• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.32-36
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• 2016

In wireless communication systems, jamming attack is a critical threat. Especially, reactive jamming can jam when the sender and receiver are communicating, which can maximize the attack efficiency of jamming. In this paper, we use the property of multi-input multi-output (MIMO) technology to achieve jamming resilient orthogonal frequency-division multiplexing (OFDM) communications. In particular, we use MIMO interference cancellation to remove the jamming signals strategically. We first investigate the reactive jamming attack model and their impacts on the MIMO-OFDM systems. We then present an iterative channel estimation algorithm that exploits MIMO interference cancellation. Our simulations show various anti-jamming methods and demonstrate the efficiency of our proposed algorithm under the reactive jamming attack.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4240-4258
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• 2016

A practical iterative channel estimation technique is proposed for the multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system in the high-speed mobile environment, such as high speed railway scenario. In the iterative algorithm, the Kalman filter and data detection are jointed to estimate the time-varying channel, where the detection error is considered as part of the noise in the Kalman recursion in each iteration to reduce the effect of the detection error propagation. Moreover, the employed Kalman filter is from the canonical state space model, which does not include the parameters of the autoregressive (AR) model, so the proposed method does not need to estimate the parameters of AR model, whose accuracy affects the convergence speed. Simulation results show that the proposed method is robust to the fast time-varying channel, and it can obtain more gains compared with the available methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4C
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• pp.397-402
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• 2009

Accurate estimation of time-selective fading channel is a difficult problem in OFDM(Orthogonal Frequency Division Multiplexing) system. There are many channel estimation algorithms that are very weak in noisy channel. For solving this problem, we use EM (Expectation-Maximization) algorithm for iterative optimization of the data. We propose an EM-LPC algorithm to estimate the time-selective fading. The proposed algorithm improves of the BER performance compared to EM based channel estimation algorithm and reduces the iteration number of the EM loop. We simulated the uncoded system. If coded system use the EM-LPC algorithm, the performance are enhanced because of the coding gain. The EM-LPC algorithm is able to apply to another communication system, not only OFDM systems. The image processing of the medical instruments that the demand of accurate estimation can also use the proposed algorithm.

• Journal of Communications and Networks
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• v.16 no.4
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• pp.447-457
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• 2014

In this paper, we investigate the frequency domain channel estimation for multiple-input multiple-output (MIMO) single-carrier frequency-division multiple-access (SC-FDMA) systems. In MIMO SC-FDMA, code-division multiplexed (CDM) pilots such as cyclic-shifted Zadoff-Chu sequences have been adopted for channel estimation. However, most frequency domain channel estimation schemes were developed based on frequency-division multiplexing of pilots. We first develop a channel estimation error model by using CDM pilots, and then analyze the mean-square error (MSE) of various minimum MSE (MMSE) frequency domain channel estimation techniques. We show that the cascaded one-dimensional robust MMSE (C1D-RMMSE) technique is complexity-efficient, but it suffers from performance degradation due to the channel correlation mismatch when compared to the two-dimensional MMSE (2D-MMSE) technique. To improve the performance of C1D-RMMSE, we design a robust iterative channel estimation (RITCE) with a frequency replacement (FR) algorithm. After deriving the MSE of iterative channel estimation, we optimize the FR algorithm in terms of the MSE. Then, a low-complexity adaptation method is proposed for practical MIMO SC-FDMA systems, wherein FR is performed according to the reliability of the data estimates. Simulation results show that the proposed RITCE technique effectively improves the performance of C1D-RMMSE, thus providing a better performance-complexity tradeoff than 2D-MMSE.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2446-2462
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• 2016

