• Journal of Communications and Networks
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• v.15 no.4
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• pp.383-397
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• 2013

In this paper, the sensitivity of massive antenna arrays and digital beamforming to radio frequency (RF) chain in-phase quadrature-phase (I/Q) imbalance is studied and analyzed. The analysis shows that massive antenna arrays are increasingly sensitive to such RF chain imperfections, corrupting heavily the radiation pattern and beamforming capabilities. Motivated by this, novel RF-aware digital beamforming methods are then developed for automatically suppressing the unwanted effects of the RF I/Q imbalance without separate calibration loops in all individual receiver branches. More specifically, the paper covers closed-form analysis for signal processing properties as well as the associated radiation and beamforming properties of massive antenna arrays under both systematic and random RF I/Q imbalances. All analysis and derivations in this paper assume ideal signals to be circular. The well-known minimum variance distortionless response (MVDR) beamformer and a widely-linear (WL) extension of it, called WL-MVDR, are analyzed in detail from the RF imperfection perspective, in terms of interference attenuation and beamsteering. The optimum RF-aware WL-MVDR beamforming solution is formulated and shown to efficiently suppress the RF imperfections. Based on the obtained results, the developed solutions and in particular the RF-aware WL-MVDR method can provide efficient beamsteering and interference suppressing characteristics, despite of the imperfections in the RF circuits. This is seen critical especially in the massive antenna array context where the cost-efficiency of individual RF chains is emphasized.

• ETRI Journal
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• v.41 no.3
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• pp.298-307
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• 2019

This paper investigates the use of the inverse-free sparse Bayesian learning (SBL) approach for peak-to-average power ratio (PAPR) reduction in orthogonal frequency-division multiplexing (OFDM)-based multiuser massive multiple-input multiple-output (MIMO) systems. The Bayesian inference method employs a truncated Gaussian mixture prior for the sought-after low-PAPR signal. To learn the prior signal, associated hyperparameters and underlying statistical parameters, we use the variational expectation-maximization (EM) iterative algorithm. The matrix inversion involved in the expectation step (E-step) is averted by invoking a relaxed evidence lower bound (relaxed-ELBO). The resulting inverse-free SBL algorithm has a much lower complexity than the standard SBL algorithm. Numerical experiments confirm the substantial improvement over existing methods in terms of PAPR reduction for different MIMO configurations.

• Journal of Communications and Networks
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• v.18 no.1
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• pp.95-104
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• 2016

Massive multiple-input multiple-output (MIMO) is a promising approach for cellular communication due to its energy efficiency and high achievable data rate. These advantages, however, can be realized only when channel state information (CSI) is available at the transmitter. Since there are many antennas, CSI is too large to feed back without compression. To compress CSI, prior work has applied compressive sensing (CS) techniques and the fact that CSI can be sparsified. The adopted sparsifying bases fail, however, to reflect the spatial correlation and channel conditions or to be feasible in practice. In this paper, we propose a new sparsifying basis that reflects the long-term characteristics of the channel, and needs no change as long as the spatial correlation model does not change. We propose a new reconstruction algorithm for CS, and also suggest dimensionality reduction as a compression method. To feed back compressed CSI in practice, we propose a new codebook for the compressed channel quantization assuming no other-cell interference. Numerical results confirm that the proposed channel feedback mechanisms show better performance in point-to-point (single-user) and point-to-multi-point (multi-user) scenarios.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1098-1112
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• 2018

Achievable sum rate and energy efficiency (EE) are investigated for the massive multiple-input multiple-output (Massive MIMO) downlink with channel aging in the time varying Ricean fading channel. Specifically, the expression of the achievable sum rate of the system for the maximum ratio transmission (MRT) precoder with aged channel state information (CSI) in the time varying Ricean fading channel is first presented. Based on the expression, the effect of both channel aging and the Ricean factor on the power scaling law are studied. It is found that the transmit power of base station (BS) is scaled down by $1/{\sqrt{M}}$(where M is the number of the BS antennas) when the Ricean factor K is equal to zero (i.e., time varying Rayleigh fading channel), indicating that aged CSI does not affect the power scaling law. However, the transmit power of the BS is scaled down by 1/M for the time varying Ricean fading channel (where $K{\neq}0$) indicating that the Ricean factor affects the power scaling law and sum rate, and channel aging only leads to a reduction of the sum rate. Second, the EE of the system is analyzed based on the general power consumption model. Both the theoretical analysis and the simulations show that the channel aging could degrade the sum rate and the EE of the system, and it does not affect the power scaling law.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.9
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• pp.861-869
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• 2014

