• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.794-815
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• 2023

The rapid development of mobile communication not only has made the industry gradually diversified, but also has enhanced the service quality requirements of users. In this regard, it is imperative to consider jointly network slicing and mobile edge computing. The former mainly ensures the requirements of varied vertical services preferably, and the latter solves the conflict between the user's own energy and harsh latency. At present, the integration of the two faces many challenges and need to carry out at different levels. The main target of the paper is to minimize the energy consumption of the system, and introduce a multi-slice joint task offloading and resource allocation scheme for massive multiple input multiple output enabled heterogeneous networks. The problem is formulated by collaborative optimizing offloading ratios, user association, transmission power and resource slicing, while being limited by the dissimilar latency and rate of multi-slice. To solve it, assign the optimal problem to two sub-problems of offloading decision and resource allocation, then solve them separately by exploiting the alternative optimization technique and Karush-Kuhn-Tucker conditions. Finally, a novel slices task offloading and resource allocation algorithm is proposed to get the offloading and resource allocation strategies. Numerous simulation results manifest that the proposed scheme has certain feasibility and effectiveness, and its performance is better than the other baseline scheme.

• Journal of IKEEE
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• v.25 no.3
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• pp.420-424
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• 2021

The massive MIMO system, which is a core technology of 5G communication systems, has a problem that it is difficult to implement in a frequency division duplex system based on limited channel feedback because a large amount of channel information is required at the transmitting end. In order to solve this problem, the Joint Spatial Division and Multiplexing (JSDM) technique that dramatically reduces the channel information requirement by removing interference between the user groups using channel correlation information that does not change for a long time has been proposed. Recently, a regularized JSDM technique has been proposed to further improve performance by allowing residual interference between the user groups. However, such JSDM-related studies were mainly designed to focus on inter-group interference cancellation, and thus performance analysis was not performed in a more realistic environment assuming limited feedback in the intra-group interference cancellation phase. In this paper, we analyze the performance of the JSDM and regularized JSDM techniques according to the number of groups and users in a limited feedback environment, and through the simulation results, demonstrate that the regularized JSDM technique shows a more remarkable advantage compared to the existing JSDM in a limited feedback environments.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.7
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• pp.3-8
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• 2014

We consider a limited feedback based hybrid beamforming which reduces the energy of feedback information. In the millimeter wave channel, some rays with large ray gain dominate energy of the channel. Using this point, we propose a channel feedback scheme that employs limited number of channel rays. Also, we provide a hybrid beamforming scheme for the limited feedback system. Based on the simulation results, the proposed scheme shows a comparable data rate performance with conventional schemes, while it remarkably reduces energy of channel feedback.

• ETRI Journal
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• v.45 no.6
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• pp.952-962
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• 2023

In this study, a space-time transmission scheme is proposed to tackle the limitations of channel estimation with orthogonal pilot information in colocated multiple-input multiple-output systems with several transmitting and receiving antennas. Channel information is obtained using orthogonal pilots. Channel estimation introduces pilot heads required to estimate a channel. This leads to bandwidth insufficiency. As a result, trade-offs exist between the number of pilots required to estimate a channel versus spectral efficiency. The detection of data symbols is performed using the maximum likelihood decoding method as it provides a consistent approach to parameter estimation problems. The moment-generating function of the instantaneous signal-to-noise ratio is used to drive an approximate expression of the symbol error rate for the proposed scheme. Furthermore, the order of diversity is less by one than the number of receiver antennas used in the proposed scheme. The effect of the length of a pilot sequence on the proposed scheme's performance is also investigated.

• 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.