• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.5
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• pp.123-129
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• 2018

Recently, as required wireless communication traffic increase, millimeter wave mobile technologies that can secure broadband spectrum are gaining attention. However, the path loss is high in the millimeter wave channel. Massive MIMO system is being researched in which can complement the path loss by beamforming by equiped large-scale antenna at the base station. While legacy beamforming techniques have analog and digital methods, practical difficulties exist for application to massive MIMO systems in terms of system complexity and cost. Therefore, this paper studies a hybrid beamforming scheme for massive MIMO system in the millimeter wave band. Also this paper considers spatial multiplexing scheme to serve multi-users with multiple received antennas. Gains of the beamforming and the spatial multiplexing schemes are evaluated by analyzing the spectral efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.261-279
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• 2023

In this article, the uplink achievable rate is investigated for massive multiple-input multiple-output (MIMO) under correlated Ricean fading channel, where each base station (BS) and user are both deployed multiple antennas. Considering the availability of prior knowledge at BS, two different channel estimation approaches are adopted with and without prior knowledge. Based on these channel estimations, a two-layer decoding scheme is adopted with maximum ratio precoding as the first layer decoder and optimal second layer precoding in the second layer. Based on two aforementioned channel estimations and two-layer decoding scheme, the exact closed form expressions for uplink achievable rates are computed with and without prior knowledge, respectively. These derived expressions enable us to analyze the impacts of line-of-sight (LoS) component, two-layer decoding, data transmit power, pilot contamination, and spatially correlated Ricean fading. Then, numerical results illustrate that the system with spatially correlated Ricean fading channel is superior in terms of uplink achievable rate. Besides, it reveals that compared with the single-layer decoding, the two-layer decoding scheme can significantly improve the uplink achievable rate performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5410-5426
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• 2019

With the advent of the fifth-generation (5G) era, Massive multiple-input multiple-output (MIMO) relay systems have experienced the rapid development. Recently, the performance analysis models of Massive MIMO relay systems have been proposed, which are mostly based on Rayleigh fading channels. In order to create a more suitable model for 5G Internet of Things scenarios, our study is based on the Rician fading channels, where line-of-sight (LOS) path exists in the channels. In this paper, we assume the channel state information (CSI) is perfect. In this case, we use statistical information to derive the analytical exact closed-form expression for the achievable sum rate of the uplink for the Massive MIMO two-hop relay system over Rician fading channels. Moreover, considering the different communication scenarios, we derive the analytical exact closed-form expression for the achievable sum rates of the uplink for other three scenarios. Finally, based on these expressions, we make simulations and analyze the performance under different transmit powers and Rician-factors, which provides a theoretical basis and reference for further research.

• International journal of advanced smart convergence
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• v.9 no.2
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• pp.58-67
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• 2020

In this paper, we propose a data-driven-based beam selection scheme for massive multiple-input and multiple-output (MIMO) systems in ultra-dense networks (UDN), which is capable of addressing the problem of high computational cost of conventional coordinated beamforming approaches. We consider highly dense small-cell scenarios with more small cells than mobile stations, in the millimetre-wave band. The analog beam selection for hybrid beamforming is a key issue in realizing millimetre-wave UDN MIMO systems. To reduce the computation complexity for the analog beam selection, in this paper, two deep neural network models are used. The channel samples, channel gains, and radio frequency beamforming vectors between the access points and mobile stations are collected at the central/cloud unit that is connected to all the small-cell access points, and are used to train the networks. The proposed machine-learning-based scheme provides an approach for the effective implementation of massive MIMO system in UDN environment.

• Journal of Information Processing Systems
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• v.17 no.6
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• pp.1083-1096
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• 2021

Compressed sensing-based matching pursuit algorithms can estimate the sparse channel of massive multiple input multiple-output systems with short pilot sequences. Although they have the advantages of low computational complexity and low pilot overhead, their accuracy remains insufficient. Simply multiplying the weight value and the estimated channel obtained in different iterations can only improve the accuracy of channel estimation under conditions of low signal-to-noise ratio (SNR), whereas it degrades accuracy under conditions of high SNR. To address this issue, an improved weighted matching pursuit algorithm is proposed, which obtains a suitable weight value u_op by training the channel data. The step of the weight value increasing with successive iterations is calculated according to the sparsity of the channel and u_op. Adjusting the weight value adaptively over the iterations can further improve the accuracy of estimation. The results of simulations conducted to evaluate the proposed algorithm show that it exhibits improved performance in terms of accuracy compared to previous methods under conditions of both high and low SNR.

