder and decoder for maximum spectral efficiency. Comparison between different precoding techniques is provided. Results show that HybridPrecodingNet approaches the sub-optimal solution and gives significant spectral efficiency enhancement.

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“…An extended Saleh-Valenzuela model is commonly applied in mmWavemassive MIMO channel modeling. Thus, our research work considers this model due to the high antenna correlation and the limited spatial selectivity [37]. The hypothesis in which each scatter represents a single path is assumed.…”

Section: B Mmwave Channel Modelmentioning

confidence: 99%

Massive MIMO, mmWave and mmWave-Massive MIMO Communications: Performance Assessment with Beamforming Techniques

Engda¹,

Wondie²,

Steinbrunn³

2020

Preprint

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A considerable amount of enabling technologies are being explored in the era of fifth generation (5G) mobile system. The dream is to build a wireless network that substantially improves the existing mobile networks in all performance metrics. To address this 5G design targets, massive MIMO (multiple input multiple output) and mmWave (millimeter wave) communication are also candidate technologies. Luckily, in many respects these two technologies share a symbiotic integration. Accordingly, a logical step is to integrate mmWave communications and massive MIMO to form mmWave-massive MIMO which substantially increases user throughput, improve spectral and energy efficiencies, increase the capacity of mobile networks and achieve high multiplexing gains. Thus, this work analyses the concepts, performances, comparison and discussion of these technologies called: massive MIMO, mmWave Communications and mmWave-massive MIMO systems jointly. Besides, outcomes of extensive researches, emerging trends together with their respective benefits, challenges, proposed solutions and their comparative analysis is addressed. The performance of hybrid analog-digital beamforming architecture with a fully digital and analog beamforming techniques are also analyzed. Analytical and simulation results show that the low-complexity hybrid analog-digital precoding achieves all round comparable precoding gains for mmWave-Massive MIMO technology.

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DFT codebook-based hybrid precoding for multiuser mmWave massive MIMO systems

Cited by 17 publications

References 22 publications

Precoding and Beamforming Techniques in mmWave-Massive MIMO: Performance Assessment

Precoding and Beamforming Techniques in mmWave-Massive MIMO: Performance Assessment

Performance Enhancement of MmWave MIMO Systems Using Deep Learning Framework

Massive MIMO, mmWave and mmWave-Massive MIMO Communications: Performance Assessment with Beamforming Techniques

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