• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.108-122
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• 2014

Massive antenna array is an attractive candidate technique for future broadband wireless communications to acquire high spectrum and energy efficiency. However, such benefits can be realized only when proper channel information is available at the transmitter. Since the amount of the channel information required by the transmitter is large for massive antennas, the feedback is burdensome in practice, especially for frequency division duplex (FDD) systems, and needs normally to be reduced. In this paper a novel channel feedback reduction scheme based on the theory of distributed compressive sensing (DCS) is proposed to apply to massive antenna arrays with spatial correlation, which brings substantially reduced feedback load. Simulation results prove that the novel scheme is better than the channel feedback technique based on traditional compressive sensing (CS) in the aspects of mean square error (MSE), cumulative distributed function (CDF) performance and feedback resources saving.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.6A
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• pp.635-642
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• 2008

We propose the Optimum Power Allocation (OPA) scheme for Distributed Antenna Systems(DAS) in the time-varying Rayleigh fading channel. Recently, the OPA schemes which uses the Channel State Information (CSI) including a small scale (fast) fading have been proposed. However, the channel is changing vary fast over time due to small scale fading, therefore Bit Error Rate (BER) increases. Because of this reason, we derive the OPA for minimizing BER in DAS, which only uses a large scale fading to CSI and excepts a small scale fading. The simulation results show that the proposed OPA achieves better BER performance than conventional OPA considering a small scale fading in time-varying Rayleigh fading channel, and also has similar performance in Rayleigh flat-fading environment. The BER performance of proposed OPA which derived in Rayleigh fading channel is similar to minimum BER of Ricean fading channel which has small Line-of-Sight (LOS).

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.693-698
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• 2000

Aspects of classical information theory, such as rate distortion theory, investigate how to encode and decode information from an independently identically distributed source so that the asymptotic distortion rate between the source and its quantized representation is minimized. However, in most natural dynamics, the source state is highly corrupted by disturbances, and the measurement contains the noise. In recent coder-estimator sequence is developed for state estimation problem based on observations transmitted with finite communication capacity constraints. Unlike classical estimation problems where the observation is a continuous process corrupted by additive noises, the condition is that the observations must be coded and transmitted over a digital communication channel with finite capacity. However, coder-estimator sequence does not provide such a quantitative analysis as a variance for estimation error. In this paper, under the assumption that the estimation error is Gaussian distribution, a variance for coder-estimation sequence is proposed and its fitness is evaluated through simulations with a simple example.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.10
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• pp.1934-1936
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• 2015

This paper proposes an optimal relay selection and adaptive throughput enhancement scheme utilizing superposition modulation in cooperative communication. The optimal relay is selected and the channel state is estimated by utilizing superposition modulation. The source determines the number of superimposed signal in accordance with the estated channel state. As a result, throughput is increased in accordance with the channel state.

• ETRI Journal
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• v.45 no.6
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• pp.929-938
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• 2023

The detection of all the symbols transmitted simultaneously in multiuser systems using limited wireless resources is challenging. Traditional model-based methods show high performance with perfect channel state information (CSI); however, severe performance degradation will occur if perfect CSI cannot be acquired. In contrast, data-driven methods perform slightly worse than model-based methods in terms of symbol error ratio performance in perfect CSI states; however, they are also able to overcome extreme performance degradation in imperfect CSI states. This study proposes a novel deep learning-based method by improving a state-of-the-art data-driven technique called deep soft interference cancellation (DSIC). The enhanced DSIC (EDSIC) method detects multiuser symbols in a fully sequential manner and uses an efficient neural network structure to ensure high performance. Additionally, error-propagation mitigation techniques are used to ensure robustness against channel uncertainty. The EDSIC guarantees a performance that is very close to the optimal performance of the existing model-based methods in perfect CSI environments and the best performance in imperfect CSI environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.7
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• pp.1468-1476
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• 1997

In mobile communication systems, the Reduced State Sequence Estimation(RSSE) receiver must be able to track changes in the channel. This is carried out by the adaptive channel estimator. However, when the tentative decisions are used in the channel estimator, incorrect decisions can cause error propagation. This paper presents a new channel estimator using the path history in the Viterbi decoder for preventing error propagation. The selection of the path history in the Viterbi decoder for preventing error propagation. The selection of the path history for the channel estimator depends on the path metric as in the decoding of the Viterbi decoder in RSSE. And a discussion on the channel estimator with different adaptation algorithms such as Least Mean Square(LMS) algorithm and Recursive Least Square(RLS) algorithm is provided. Results from computer simulations show that the RSSE receivers using the proposed channel estimator have better performance than the other conventional RSSE receiver, and that the channel estimator with RLS algorithm is adequate for multipath fading channel.

