• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3498-3511
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• 2016

We investigate the channel state information (CSI) in multi-input multi-output (MIMO) cooperative networks that employ the amplify-and-forward transmission scheme. Least squares and expectation conditional maximization have been proposed in the system. However, neither of these two approaches takes advantage of channel sparsity, and they cause estimation performance loss. Unlike linear channel estimation methods, several compressed channel estimation methods are proposed in this study to exploit the sparsity of the MIMO cooperative channels based on the theory of compressed sensing. First, the channel estimation problem is formulated as a compressed sensing problem by using sparse decomposition theory. Second, the lower bound is derived for the estimation, and the MIMO relay channel is reconstructed via compressive sampling matching pursuit algorithms. Finally, based on this model, we propose a novel algorithm so called sparsity adaptive expectation maximization (SAEM) by using Kalman filter and expectation maximization algorithm so that it can exploit channel sparsity alternatively and also track the true support set of time-varying channel. Kalman filter is used to provide soft information of transmitted signals to the EM-based algorithm. Various numerical simulation results indicate that the proposed sparse channel estimation technique outperforms the previous estimation schemes.

• Journal of Broadcast Engineering
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• v.6 no.1
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• pp.72-81
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• 2001

An adaptive channel estimation technique for OFDM-based DTV receivers is proposed using a new mobility estimator. Sample mean techniques for channel estimation have displayed good performance in slow fading channels, because averaging reduces noise In channel estimation operation. This paper suggests an algorithm which selects the optimal number of symbols within which the sample mean of consecutive pilot data can be obtained. The designed mobility estimator determines the optimal number by comparing mobility variance and estimated noise valiance. The algorithm using the mobility estimator obtains an optimal channel function under time-invariant or time-variant multipath fading channels, thereby making the best BER performance.

• Journal of Communications and Networks
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• v.6 no.1
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• pp.19-25
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• 2004

In this paper, we present a trellis-based blind channel estimation and equalization technique coupling two kinds of adaptive Viterbi algorithms. First, the initial blind channel estimation is accomplished by incorporating the list parallel Viterbi algorithm with the least mean square (LMS) updating approach. In this operation, multiple trellis mappings are preserved simultaneously and ranked in terms of path metrics. Equivalently, multiple channel estimates are maintained and updated once a single symbol is received. Second, the best channel estimate from the above operation will be adopted to set up the whole trellis. The conventional adaptive Viterbi algorithm is then applied to detect the signal and further update the channel estimate alternately. A small delay is introduced for the symbol detection and the decision feedback to smooth the noise impact. An automatic switch between the above two operations is also proposed by exploiting the evolution of path metrics and the linear constraint inherent in the trellis mapping. Simulation has shown an overall excellent performance of the proposed scheme in terms of mean square error (MSE) for channel estimation, robustness to the initial channel guess, computational complexity, and channel equalization.

• ETRI Journal
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• v.45 no.3
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• pp.379-393
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• 2023

Underwater communication (UWC) is widely used in coastal surveillance and early warning systems. Precise channel estimation is vital for efficient and reliable UWC. The sparse direct-adaptive filtering algorithms have become popular in UWC. Herein, we present an improved adaptive convex-combination method for the identification of sparse structures using a reweighted normalized leastmean-square (RNLMS) algorithm. Moreover, to make RNLMS algorithm independent of the reweighted l₁-norm parameter, a modified sparsity-aware adaptive zero-attracting RNLMS (AZA-RNLMS) algorithm is introduced to ensure accurate modeling. In addition, we present a quantitative analysis of this algorithm to evaluate the convergence speed and accuracy. Furthermore, we derive an excess mean-square-error expression that proves that the AZA-RNLMS algorithm performs better for the harsh underwater channel. The measured data from the experimental channel of SPACE08 is used for simulation, and results are presented to verify the performance of the proposed algorithm. The simulation results confirm that the proposed algorithm for underwater channel estimation performs better than the earlier schemes.

• 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.

• ETRI Journal
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• v.46 no.3
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• pp.392-403
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• 2024

Even though generalized frequency division multiplexing is an alternative waveform method expected to replace the orthogonal frequency division multiplexing in the future, its implementation must alleviate channel effects. Least-squares (LS), a low-complexity channel estimation technique, could be improved by using the discrete Fourier transform (DFT) without increasing complexity. Unlike the usage of the LS method, the DFT-based method requires the receiver to know the channel impulse response (CIR) length, which is unknown. This study introduces a simple, yet effective, CIR length estimator by utilizing LS estimation. As the cyclic prefix (CP) length is commonly set to be longer than the CIR length, it is possible to search through the first samples if CP is larger than a threshold set using the remaining samples. An adaptive scale is also designed to lower the error probability of the estimation, and a simple signal-to-interference-noise ratio estimation is also proposed by utilizing a sparse preamble to support the use of the scale. A software simulation is used to show the ability of the proposed system to estimate the CIR length. Due to shorter CIR length of rural area, the performance is slightly poorer compared to urban environment. Nevertheless, satisfactory performance is shown for both environments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.7
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• pp.1293-1295
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• 2015

In this letter, an adaptive multi-antenna channel estimation scheme is proposed for uplink multiuser environments such as LTE-A systems to accurately estimate time-varying channels within an affordable complexity. It is confirmed that the proposed channel estimator can achieve accurate channel tracking performance even when various time-varying channel environments and traffic patterns are provided.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5A
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• pp.492-501
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• 2004

The performance of mobile communication systems depends on the state of the time-varying multi-path fading channel. To effectively prevent the corruption of video stream and its propagation in spatial and temporal domain, proactive error controls are widely being deployed. Among possible candidates, the rate compatible punctured convolutional (RCPC) code has been widely used for multimedia data, since its rate can be determined flexibly. In this paper, the adaptive channel estimation and the adaptive error correction techniques over the time-varying mobile channel have been proposed. Extensive computer simulations show that the proposed techniques yield the superior performance than the fixed rate system.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.579-582
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• 2001

The performance of a coherent rake receiver of DS-CDMA systems is significantly affected by the accuracy of channel estimation. The performance of the channel estimator can be improved by employing a channel estimation filter (CEF) whose impulse response is adjusted according to the channel condition. In this paper, we consider the design of an adaptive channel estimator for DS-CDMA systems with a pilot channel. The proposed channel estimator estimates the channel condition, which can be performed without haying exact a priori information on the operating condition. The estimated channel condition adjusts the impulse response of the CEF. Numerical results show that the use of the proposed channel estimator can provide BER performance quite robust to a wide range of channel condition.