• Journal of Advanced Marine Engineering and Technology
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• v.39 no.3
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• pp.280-285
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• 2015

We consider a linear transceiver design method for multi-user multiple-input multiple-output (MIMO) downlink channels where a base station (BS) equipped with a finitely large number of antennas. Although a matched-filter precoder is a capacity-achieving method in massive MIMO downlink systems, it cannot guarantee to achieve the multi-user MIMO capacity in a finitely large number of antennas due to inter-user interferences. In this paper, we propose a two-stage precoder design method that maximizes the sum-rate of cell-edge users when the BS equipped with a finitely large number of antennas. At the first stage, a matched-filter precoder is adopted to exploit both beamforming gain and the reduction of the dimension of effective channels. Then, we derive the second stage precoder that maximizes the sum-rate by minimizing the weighted mean square error (WMSE). From simulation and analysis, we verify the effectiveness of the proposed method.

• 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.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.21-29
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• 2014

Due to enormous number of user and limited memory space, the memory saving is become an important issue for big data service these days. In the large scaled multiple-input multiple-output (MIMO) system, the Teoplitz channel can play the significance rule to improve the performance as well as power efficiency. In this paper, we propose a Toeplitz channel decomposition based on matrix vectorization. Here we use Toeplitz matrix to the channel for large scaled MIMO system. And we show that the Toeplitz Jacket matrices are decomposed to Cooley-Tukey sparse matrices like fast Fourier transform (FFT).

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.11
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• pp.33-39
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• 2014

We propose an optimal number of transmit antennas which maximizes energy-efficiency (EE) in multi-user massive multiple-input multiple-output (MIMO) downlink system with the maximal ratio transmission (MRT) precoding. With full channel state information at the transmitter (CSIT), we find a closed form solution by partial differential function with proper approximations using average channel gain, independence of individual channels, and average path loss. With limited feedback, we get a solution numerically by the bisection with approximations in the same manner, and analyze an effect of feedback bits on the optimal number of transmit antennas. Simulation results show that the optimal numbers of transmit antenna getting from proposed closed form solution and exhaustive search are nearly same.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.7
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• pp.723-731
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• 2016

A core technological base to provide enhanced data rates required by 5G mobile wireless communications is the improved bandwidth efficiency using massive multiple-input multiple-output (MIMO) transmission. MIMO transmission requires the channel estimation using the channel state information reference signaling (CSI-RS) and appropriate beamforming, thus the design of the codebook defining proper beamforming vectors is an important issue. In this paper, we propose a multi-rank codebook based on the discrete Fourier transform (DFT) matrix, by utilizing statistical properties of the channel generated by the spatial channel model (SCM). The proposed method includes a structural change of the precoding matrix indicator (PMI) by considering the phase difference distributions between adjacent antenna elements, as well as the selected codevector characteristics of each transmission layer. Performance gain of the proposed method is evaluated and verified by making the performance comparison to the 3GPP standard codebooks adopted by Long-Term Evolution (LTE) systems.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.3
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• pp.1047-1062
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• 2018

In this paper the problem of massive multiple input multiple output (MIMO) channel estimation with sparsity aware adaptive algorithms for $5^{th}$ generation mobile systems is investigated. These channels are shown to be non-stationary along with being sparse. Non-stationarity is a feature that implies channel taps change with time. Up until now most of the adaptive algorithms that have been presented for channel estimation, have only considered sparsity and very few of them have been tested in non-stationary conditions. Therefore we investigate the performance of several newly proposed sparsity aware algorithms in these conditions and finally propose an enhanced version of RZA-LMS/F algorithm with variable threshold namely VT-RZA-LMS/F. The results show that this algorithm has better performance than all other algorithms for the next generation channel estimation problems, especially when the non-stationarity gets high. Overall, in this paper for the first time, we estimate a non-stationary Rayleigh fading channel with sparsity aware algorithms and show that by increasing non-stationarity, the estimation performance declines.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.3-9
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• 2015

Under the maximum transmit power constraint and the minimum rate constraint, we propose the optimal number of transmit antennas and transmit power which maximize energy-efficiency (EE) in multi-user multiple-input multiple-output (MIMO) downlink system with the maximal ratio transmission (MRT) precoding. Because the optimization problem for the instantaneous channel is difficult to solve, we use independence of individual channel, average channel gain and path loss to approximate the objective function. Since the approximated EE optimization problem is two-dimensional search problem, we find the optimal number of transmit antennas and transmit power using Lagrange multipliers and our proposed algorithm. Simulation results show that the number of transmit antennas and power obtained by proposed algorithm are almost identical to the value by the exhaustive search.