This paper shows the research of a platform architecture relates to the LTE-based macro basestation; the proposed platform architecture is designed with the interface between the baseband signal and IF (Intermediate Frequency) per codeword. Using this method, we can smoothly transmit/receive a large amounts of data regardless of the number of antenna in a macro base station which is used technology such as massive MIMO. In this paper, We analyzed the evolution of LTE technology and the trend in the development of the LTE-based system. For validation of the proposed architecture, we compare the general architecture of a conventional with the proposed architecture. From the calculation results of transmission quantity data, we see that the proposed architecture can give better performance than the existing architecture. By presenting this architecture, we hope to provide a new foundation for Design and Implementation of a LTE base station platform which is used technology such as massive MIMO, carrier aggregation (CA), coordinated multi point (CoMP).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1559-1565
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• 2021

In this paper, an antenna selection scheme is proposed in massive multi-user multiple input multiple output (MU-MIMO) systems. The proposed antenna selection scheme can achieve almost the same performance as a conventional scheme while significantly reducing the overhead of feedback by using deep reinforcement learning (DRL). Each user compares the channel gains of massive antennas in base station (BS) to the L-largest channel gain, converts them to one-bit binary numbers, and feed them back to BS. Thus, the feedback overhead can be significantly reduced. In the proposed scheme, DRL is adopted to prevent the performance loss that might be caused by the reduced feedback information. We carried out extensive Monte-Carlo simulations to analyze the performance of the proposed scheme and it was shown that the proposed scheme can achieve almost the same average sum-rates as a conventional scheme that is almost optimal.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.1042-1058
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• 2024

Terahertz (THz) communication is becoming a key technology for future 6G wireless networks because of its ultra-wide band. However, the implementation of THz communication systems confronts formidable challenges, notably beam splitting effects and high computational complexity associated with them. Our primary objective is to design a hybrid precoder that minimizes the Euclidean distance from the fully digital precoder. The analog precoding part adopts the delay-phase alternating minimization (DP-AltMin) algorithm, which divides the analog precoder into phase shifters and time delayers. This effectively addresses the beam splitting effects within THz communication by incorporating time delays. The traditional digital precoding solution, however, needs matrix inversion in THz massive multiple-input multiple-output (MIMO) communication systems, resulting in significant computational complexity and complicating the design of the analog precoder. To address this issue, we exploit the characteristics of THz massive MIMO communication systems and construct the digital precoder as a product of scale factors and semi-unitary matrices. We utilize Schatten norm and Hölder's inequality to create semi-unitary matrices after initializing the scale factors depending on the power allocation. Finally, the analog precoder and digital precoder are alternately optimized to obtain the ultimate hybrid precoding scheme. Extensive numerical simulations have demonstrated that our proposed algorithm outperforms existing methods in mitigating the beam splitting issue, improving system performance, and exhibiting lower complexity. Furthermore, our approach exhibits a more favorable alignment with practical application requirements, underlying its practicality and efficiency.

• ETRI Journal
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• v.45 no.5
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• pp.899-909
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• 2023

In mobile communication, the most exploratory technology of fifth generation is massive multiple input multiple output (MIMO). The minimum mean square error and zero forcing based linear detectors are used in multiuser detection for MIMO single-carrier frequency division multiple access (SCFDMA). When the received signal is detected and regularization sequence is joined in the equalization of spectral null amplification, these schemes experience an error performance and the signal detection assesses an inversion of a matrix computation that grows into complexity. Ordered successive interference cancelation (OSIC) detection is considered for MIMO SC-FDMA, which uses a posteriori information to eradicate these problems in a realistic environment. To cancel the interference, sorting is preferred based on signal-to-noise ratio and log-likelihood ratio. The distinctiveness of the methodology is to predict the symbol with the lowest error probability. The proposed work is compared with the existing methods, and simulation results prove that the defined algorithm outperforms conventional detection methods and accomplishes better performance with lower complication.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.4
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• pp.628-636
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• 2015

In this paper, we propose a non-convex compressed sensing(NCCS)-based channel state information(CSI) feedback scheme for massive multiple-input multiple-output(MIMO) systems. Combining the random vector quantization(RVQ), the proposed scheme permits a transmitter to obtain CSI with acceptable accuracy under substantially reduced feedback load. Furthermore, it recovers CSI from fewer measurements than that of existing convex compressed sensing(CCS)-based schemes even if the measurements are inaccurate and incomplete. Simulation results show that the proposed scheme achieves higher throughput than both existing CCS-based feedback scheme and random vector quantization(RVQ) feedback scheme with the same feedback load.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.49-55
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• 2022

In the next generation mobile communication systems, hybrid massive multiple-input multiple output (MIMO) can be used to highly improve an achievable rate without increasing the number of RF chains. Recently, successive-interference-cancellation (SIC) based hybrid precoder design scheme was proposed to reduce the complexity. However, since this scheme uses simple diagonal matrix for baseband precoding, it cannot solve an interference problem between the transmitted streams. Also, there is a limitation for improving the data rate because of the use of one phase shifter for analog precoding. To solve these problems, in this paper we propose a digital precoding based on the SVD of the effective channel and an analog precoding using two phase shifters. Through simulation, we show that the proposed scheme has better achievable rate and SINR performances than the conventional one.