In this paper, a frequency domain Expectation-Maximization (EM)-based channel estimation algorithm for Space Time Block Coded-Orthogonal Frequency Division Multiplexing (STBC-OFDM) systems is investigated to support higher data rate applications in wireless communications. The computational complexity of the frequency domain EM-based channel estimation is increased when higher order constellations are used because of the ascending size of the search set space. Thus, a search set reduction algorithm is proposed to decrease the complexity without sacrificing the system performance. The performance results of the proposed algorithm is obtained in terms of Bit Error Rate (BER) and Mean Square Error (MSE) for 16QAM and 64QAM modulation schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4835-4855
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• 2018

In this paper, we study the sparse signal recovery that uses information of both support and amplitude of the sparse signal. A convergent iterative algorithm for sparse signal recovery is developed using Majorization-Minimization-based Non-convex Optimization (MM-NcO). Furthermore, it is shown that, typically, the sparse signals that are recovered using the proposed iterative algorithm are not globally optimal and the performance of the iterative algorithm depends on the initial point. Therefore, a modified MM-NcO-based iterative algorithm is developed that uses prior information of both support and amplitude of the sparse signal to enhance recovery performance. Finally, the modified MM-NcO-based iterative algorithm is used to estimate the time-varying sparse wireless channels with temporal correlation. The numerical results show that the new algorithm performs better than related algorithms.

• Journal of Communications and Networks
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• v.5 no.2
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• pp.167-173
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• 2003

We treat the problem of channel estimation and interference cancellation in multiuser ultra-wide-band (UWB) communication systems over multipath fading channels. The UWB system under consideration employs a random time-hopping impulse radio format. We develop a channel estimation method based on linear weighted algorithm. An iterative channel estimation and interference cancellation scheme is proposed to successively improve the receiver performance. We also consider systems employing multiple transmit and/or receive antennas. For systems with multiple receive antennas, we develop a diversity receiver for the wellseparated antennas. For systems with multiple transmit antennas, we propose to make use of Alamouti’s space-time transmission scheme, and develop the corresponding channel estimation and interference cancellation receiver techniques. Simulation results are provided to demonstrate the performance of various UWB receiver techniques developed in this paper.

• The Journal of the Acoustical Society of Korea
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• v.41 no.4
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• pp.410-418
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• 2022

Channel reliability estimation for iterative codes such as turbo codes is very important factor in time varying underwater acoustic channel, an incorrect estimation of channel reliability induced performance degradation. Therefore, this paper presents an optimal channel reliability estimation method for turbo coded FSK signal with rate of 1/3. The estimated BER algorithm is a method that can estimate the reliability of received data by comparing received data and decoded data, and we determine optimal channel reliability by using the method. In order to analyze the performance, the experiment was conducted on a lake in Munkyeong city by moving in the range of 300 m to 500 m. At the result of applying presented method to failed decoding packets, we confirm all packets are decoded successfully.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.1
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• pp.27-32
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• 2016

In this paper, we proposed a soft decision-directed channel estimation based on MMSE estimation for MIMO-OFDM system. While the conventional method employs only pilot signals for channel estimation, the proposed algorithm performs channel estimation using pilot and reliable data signals. We also proposed selection criterion among reliable data signal for channel estimation. From numerical simulations, we show that the proposed channel estimator achieves 1 dB performance gain over conventional channel estimators.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4873-4888
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• 2018

A joint blind parameter estimation algorithm based on minimum channel stability function aimed at the non-cooperative high-order modulated paired carrier multiple access (PCMA) signals is proposed. The method, which uses hierarchical search to estimate time delay, amplitude and frequency offset and the estimation of phase offset, including finite ambiguity, is presented simultaneously based on the derivation of the channel stability function. In this work, the structure of hierarchical iterative processing is used to enhance the performance of the algorithm, and the improved algorithm is used to reduce complexity. Compared with existing data-aided algorithms, this algorithm does not require a priori information. Therefore, it has significant advantage in solving the problem of blind parameter estimation of non-cooperative high-order modulated PCMA signals. Simulation results show the performance of the proposed algorithm is similar to the modified Cramer-Rao bound (MCRB) when the signal-to-noise ratio is larger than 16 dB. The simulation results also verify the practicality of the proposed algorithm.