• Journal of Communications and Networks
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• v.16 no.1
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• pp.1-9
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• 2014

Block diagonalization (BD) has been proposed as a simple and effective technique in multiuser multiple-input multiple-output (MU-MIMO) broadcast channels. However, when channel state information (CSI) knowledge is limited at the transmitter, the performance of the BD may be degraded because inter-user interference cannot be completely eliminated. In this paper, we propose an efficient CSI quantization technique for BD precoded systems with limited feedback where users supported by a base station are selected by dynamic scheduling. First, we express the received signal-to-interference-plus-noise ratio (SINR) when multiple data streams are transmitted to the user, and derive a lower bound expression of the expected received SINR at each user. Then, based on this measure, each user determines its quantized CSI feedback information which maximizes the derived expected SINR, which comprises both the channel direction and the amplitude information. From simulations, we confirm that the proposed SINR-based channel quantization scheme achieves a significant sum rate gain over the conventional method in practical MU-MIMO systems.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2406-2412
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• 2015

Multi-user multi-input multi-output (MU-MIMO) system has attracted the 4^th generation wireless network as one of core technique for performance enrichment. In this system rate control is a challenging problem and another problem is optimization. Proper scheduling can resolve these problems by deciding which set of user and at which rate the users send their data. This paper proposes a new multi-parameter based scheduling (MPS) for downlink multi-user multiple-input multiple-output (MU-MIMO) system under space-time block coding (STBC) transmissions. Goal of this MPS scheme is to offer improved link level performance in terms of a low average bit error rate (BER), high packet delivery ratio (PDR) with improved resource utilization and service fairness among the user. This scheme allows the set of users to send data based on their channel quality and their demand rates. Simulation compares the MPS performance with other scheduling scheme such as fair scheduling (FS), normalized priority scheduling (NPS) and threshold based fair scheduling (TFS). The results obtained prove that MPS has significant improvement in average BER performance with improved resource utilization and fairness as compared to the other scheduling scheme.

• 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.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.99-105
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• 2012

Recently, there are many user selection algorithms in multi user multiple-input multiple-output (MU-MIMO) systems. One of well-known user selection methods is Semi orthogonal user selection (SUS). It is an algorithm maximizing channel capacity. However, it is applicable only when user's antenna is one. We propose a generalized user selection algorithm regardless of the number of user's antennas. In the proposed scheme, Base station (Bs) selects the first user who has the highest determinant of channel and generates a user group that correlation with first user's channel is less than allowance of correlation. Then, each determinant of channels made up of first user's channel and a user's channel in the generated group is calculated and BS selects the next user who has the highest determinant of that. BS selects following users by repeating above procedure. In this paper, we get better performance because of selecting users who have the highest determinant of channel as well as allowance of correlation optimally calculated through matrix operations.

• Journal of Communications and Networks
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• v.13 no.3
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• pp.232-239
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• 2011

This paper investigates the user selection problem of successive zero-forcing precoded multiuser multiple-input multiple-output (MU-MIMO) downlink systems, in which the base station and mobile receivers are equipped with multiple antennas. Assuming full knowledge of the channel state information at the transmitter, dirty paper coding (DPC) is an optimal precoding strategy, but practical implementation is difficult because of its excessive complexity. As a suboptimal DPC solution, successive zero-forcing DPC (SZF-DPC) was recently proposed; it employs partial interference cancellation at the transmitter with dirty paper encoding. Because of a dimensionality constraint, the base station may select a subset of users to serve in order to maximize the total throughput. The exhaustive search algorithm is optimal; however, its computational complexity is prohibitive. In this paper, we develop two low-complexity user scheduling algorithms to maximize the sum rate capacity of MU-MIMO systems with SZF-DPC. Both algorithms add one user at a time. The first algorithm selects the user with the maximum product of the maximum column norm and maximum eigenvalue. The second algorithm selects the user with the maximum product of the minimum column norm and minimum eigenvalue. Simulation results demonstrate that the second algorithm achieves a performance similar to that of a previously proposed capacity-based selection algorithm at a high signal-to-noise (SNR), and the first algorithm achieves performance very similar to that of a capacity-based algorithm at a low SNR, but both do so with much lower complexity.

• 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.33 no.1C
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• pp.79-85
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• 2008

Dirty Paper Coding(DPC) can achieve the sum capacity of a multiuser multiple-input multiple-output(MU MIMO) broadcast channels. However, due to the high computational complexity of the successive encoding and decoding, deploying DPC in real systems is impractical. As one of practical alternatives to DPC, Block Diagonalization(BD) was researched. BD is an extension of the zero-forcing preceding technique that eliminates interuser interference(IUI) in downlink MIMO systems. Though BD has lower complexity than DPC, BD shows poor sum capacity performance. We show that sum capacity performance of BD is degraded due to no IUI constraint. Then, we modify BD to improve its sum capacity performance with relaxing the constraint and sub optimal channel set searching. With simulation results, it can be verified that our modification in BD induces some improvement in sum capacity performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.7
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• pp.1597-1601
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• 2013

Multiple antenna technique is attracting attention as a core technology for next-generation mobile communication systems to accommodate explosively increasing mobile data traffic. Especially, recent researches focus on multi-user multiple input multiple output (MU-MIMO) system where base stations are equipped with several tens of transmit antennas and transmit data to multiple terminals (users) simultaneously. To enhance the performance of MU-MIMO systems, we, in this paper, propose an adaptive user selection algorithm which adaptively selects a user set according to varying channel states. According to Monte-Carlo based computer simulations, the performance of proposed scheme is significantly improved compared to the conventional scheme without user selection and approaches that of exhaustive search-based optimal scheme. On the other hand, the proposed scheme can reduce the computational complexity to $K/(2^K-1)$ compared to the optimal scheme where K denotes the number of total users.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.9A
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• pp.673-678
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• 2009

This paper presents a feedback method for improving the system capacity of MU-MIMO system for downlink channel environments. In a typical conventional feedback method, CVQ, in order to enhance the channel capacity, not only the feedback load is increased but also the quantization of the channel vector is increased, because the channel parameter of each user has to be fed back after quantizing one of the pre-defined N-codebook vectors. In this paper, a novel feedback method is proposed which provides an improved system capacity by transferring the channel state information without increasing the feedback load. Performance of the proposed method is compared to the conventional CVQ method through computer simulations. The simulation results show that the proposed method with 3-bit feedback provides a system capacity comparable to the CVQ method of 6-bit feedback when the number of transmit antennas is 2.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.75-82
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• 2018

In this paper, we consider a precoder design for downlink multiuser multiple-input multiple-output (MU-MIMO) in distributed antenna systems (DAS). In DAS, remote radio heads (RRHs) are placed at geographically different locations within a cell area. Three different precoder design schemes are proposed to maximize the separate or joint signal-to-leakage-plus-noise ratio (SLNR) metrics by considering RRH sum power or per-RRH power constraints. The analytical closed-form form solution for each optimization problem is presented. Through computer simulation, we show that the joint SLNR based precoding schemes have better signal-to-interference-plus-noise ratio (SINR) and bit error rate (BER) performances than the separate SLNR based schemes. Also, it is shown that the precoding scheme with RRH sum power constraint has better performance than the precoding scheme with per-RRH power constraint.