• ETRI Journal
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• v.38 no.2
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• pp.280-290
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• 2016

To implement high-order multiuser multiple input and multiple output (MU-MIMO) for massive MIMO systems, there must be a feedback scheme that can warrant its performance with a limited signaling overhead. The interference-to-noise ratio can be a basis for a novel form of Codebook (CB)-based MU-MIMO feedback scheme. The objective of this paper is to verify such a scheme's performance under a practical system configuration with a 3D channel model in various radio environments. We evaluate the performance of various CB-based feedback schemes with different types of overhead reduction approaches, providing an experimental ground with which to optimize a CB-based MU-MIMO feedback scheme while identifying the design constraints for a massive MIMO system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.628-649
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• 2017

Security and resource-saving are both demands of the fifth generation (5G) wireless networks. In this paper, we study the secrecy spectrum efficiency (SSE) and secrecy energy efficiency (SEE) of a K-tier massive multiple-input multiple-output (MIMO) enabled heterogeneous cellular network (HetNet), in which artificial noise (AN) are employed for secrecy enhancement. Assuming (i) independent Poisson point process model for the locations of base stations (BSs) of each tier as well as that of eavesdroppers, (ii) zero-forcing precoding at the macrocell BSs (MBSs), and (iii) maximum average received power-based cell selection, the tractable lower bound expressions for SSE and SEE of massive MIMO enabled HetNets are derived. Then, the influences on secrecy oriented spectrum and energy efficiency performance caused by the power allocation for AN, transmit antenna number, number of users served by each MBS, and eavesdropper density are analyzed respectively. Moreover, the analysis accuracy is verified by Monte Carlo simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1330-1350
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• 2022

As a preprocessing operation of transmitter antennas, the hybrid precoding is restricted by the limited computing resources of the transmitter. Therefore, this paper proposes a novel hybrid precoding that guarantees the communication efficiency with low complexity and a fast computational speed. First, the analog and digital precoding matrix is derived from the maximum eigenvectors of the channel matrix in the sub-connected architecture to maximize the communication rate. Second, the extended power iteration (EPI) is utilized to obtain the maximum eigenvalues and their eigenvectors of the channel matrix, which reduces the computational complexity caused by the singular value decomposition (SVD). Third, the Aitken acceleration method is utilized to further improve the convergence rate of the EPI algorithm. Finally, the hybrid precoding based on the EPI method and the Aitken acceleration algorithm is evaluated in millimeter-wave (mmWave) massive multiple-input and multiple-output (MIMO) systems. The experimental results show that the proposed method can reduce the computational complexity with the high performance in mmWave massive MIMO systems. The method has the wide application prospect in future wireless communication systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.2047-2066
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• 2024

In order to improve the coverage and achieve massive spectrum access, non-orthogonal multiple access (NOMA) technology is applied in millimeter wave massive multiple-input multiple-output (mMIMO) communication network. However, the power assumption of active sensors greatly limits its wide applications. Recently, Intelligent Reconfigurable Surface (IRS) technology has received wide attention due to its ability to reduce power consumption and achieve passive transmission. In this paper, spectral efficiency maximum problem in the millimeter wave mMIMO-NOMA system with IRS is considered. The sparse RF chain antenna structure is designed at the base station based on continuous phase modulation. Furthermore, a joint optimization problem for power allocation, power splitting, analog precoding and IRS reconfigurable matrices are constructed, which aim to achieve the maximum spectral efficiency of the system under the constraints of user's quality of service, minimum energy harvesting and total transmit power. A three-stage iterative algorithm is proposed to solve the above mentioned non-convex optimization problems. We obtain the local optimal solution by fixing some optimization parameters firstly, then introduce the relaxation variables to realize the global optimal solution. Simulation results show that the spectral efficiency of the proposed scheme is superior compared to the conventional system with phase shifter modulation. It is also demonstrated that IRS can effectively assist mmWave communication and improve the system spectral efficiency.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.688-698
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• 2016

In this paper, we investigate the achievable sum rate and energy efficiency of downlink massive multiple-input multiple-output antenna systems with zero-forcing precoding, by taking into account the randomness of user locations. Specifically, we propose two types of non-uniform user distributions, namely, center-intensive user distribution and edge-intensive user distribution. Based on these user distributions, we derive novel tight lower and upper bounds on the average sum rate. In addition, the impact of user distributions on the optimal number of users maximizing the sum rate is characterized. Moreover, by adopting a realistic power consumption model which accounts for the transmit power, circuit power and signal processing power, the energy efficiency of the system is studied. In particular, closed-form solutions for the key system parameters, such as the number of antennas and the optimal transmit signal-to-noise ratio maximizing the energy efficiency, are obtained. The findings of the paper suggest that user distribution has a significant impact on the system performance: for instance, the highest average sum rate is achieved with the center-intensive user distribution, while the lowest average sum rate is obtained with the edge-intensive user distribution. Also, more users can be served with the center-intensive user distribution.