• Journal of information and communication convergence engineering
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• v.4 no.4
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• pp.151-154
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• 2006

In this work, a novel optimal multiuser detection (MUD) approach, which not only achieves the optimal maximum-likelihood (ML)-like performance but also has reasonably low computational complexity, for Space-time coded OFDM (ST-OFDM) systems is presented. In the proposed detection scheme, the signal model is firstly re-expressed into linearly equivalent one. Then, with the linearly equivalent signal model, a new jointly MUD algorithm is proposed to detect signals. The ML-like bit-error-rate (BER) performance and reasonably low complexity of the proposed detection are verified by computer simulations.

• 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.

• Current Optics and Photonics
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• v.1 no.4
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• pp.289-294
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• 2017

A high-performance time-division multiplexing (TDM) -based multiuser (MU) multiple-input multipleoutput (MIMO) system for efficient indoor visible-light communication (VLC) is presented. In this work, a MIMO technique based on RGB light-emitting diodes (LEDs) with selection combining (SC) is utilized for data transmission. That is, the proposed scheme employs RGB LEDs for parallel transmission of user data and transmits MU data in predefined slots of a time frame with a simple and efficient design, to schedule the transmission times for multiple users. Simulation results demonstrate that the proposed scheme offers an approximately 6 dB gain in signal-to-noise ratio (SNR) at a bit error rate (BER) of $3{\times}10^{-5}$, as compared to conventional MU single-input single-output (SISO) systems. Moreover, a data rate of 66.7 Mbps/user at a BER of $10^{-3}$ is achieved for 10 users in indoor VLC environments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.8
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• pp.2607-2625
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• 2014

Previous studies on multiuser multiple-input multiple-output (MIMO) mostly assume a homogeneous signal-to-noise ratio (SNR), where each user has the same average SNR. However, real networks are more likely to feature heterogeneous SNRs (a random-valued average SNR). Motivated by this fact, we analyze a multiuser MIMO downlink with a zero-forcing (ZF) receiver in a heterogeneous SNR environment. A transmitter with Mantennas constructs M orthonormal beams and performs the SNR-based proportional fairness (S-PF) scheduling where data are transmitted to users each with the highest ratio of the SNR to the average SNR per beam. We develop a new analytical expression for the sum throughput of the multiuser MIMO system. Furthermore, simply modifying the expression provides the sum throughput for important special cases such as homogeneous SNR, max-rate scheduling, or high SNR. From the analysis, we obtain new insights (lemmas): i) S-PF scheduling maximizes the sum throughput in the homogeneous SNR and ii) under high SNR and a large number of users, S-PF scheduling yields the same multiuser diversity for both heterogeneous SNRs and homogeneous SNRs. Numerical simulation shows the interesting result that the sum throughput is not always proportional to M for a small number of users.

• Journal of Satellite, Information and Communications
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• v.6 no.1
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• pp.19-27
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• 2011

In this paper, we propose the data stream allocation algorithms for maximizing sum capacity of downlink multiuser MIMO (Multiple-input Multiple-output) systems with BD (Block Diagonalization). The conventional BD precoding algorithms maximize the capacity by controlling power against channel gain of each user. In multiuser MIMO systems, however, the number of data streams for each user can be used to as another control parameter, which determines the capacity. This paper proposes the data stream allocation algorithm of BD for increasing capacity in multiuser MIMO systems. The proposed algorithm allocates unequal bit stream to each user based on channel matrix of each user for maximizing sum capacity. It is proved that proposed algorithm can achieve the significantly improved sum capacity by computer simulation.

• Journal of Advanced Navigation Technology
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• v.13 no.5
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• pp.736-741
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• 2009

In this paper, adaptive optimizations of precoder codebook to channel conditions is proposed for a multiuser multiple-input multiple-output (MIMO) system with split linear array and limited feedback. We propose adaptive method for constructing a precoder codebook by coloring the random vector quantization codebook at each link by using limited long-term feedback information on transmit correlation matrix of each link. It is shown that the proposed multiuser MIMO codebook design scheme outperforms existing multiuser MIMO codebook design schemes for various channel conditions in terms of the average sum throughput of multiuser MIMO systems using zero-forcing maximum eigenmode transmission and limited feedback.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3010-3025
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• 2016

Lattice reduction (LR) has been used widely in conventional multiple-input multiple-output (MIMO) systems to enhance the performance. However, LR is hard to be applied to the relay systems which are important but more complicated in the wireless communication theory. This paper introduces a new viewpoint for utilizing LR in multiuser MIMO relay systems. The vector precoding (VP) is designed along with zero force (ZF) criterion and minimum mean square error (MMSE) criterion and enhanced by LR algorithm. This implementable precoder design combines nonlinear processing at the base station (BS) and linear processing at the relay. This precoder is capable of avoiding multiuser interference (MUI) at the mobile stations (MSs) and achieving excellent performance. Moreover, it is shown that the amount of feedback information is much less than that of the singular value decomposition (SVD) design. Simulation results show that the proposed scheme using the complex version of the Lenstra--Lenstra--Lovász (LLL) algorithm significantly improves system performance.

• 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 Communications and Networks
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• v.15 no.4
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• pp.352-361
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• 2013

Combining multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) with a massive number of transmit antennas (massive MIMO-OFDM) is an attractive way of increasing the spectrum efficiency or reducing the transmission energy per bit. The effectiveness of Massive MIMO-OFDM is strongly affected by the channel state information (CSI) estimation method used. The overheads of training frame transmission and CSI feedback decrease multiple access channel (MAC) efficiency and increase the CSI estimation cost at a user station (STA). This paper proposes a CSI estimation scheme that reduces the training frame length by using a novel pilot design and a novel unitary matrix feedback method. The proposed pilot design and unitary matrix feedback enable the access point (AP) to estimate the CSI of the signal space of all transmit antennas using a small number of training frames. Simulations in an IEEE 802.11n channel verify the attractive transmission performance of the proposed methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.11A
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• pp.1027-1037
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• 2010

In this paper, we propose the linear interpolation-based BD (Block Diagonalization) precoding approximation algorithm for low complexity in downlink multiuser MIMO-OFDM (Multiple-input Multiple-output Orthogonal Frequency Division Multiplexing) systems. In the case of applying the general BD precoding algorithm to multiuser MIMO-OFDM systems, the computational complexity increases in proportional to the number of subcarriers. The proposed interpolation-based BD precoding approximation algorithm can be achieved similar SER performance with general BD algorithm and can decrease the computational complexity. It is proved that proposed algorithm can achieve the significantly decreased computational complexity by computer simulation.