• Journal of electromagnetic engineering and science
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• v.9 no.3
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• pp.124-129
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• 2009

Although the maximum sum-rate capacity of multiple-input multiple output(MIMO) broadcast channels(BCs) can be achieved by dirty-paper coding(DPC), the results were obtained without fairness considerations in uncorrelated MIMO channels. In this paper, we propose new multiuser scheduling algorithms, which find a best user set for approaching the maximum sum-rate capacity while maintaining fairness among users. We analyze the performance of the proposed algorithms using zero-forcing dirty paper coding(ZF-DPC) in the correlated MIMO BCs for throughput and delay fairness, respectively. Numerical results demonstrate that a large time window can reduce the average throughput difference between users, but it increases head-of-line(HOL) delay jitters in the case of delay fairness.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.7
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• pp.23-28
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• 2010

We propose a reference vector diversity method in multi-cell multi-user uplink system with the subspace interference alignment to obtain higher sum rate capacity. The proposed method transmits several reference vectors before the data transmission, and selects the best reference vector to maximize the cell sum rate. The proposed method provides higher sum-rate capacity compared with the previous interferenc alignment. Simulation result exhibits the proposed method improves the sum-rate capacity by 60%.

• Journal of Communications and Networks
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• v.10 no.2
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• pp.186-193
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• 2008

A two-hop multiple-input multiple-output (MIMO) relay network which comprises a multiple antenna source, an amplify-and-forward MIMO relay and many potential users are studied in this paper. Consider the achievable sum rate as the performance metric, a joint design method for the processing units of the BS and relay node is proposed. The optimal structures are given, which decompose the multiuser MIMO relay channel into several parallel single-input single-output relay channels. With these structures, the signal-to-noise ratio at the destination users is derived; and the power allocation is proved to be a convex problem. We also show that high sum rate can be achieved by pairing each link according to its magnitude. The sum rate of three broadcast strategies, time division multiple access (TDMA) to the strongest user, dirty paper coding (DPC), and beamforming (BF) are investigated. The sum rate bounds of these strategies and the sum capacity (achieved by DPC) gain over TDMA and BF are given. With these results, it can be easily obtained that how far away TDMA and BF are from being optimal in terms of the achievable sum rate.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.109-110
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• 2007

The sum-rate capacity of multi-antenna broadcast channels recently has attracted much research interests. However, those effort mainly has focused on a single-cell system. In this paper, we consider a multi-cell system where a transmitter uses zero-forcing beamforming with multiple antennas. We select a linear zero-forcing weight that maximizes the sum-rate when intercell interference exists. With numerical investigation, we will show the sum-rate gain achieved by the proposed method gets larger when the number of interfering cells increases.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.10C
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• pp.936-941
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• 2003

Density evolution was developed as a method for computing the capacity of low-density parity-check(LDPC) codes under the sum-product algorithm [1]. Based on the assumption that the passed messages on the belief propagation model can be approximated well by Gaussian random variables, a modified and simplified version of density evolution technique was introduced in [2]. Recently, the min-sum algorithm was applied to the density evolution of LDPC codes as an alternative decoding algorithm in [3]. Next question is how the min-sum algorithm is combined with a Gaussian approximation. In this paper, the capacity of various rate LDPC codes is obtained using the min-sum algorithm combined with the Gaussian approximation, which gives a simplest way of LDPC code analysis. Unlike the sum-product algorithm, the symmetry condition [4] is not maintained in the min-sum algorithm. Therefore, the variance as well as the mean of Gaussian distribution are recursively computed in this analysis. It is also shown that the min-sum threshold under a gaussian approximation is well matched to the simulation results.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.3
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• pp.77-85
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• 2018

Multi-User Multiple-Input Multiple-Output (MU-MIMO) is the core technology for improving the channel capacity compared to Single-User MIMO (SU-MIMO) by using multiuser gain and spatial diversity. Key problem for the MU-MIMO is the user selection which is the grouping the users optimally. To solve this problem, we adopt Extreme Value Theory (EVT) at the beginning of the proposed algorithm, which defines a primary user set instead of a single user that has maximum channel power according to a predetermined threshold. Each user in the primary set is then paired with all of the users in the system to define user groups. By comparing these user groups, the group that produces a maximum sum rate can be determined. Through computer simulations, we have found that the proposed method outperforms the conventional technique yielding a sum rate that is 0.81 bps/Hz higher when the transmit signal to noise ratio (SNR) is 30 dB and the total number of users is 100.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.10
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• pp.956-964
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• 2012

An opportunistic interference alignment based on dynamic cell selection is proposed. Since the proposed method can switch the desired signal space and the interference space of received signals, an additional selective diversity gain increases. The performance analysis using probabilistic models provides a mathematical expression for the sum-rate capacity. Simulation examples show that the proposed method achieves the higher sum-rate capacity than that of the conventional opportunistic interference alignment.

• ETRI Journal
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• v.38 no.1
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• pp.62-69
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• 2016

In this paper, we propose two novel user selection algorithms for multiuser multiple-input and multiple-output downlink wireless systems, in which both a base station (BS) and mobile stations (MSs) are equipped with multiple antennas. Linear transmit beamforming at the BS and receive combining at the MSs are used to avoid interference between users and find a better sum-rate capacity performance. An optimal technique for selecting users would entail an exhaustive search, which in practice becomes computationally complex for a realistic number of users. Suboptimal algorithms with low complexity are proposed for a coordinated beamforming scheme. Simulation results show that the performance of the proposed algorithms is better than that provided by previous algorithms and is very close to an optimal approach with reduced complexity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.3A
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• pp.238-244
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• 2010

We propose a user selection method in multi-cell multiuser uplink system with the subspace interference alignment to maintain the high sum-rate capacity. The proposed method selects users whose interference to adjacent cells are strong and apply the subspace interference alignment to the users. The proposed method provides that the number of users performing the interference alignment reduces and the high total sum-rate is maintained. Simulation results exhibit the proposed method reduces the number of users who would decompose the channel for the subspace interference alignment by 50% when the required sum-rate is 90% of the maximal achievable sum-rate.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.583-585
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• 2016

The recent advances in wireless networks area have led to new techniques, such as small cells or full-duplex (FD) transmission, have also been developed to further increase the network capacity. Particularly, full-duplex communication promises expected throughput gain by doubling the spectrum compared to half-duplex (HD) communication. Because this technique permits one set of frequencies to simultaneously transmit and receive signals. In this paper, we focus on the binary power control for the users and the base stations in full-duplex multiple cellulars wireless networks to obtain optimal sum-rate under the effect interference and noise. We investigate with a scenario in there one carrier is assigned to only one user in each cell and construct a model for this problem. In this work, we apply the binary power control by the its simplification in the implemented algorithm for both uplink and downlink simultaneously to maximize sum data rate of the system. At first, we realize the 2-cells case separately to check the optimal power allocation whether being binary. Then, we carry on with N-cells case in general through properties of binary power control.