• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.9A
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• pp.1022-1030
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• 2004

The next generation cellular radio systems require high data rate transmission and large system capacity In order to meet these requirements, multiple antennas can be used at the base and mobile stations, forming MIMO(multiple-input, multiple-output) channels This paper considers a downlink MIMO system assuming a large number of base station antennas, a small number of mobile station antennas, and rich-scattering, quasi-stationary, and flat-fading channel environments When the channel state information is given at the base station in a single user system, a MIMO technique with SVD(singular value decomposition) and water-filling can achieve the maximal downlink channel capacity. In multi-user environments, however, SDMA(space division multiple acces) technique can be used to further increase the total channel capacity supported by the base station This paper proposes a MIMO SDMA technique which can transmit parallel data streams to each of multiple users. The proposed method. can achieve higher total channel capacity than SVD-based MIMO techniques or conventional SDMA using smart antennas.

• Journal of Communications and Networks
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• v.5 no.2
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• pp.104-115
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• 2003

It is well known that Multiple Input Multiple Output (MIMO) systems offer the promise of achieving very high spectrum efficiencies (many tens of bit/s/Hz) in a mobile environment. The gains in MIMO capacity are sensitive to the presence of spatial and temporal correlation introduced by the radio environment. In this paper, we examine how MIMO capacity is influenced by a number of factors e.g., a) temporal correlation b) various combinations of low/high spatial correlations at either end, c) combined spatial and temporal correlations. In all cases, we compare the channel capacity that would be achievable under independent fading. We investigate the behaviour of "capacity fades," examine how often the capacity experiences the fades, develop a method to determine level crossing rates and average fade durations and relate these to antenna numbers. We also evaluate the influence of channel correlation on the capacity autocorrelation and assess the fit of a Gaussian random process to the temporal capacity sequence. Finally we note that the particular spatial correlation structure of the MIMO channel is influenced by a large number of factors. For simplicity, it is desirable to use a single overall correlation measure which parameterizes the effect of correlation on capacity. We verify this single parameter concept by simulating a large number of different spatially correlated channels.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.8
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• pp.63-68
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• 2004

The capacity of MIMO systems is numerically analyzed when channel estimation error exists. The analysis shows that the capacity is influenced by Mean Square Error (MSE) as well as average Signal to Noise Ratio (SNR). Furthermore, in this paper we present the standard selecting a channel estimator suitable to a system owing to get a tolerable channel estimation error in a given average SNR and channel capacity loss. The simulation results show that the tolerable MSEs for 1 bps/Hz capacity loss are about 10$^{-2}$ and 10$^{-4}$ at n dB and 40 dB average SNR, respectively.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.3 s.106
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• pp.267-271
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• 2006

In this paper, we use the OFDM transmission channel model applied to the MIMO antennas considering spatial propagation property to evaluate and investigate the ergodic capacity of the channel. Specially, we have applied our results to 3GPP TR 25.99 V1.1.0 case 1 LOS off channel description and calculated ergodic capacity with parameters, cluster angle spread and angle of arrival(AOA). Our results show that as the cluster angle spread increase the channel capacity increase until 35 degree, but for more than 35 degree channel capacity does not improved.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.47-50
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• 2008

Multiple-input multiple-output (MIMO) is an efficient technology to increase data rate in wireless networks due to bandwidth and power limitations. Data transmission rate between transmitter and receiver is determined by channel capacity. MIMO has anadvantage of reliable communication over wireless channel because of utilizing the channel capacity properly. In this letter, we drive a new formula, closed form capacity formula, using confluent hypergeometric function.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2003.11a
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• pp.43-46
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• 2003

This paper presents capacity characteristics of the indoor LOS(Line-Of-Sight) propagation channel for MIMO system at 5GHz. The distance between antenna elements, their moving path, and number of transmitting and receiving antennas can be determined by wanted eigen-vlaue, and channel capacity of the MIMO communication channel using only reliable simulation without measurements. The simulation uses 3D Ray tracing and patch scattering model to which electromagnetic material constants are applied. As distance between antenna elements increases, distribution of the eigen-value show a tendency to decrease, but channel capacity increases in LOS environment. However, despite of short distance between antenna elements, large value of channel capacity is obtained in positions which have high AS. When the position of receiver antennas are shifted, channel capacity hardly changed, and as number of antenna elements increases, channel capacity also increases regularly.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.5
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• pp.723-729
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• 2011

In this paper, we simulate and evaluate the performance of MIMO systems adopting MMSE-OSUC receiver algorithm under Rayleigh fading channel environment. In the simulation, BPSK, QPSK, 16QAM, and 64QAM modulation is used with frame length of 100 symbols. First, the concept of MIMO is introduced by the analytical basis of the channel capacity of MIMO system. From the performance analysis results, the channel capacity is identified by the function of channel and it is affected by the channel characteristic. Next, based on this approach, the algorithm for performance evaluation over MIMO channel was analyzed. From the performance analysis results, it is found that MMSE-OSUC receiver algorithm generally outperform conventional ZF-OUSC receiver algorithm in performance but the performance difference between the two algorithms is reduced as modulation scheme with larger constellation point is used.

• 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 information and communication convergence engineering
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• v.3 no.4
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• pp.172-175
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• 2005

In this paper, a new method to get the optimum channel capacity of a Multiple-Input Multiple­Output (MIMO) system is presented. The proposed method exploits the diagonal structure of channel matrix to maximize the channel capacity. The diagonal format of the channel matrix is formed by multiplying the transmitted signal with the pre-compensated channel PCC) matrix. Numerical simulations show that the proposed method exploiting the diagonal structure of channel matrix could significantly increase the system capacity compared with the system without applying the diagonal structure of channel matrix.

• Journal of Communications and Networks
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• v.15 no.4
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• pp.338-351
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• 2013

Multiple-input multiple-output (MIMO) communication may provide high spectral efficiency through the deployment of a very large number of antenna elements at the base stations. The gains from massive MIMO communication come from the use of multi-user MIMO on the uplink and downlink, but with a large excess of antennas at the base station compared to the number of served users. Initial work on massive MIMO did not fully address several practical issues associated with its deployment. This paper considers the impact of channel aging on the performance of massive MIMO systems. The effects of channel variation are characterized as a function of different system parameters assuming a simple model for the channel time variations at the transmitter. Channel prediction is proposed to overcome channel aging effects. The analytical results on aging show how capacity is lost due to time variation in the channel. Numerical results in a multicell network show that massive MIMO works even with some channel variation and that channel prediction could partially overcome channel aging effects.