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Copyright of Study on Optical Communications / Guangtongxin Yanjiu is the property of Study on Optical Communications Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Study on Optical Communications / Guangtongxin Yanjiu is the property of Study on Optical Communications Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

[Objective] Power Line Carrier(PLC)communication adopts the frame burst transmission mode. Due to the carrier frequency offset between transceivers, various noise and time-varying characteristics of PLC channel and the system has no dedicated reference signal. The traditional channel estimation has no tracking and prediction ability for the channel, which leads to the deterioration of the PLC system performance. [Methods] Aiming at the existing problems, this paper proposes a Denoising Long Short Term Memory (DnLSTM) neural network based on Long Short Term Memory (LSTM) neural network and Denoising Convolutional Neural Network (DnCNN), which is used for PLC channel estimation. First, offline training is performed on DnLSTM and the parameters are saved after training. Then the trained parameters are deployed in PLC system. After loading parameters, online prediction is performed to obtain the predicted PLC system channel estimation. In the simulation of PLC system, this paper uses Least Squares (LS) algorithm, Minimum Mean Square Error (MMSE) algorithm and DnLSTM to estimate the channel response, and gives the simulation results under the conditions of Additive White Gaussian Noise (AWGN), combined noise, impulsive noise and colored noise. Meanwhile, simulations for different number of preamble symbols for channel estimation are performed. [Results] The results show that there is a relationship between the accuracy of DnLSTM channel estimation and the number of preamble symbols. Using four preamble symbols for channel estimation, its estimation accuracy is better than LS and close to MMSE algorithm. DnLSTM has a good ability to resist carrier frequency offset and channel time-varying. When the number of preamble symbols for channel estimation increases, PLC system performance with low Singnal to Noise Ratio (SNR) gets better and PLC system performance is similar with high SNR. [Conclusion] According to simulation results above, it can be concluded that DnLSTM, which is based on DnCNN and LSTM, can predict PLC system channel response with frequency offset very well and it can track the varying PLC system channel response in real time [ABSTRACT FROM AUTHOR]

【Objective】With the development of the space-ground integrated information network, the Low Earth Orbit (LEO) satellite communication system is ushering in a development boom. The Paired Carrier Multiple Access (PCMA) technology is gradually developing to the low-orbit satellite communication due to its advantages of saving bandwidth resources. However, traditional PCMA technology is mostly used in high-orbit satellites, and cannot adapt to the highly dynamic fading channel character-istics of low-orbit satellite channels, which greatly degrades the bit error performance of the PCMA receiver. The bottleneck lies in the channel estimation and equalization technologies for overlapping signals.【Methods】Aiming at the channel characteristics of LEO satellites, this paper proposes a channel estimation scheme that combines training sequence estimation and Autoregressive (AR) model prediction. Based on the idea of superimposed training sequence channel estimation, an iterative method suitable for PCMA mixed signal channel estimation is introduced to improve the accuracy of training sequence channel estimation through iteration. The AR model is used to predict the Channel State Information (CSI) of the data sequence in real time. The use of AR model can also reduce the frequency of channel estimation in training sequences, so as to adapt to the dynamics of LEO satellite channels.【Results】The simulation results show that the idea of superimposed training sequence channel estimation can be applied to the PCMA signals, and accurate channel estimation can be obtained after iterations. The method proposed in this paper can effectively improve the accuracy of channel estimation. After signal separation and demodulation, the bit error rate can reach the order of 10-3when the signal-to-noise ratio is greater than 9 dB.【Conclusion】A channel estimation method for PCMA signal is proposed in this paper. The simulation results show that the bit error rate loss is within an acceptable range, which can support the application of PCMA technology in low-orbit satellite communication. The proposed algorithm has the advantages of simple structure, low complexity, and high practical value.

