• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.8-14
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• 2008

There are two a approaches for the Cognitive Radio(CR) development. One is 'Full CR', which Joseph Mitola III proposed, and another is 'Spectrum CR', which is currently being standardized. The target approach of this paper is the latter and we develop a Cognitive Engine(CE) and simulated a channel set management(CSM), which is a core function of CE. The Channel set management evaluates channel quality and Incumbent User(IU) vacancy possibility and classifies the channel set, which is performed by using channel state history. Especially, a very important function for the channel set management is a channel state prediction and this paper proposed a Hidden Markov Model(HMM) based channel state prediction and a method for increasing performance. Also, we applied the proposed method into our simulator and simulated channel state prediction. Through the simulation, we verified as we applied our proposed scheme, the performance of channel state prediction gets better and through comparing with RS and SS, we verified the HMM based Channel state prediction is better.

• 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.

• Journal of Advanced Information Technology and Convergence
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• v.6 no.1
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• pp.45-57
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• 2016

This paper proposes an adaptive channel estimation scheme for OFDM-based IEEE 802.11ad wireless local area network (WLAN). The standard supports two types of information of OFDM packets for estimating the communication channels, which are the channel estimation field (CEF) of preamble and pilot subcarriers. The CEF-based channel estimation provides better BER (bit error rate) performance at slow fading channel state, whereas the pilot-based channel estimation is good at fast fading channel state. Hence, a combined channel estimation method is introduced to improve the performance. The prediction of the channel state to select the proper channel estimation method is required. In this work, an adaptive channel estimation scheme is also proposed to improve the performance of channel estimation (CE). Basing on a channel quality indicator (CQI), the proper channel estimation method corresponding to the channel type is decided.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.11C
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• pp.1100-1106
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• 2006

In downlink of mobile communication systems, the feedback delay between channel estimation and actual transmission causes inaccuracy in channel-state-information (CSI) and this results in performance degradation. In order to overcome this phenomenon, channel prediction is inevitable. In this paper, an adaptive transmission scheme based on channel prediction is proposed and its performance is evaluated. From simulation results, it is shown that the performance degradation due to the feedback delay is successfully mitigated by using the proposed scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.7A
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• pp.762-769
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• 2007

Adaptive MIMO-OFDM (Orthogonal Frequency Division Multiplexing) system adaptively changes modulation scheme depending on feedback channel state information (CSI). The CSI feedback channel which is the reverse link channel has multiple symbol delays including propagation delay, processing delay, frame delay, etc. The unreliable CSI due to feedback delay degrades adaptive modulation system performance. This paper compares the MSE and data capacity with respect to delay and channel signal to noise ratio for the two multi-step channel prediction schemes, CTSBP and BTSBP, such that robust adaptive SISO-OFDM/MIMO-OFDM is designed over severe mobile multipath channel conditions. This paper presents an interpolation method to reduce feedback overhead for adaptive MIMO-OFDM and shows MSE with respect to interpolation interval.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.5A
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• pp.451-458
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• 2006

In this paper, we propose a novel scheduling algorithm for downlink transmission which utilizes scarce wireless resource efficiently in an Orthogonal Frequency Division Multiple Access/Time Division Duplex system. Scheduling schemes which exploit channel information between a Base Station and terminals have been proposed recently for improved performance. Time series analysis is used to estimate the channel state of mobile terminals. The predicted information is then used for prioritized scheduling of downlink transmissions for improved throughput, delay and jitter performance. Through simulation, we show that the total throughput and mean delay of the proposed scheduling algorithm are improved compared with those of the Proportional Fairness and Maximum Carrier to Interference Ratio schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3029-3045
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• 2017

The main processes of a cognitive radio system include spectrum sensing, spectrum decision, spectrum sharing, and spectrum conversion. Experimental results show that these stages introduce a time delay that affects the spectrum sensing accuracy, reducing its efficiency. To reduce the time delay, the frequency spectrum prediction was proposed to alleviate the burden on the spectrum sensing. In this paper, the deep recurrent neural network (DRNN) was proposed to predict the spectrum of multiple time slots, since the existing methods only predict the spectrum of one time slot. The continuous state of a channel is divided into a many time slots, forming a time series of the channel state. Since there are more hidden layers in the DRNN than in the RNN, the DRNN has fading memory in its bottom layer as well as in the past input. In addition, the extended Kalman filter was used to train the DRNN, which overcomes the problem of slow convergence and the vanishing gradient of the gradient descent method. The spectrum prediction based on the DRNN was verified with a WiFi signal, and the error of the prediction was analyzed. The simulation results proved that the multiple slot spectrum prediction improved the spectrum efficiency and reduced the energy consumption of spectrum sensing.

• Journal of Communications and Networks
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• v.15 no.6
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• pp.589-600
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• 2013

In this paper, we propose a new feedback scheme called mode selection-based feedback by scheduling probability prediction (SPP-MF) for channel state feedback in OFDMA downlink system. We design the scheme such that it determines the more desirable feedback mode among selective feedback by scheduling probability prediction (SPP-SF) mode and bitmap feedback by scheduling probability prediction (SPP-BF) mode, by calculating and comparing the throughputs of the two modes. In both feedback modes, each user first calculates the scheduling probability of each subchannel (i.e., the probability that a user wins the scheduling competition for a subchannel) and then forms a feedback message based on the scheduling probability. Specifically, in the SPP-SF mode, each user reports the modulation and coding scheme (MCS) levels and indices of its best S subchannels in terms of the scheduling probability. In the SPP-BF mode, each user determines its scheduling probability threshold. Then, it forms a bitmap for the subchannels according to the scheduling probability threshold and sends the bitmap along with the threshold. Numerical results reveal that the proposed SPP-MF scheme achieves significant performance gain over the existing feedback schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.4
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• pp.475-490
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• 2010

Cognitive Radio is an advanced enabling technology for the efficient utilization of vacant spectrum due to its ability to sense the spectrum environment. It is important to determine accurate spectrum utilization of the primary system in a cognitive radio environment. In order to define the spectrum utilization state, many CR systems use what is known as the quiet period (QP) method. However, even when using a QP, interference can occur. This causes reduced system throughput and contrary to the basic condition of cognitive radio. In order to reduce the interference time, a frequency-hopping algorithm is proposed here. Additionally, to complement the loss of throughput in the FH, a HMM-based channel prediction algorithm and a channel allocation algorithm is proposed. Simulations were conducted while varying several parameters. The findings show that the proposed algorithm outperforms conventional channel allocation algorithms.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.439-445
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• 2021

In view of the complex geometric structure of the rod bundle channel and the limitation of the current CHF visualization experiment technology, it is very difficult to obtain the rod bundle CHF mechanism directly through the phenomenon of the rod bundle CHF visualization experiment. In order to obtain the applicable CHF mechanism assumption for rod bundle channel, firstly, five most representative DNB type round tube CHF mechanistic models are obtained with evaluation and screening. Then these original round tube CHF mechanistic models based on inlet conditions are converted to local conditions and coupled with subchannel analysis code ATHAS. Based on 5 × 5 full-length rod bundle CHF experimental data independently developed by Nuclear Power Institute of China (NPIC), the applicability research of each model for CHF prediction performance in rod bundle channel is carried out, and the commonness and difference of each model are comparatively studied. The CHF mechanism assumption of superheated liquid layer depletion that is most likely to be applicable for the rod bundle channel is selected and two directions that need to be improved are given. This study provides a reference for the development of CHF mechanistic model in rod bundle channel.