• The KIPS Transactions:PartC
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• v.12C no.5 s.101
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• pp.665-672
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• 2005

We present a novel pilot-aided channel estimation method for OFDM (Orthogonal Frequency Division Muitiplexing) system using WT(Wavelet transform) and interpolation. Due to excellent AWGN (Additive White Gaussian Noise) cancellation capability of n, pilot channels are estimated quite exactly and then, Dey are used in 2-degree polynomial interpolating the other remaining data symbol channels. The simulation results for Short WATM (Wireless Asynchronous Transfer Mode) channel show that the degradation in BER (Bit Error Ratio) performance of OFDM system iか this estimator is negligible compared to the case of perfect knowledge of CSI (Channel State Information).

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.12
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• pp.26-33
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• 2008

Signal detection is a key technique in wireless communication system. Recently, several detection algorithms have been developed for multiple-input multiple-output (MIMO) wireless communication systems. However, most research in this area had assumed a flat-fading channel environment and all these techniques are based on the assumption that the channel state information (CSI) at the receiver side is perfect. But in practical situation, the available CSI may be imperfect because of channel estimation errors and/or outdated training. In this paper, we will compare the performance of several detection algorithms in MIMO frequency selective fading channel environment with imperfect CSI.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.4
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• pp.795-804
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• 1999

The increasing number of users of mobile communication systems and the corresponding need for increased system capacity require the use of a modulation scheme which is both power and spectrally efficient. In this paper, we numerically calculate the BER performance of DS/CDMA-BPSK system in different fading channel (Rayleigh, Rician, Shadow Rician). Also, we calculate BER performance and the channel capacity of DS/CDMA-BPSK system which is constant or nearly constant envelopes in 3-state fading channel model. The Shadow Rician fading model described in this paper apply the parameters of the Canadian Mobile Satellite (MSAT). And we assume that the 3-state fading channel model is consist of Rayleigh fading state, Rician fading state, and shadow Rician fading state. This model can be used as a basis for the simulation of the land mobile satellite channel. The dynamic 3-state fading channel model is considered corresponding to different environments and the transitions between these environments. From the numerically calculate results, the DS/CDMA-BPSK system with MUI-20, PG-511 can not achieve the BER performance ($P_b\leq10^{-5}$). And the channel capacity did not meet the system requirement. Also, we know that the BER performance is depend m the occupancy probability of radio channel and the degree of shadow. From the results, we how that during shadowed time intervals it is necessary to use some form of error control coding and receiver diversity in order to support reliable data communication.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.3134-3155
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• 2020

In this paper, we study the joint radio and computational resource allocation in the ultra-dense mobile-edge computing networks. In which, the scenario which including both computation offloading and communication service is discussed. That is, some mobile users ask for computation offloading, while the others ask for communication with the minimum communication rate requirements. We formulate the problem as a joint channel assignment, power control and computational resource allocation to minimize the offloading cost of computing offloading, with the precondition that the transmission rate of communication nodes are satisfied. Since the formulated problem is a mixed-integer nonlinear programming (MINLP), which is NP-hard. By leveraging the particular mathematical structure of the problem, i.e., the computational resource allocation variable is independent with other variables in the objective function and constraints, and then the original problem is decomposed into a computational resource allocation subproblem and a joint channel assignment and power allocation subproblem. Since the former is a convex programming, the KKT (Karush-Kuhn-Tucker) conditions can be used to find the closed optimal solution. For the latter, which is still NP-hard, is further decomposed into two subproblems, i.e., the power allocation and the channel assignment, to optimize alternatively. Finally, two heuristic algorithms are proposed, i.e., the Co-channel Equal Power allocation algorithm (CEP) and the Enhanced CEP (ECEP) algorithm to obtain the suboptimal solutions. Numerical results are presented at last to verify the performance of the proposed algorithms.