Copyright of Automobile Technology & Material is the property of Automobile Technology & Material Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Waveform design of joint radar and communication has become a focus of intense research in recent years. Some scholars have proposed to use the odd and even carrier of Orthogonal Frequency Division Multiplexing (OFDM) signal to modulate the radar and communication functions, respectively, to realize the integration. However, OFDM systems generally use cyclic prefix to avoid Inter-Carrier Interference (ICI) and Inter-Symbol Interference (ISI) caused by multipath effects, reducing energy utilization and creating false targets, which affect radar performance. In addition, the traditional OFDM integrated signal is more sensitive to Doppler shift. A small Doppler frequency offset will also cause a considerable drop in orthogonal performance. On this basis, this paper proposes a new waveform design and processing method. This method uses blank guard intervals to replace cyclic prefixes, which can resist multipath effects while avoiding false targets introduced by cyclic prefixes, effectively preventing ICI and ISI. In terms of signal processing methods, this paper proposes a method for channel estimation and Doppler compensation using the priori information of the radar signal. Compared with the traditional method, this new method reduces the system’s resource overhead, such as pilot frequency and training sequence. It improves energy utilization and spectrum efficiency. The peak side lobe ratio, integration side lobe rate, and bit error ratio are also improved. Simulation experiments verify the effectiveness of this method.

【Objective】With the development of the sixth generation mobile communication technology, the inter-carrier interference in the traditional Orthogonal Frequency Division Multiplexing (OFDM) system makes the channel estimation performance insufficient to provide highly reliable communication, and Orthogonal Time-Frequency Space (OTFS) system can effectively solve the problem of communication system reliability degradation caused by fast time variability and Doppler effect, which has received wide attention in recent years.【Methods】In order to effectively meet the channel estimation performance requirements of OTFS systems, this paper uses an Optimized Generalized Complex Exponential (OGCE) Basis Expansion Model (BEM) to calculate the channel impulse response as a time-invariant basis function with basis function coefficients, which can effectively fit fast time-varying channels in high-speed mobile communication scenarios. The OGCE-BEM improves the spectral leakage by more intensive sampling and reduces the error of the high-frequency basis model by adding correction coefficients to reduce the error of the HF-based model.【Results】The simulation results show that the proposed algorithm is suitable for high-speed mobile communication scenarios with more reasonable design of the basis function. The estimation method has lower mean square error than the fixed forgetting factor, and the channel estimation results are more accurate. Compared with Least Square (LS), BEM-LS and BEM-Linear Minimum Mean Square Error (LMMSE) channel estimation methods, the performance of mean square error is significantly improved.【Conclusion】It can be seen that the channel estimation algorithm based on OGCE-BEM can effectively reduce the number of unknown parameters to be estimated and improve the accuracy of channel estimation.

Copyright of Study on Optical Communications / Guangtongxin Yanjiu is the property of Study on Optical Communications Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Study on Optical Communications / Guangtongxin Yanjiu is the property of Study on Optical Communications Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Aiming at the problem of low accuracy of traditional channel estimation algorithms in the harsh environment of underground coal mines, this paper proposes an improved Super Resolution Convdutional Network (SRCNN) for channel estimation. In the improved SRCNN model, the estimated value at the pilot frequency is used as input, and the improved SRCNN model replaces the interpolation process in the traditional channel estimation algorithm to reduce the complexity, and the attention mechanism ECA module is added to improve the learning of channel features to achieve more accurate channel estimation for the underground coal mine environment. Simulation results show that the channel estimation algorithm of the improved SRCNN model outperforms the traditional channel estimation algorithm and improves the estimation accuracy by one order of magnitude compared with the channel estimation of the SRCNN model.

Copyright of Journal of Harbin University of Science & Technology is the property of Journal of Harbin University of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal on Communication / Tongxin Xuebao is the property of Journal on Communications Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Harbin University of Science & Technology is the property of Journal of Harbin University of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To solve the sparse channel estimation problem in Orthogonal Frequency Division Multiplexing (OFDM) systems, this paper presents a pilot design algorithm based on multi-pilot parallel searching and binary coding. Under the Mutual Incoherence Property (MIP), we consider the deterministic pilot design problem by minimizing the coherence of the dictionary matrix. The pilot is also required to be placed within the effective subcarrier range for more practical purposes. In this scheme, the pilot set is binary coded. In each iteration, the sequence of the binary code segment is recombined to update the approximately optimal pilot position. The update of some coding segments can change multiple pilot positions at the same time. It can increase the diversity of pilots, and reduce the complexity of computation. Experimental results show that, compared with the existing pilot optimization methods, this algorithm can find a smaller MIP measurement matrix. Therefore, the corresponding pilot mode can significantly improve the performance of channel estimation.

Aiming at the time-domain sparsity and unknown sparsity of wireless channels, compressed sensing technology is applied to the channel estimation of Orthogonal Frequency Division Multiplexing (OFDM) system. This paper proposes a sparsity adaptive matching pursuit channel estimation algorithm. It uses the Discrete Fourier Transform (DFT) channel estimation algorithm to process the noise inside and outside the cyclic prefix. The estimated channel frequency response is used to terminate the sparse iteration of the Orthogonal Matching Pursuit (OMP) algorithm and realize the sparsity adaptive signal reconstruction. At the same time, in the atomic preselection stage, the Dice coefficient criterion is used instead of the inner product criterion as the correlation measurement criterion to achieve better estimation performance. The simulation results show that the algorithm has better performance than the traditional compressed sensing channel estimation algorithm, and can improve the system’s Normalized Mean Square Error (NMSE) and Bit Error Rate (BER) performance.

To solve the sparse channel estimation problem in Orthogonal Frequency Division Multiplexing (OFDM) systems, this paper presents a pilot design algorithm based on multi-pilot parallel searching and binary coding. Under the Mutual Incoherence Property (MIP), we consider the deterministic pilot design problem by minimizing the coherence of the dictionary matrix. The pilot is also required to be placed within the effective subcarrier range for more practical purposes. In this scheme, the pilot set is binary coded. In each iteration, the sequence of the binary code segment is recombined to update the approximately optimal pilot position. The update of some coding segments can change multiple pilot positions at the same time. It can increase the diversity of pilots, and reduce the complexity of computation. Experimental results show that, compared with the existing pilot optimization methods, this algorithm can find a smaller MIP measurement matrix. Therefore, the corresponding pilot mode can significantly improve the performance of channel estimation.

Aiming at the time-domain sparsity and unknown sparsity of wireless channels, compressed sensing technology is applied to the channel estimation of Orthogonal Frequency Division Multiplexing (OFDM) system. This paper proposes a sparsity adaptive matching pursuit channel estimation algorithm. It uses the Discrete Fourier Transform (DFT) channel estimation algorithm to process the noise inside and outside the cyclic prefix. The estimated channel frequency response is used to terminate the sparse iteration of the Orthogonal Matching Pursuit (OMP) algorithm and realize the sparsity adaptive signal reconstruction. At the same time, in the atomic preselection stage, the Dice coefficient criterion is used instead of the inner product criterion as the correlation measurement criterion to achieve better estimation performance. The simulation results show that the algorithm has better performance than the traditional compressed sensing channel estimation algorithm, and can improve the system’s Normalized Mean Square Error (NMSE) and Bit Error Rate (BER) performance.

Copyright of Telecommunications Science is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper studies DFT based channel estimation algorithm for practical LTE-A system.In order to solve the energy leakage problem of Channel Impulse Response（CIR）based on DFT channel estimation algorithm,a novel DFT based channel estimation method is proposed.The proposed method reconstructs the CIR by recurrence sequence in order to suppress the noise and reserve the CIR energy.The proposed method also replaces the jitter points of Channel Frequency Response（CFR）with the result of Least Square（LS）algorithm in the corresponding position to further suppress Gibbs phenomenon.Simulation results show the performance of proposed method is better than those of LS and classic DFT based algorithms.