An efficient pilot-symbol-aided and decision-directed hybrid channel estimation technique in OFDM systems

Porselvi, R.; Murugan, M.

doi:10.1007/s11235-019-00620-5

Cited by 3 publications

(1 citation statement)

References 29 publications

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“…Combining pilot symbols with channel coding has attracted the attention of several researchers. The pilot symbols can be inserted within the encoded bits after the encoding process in an arrangement known as 'external pilot insertion' [17]. This approach has been utilised in many works to improve the system performance.…”

Section: Introductionmentioning

confidence: 99%

Internal pilot insertion for polar codes

Abdulwahab

Kadhim

2021

IJEECS

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Two internal pilot insertion methods are proposed for polar codes to improve their error correction performance. The presented methods are based on a study of the weight distribution of the given polar code. The insertion of pilot bits provided a new way to control the coding rate of the modified polar code on the basis of the Hamming weight properties without sacrificing the code construction and the related channel condition. Rate control is highly demanded by 5G channel coding schemes. Two short-length polar codes were considered in the work with successive cancellation list decoding. The results showed that advantages in the range of 0.1 to 0.75 dB were obtained in the relative tolerance of the modified coded signal to the additive white Gaussian noise and fading channels at a bit error rate of 10<sup>−4</sup>. The simulation results also revealed that the performance improvements were possible with a careful insertion of the pilots. The modified polar code with pilot insertion provided performance improvement and offered the control of the coding rate without any added complexity at both the encoder and the decoder.

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Section: Introductionmentioning

confidence: 99%

Internal pilot insertion for polar codes

Abdulwahab

Kadhim

2021

IJEECS

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Research and implementation of network communication based on embedded monitoring system

Wang

2023

Wireless Netw

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Artificial neural network-based sparse channel estimation for V2V communication systems

Rahim,

Essai,

Hamad

2024

Journal of Electrical Engineering

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Artificial neural networks (ANNs) have gained a lot of attention from researchers in the past few years and have been employed on a large scale. They have also been gaining momentum in wireless communication systems. For efficient vehicle-to-vehicle (V2V) channel communication, a sparse multipath channel issue must be studied. To minimize the multipath effect, a time reversal (TR) operation and time division synchronization orthogonal frequency division multiplexing (TDS-OFDM) have been appealing because of their fast synchronization and active spectral efficiency. To improve the transceiver's execution in a frequency-selective fading channel environment, an OFDM system is used to reduce inter- symbol interference (ISI). Simultaneous Orthogonal Matching Pursuit (SOMP) channel state estimator algorithm suffer from high computational cost and high computational complexity. The ANN algorithm has better performance than SOMP algorithm. The proposed neural network technologies have lower complexity than the SOMP algorithm. The application of ANN is capable of solving complex problems, such as those encountered in image, signal processing and have been implemented for channel estimation in OFDM. The proposed ANN outperformed the SOMP algorithm with regard to signal compensation. Overall, the ANN algorithm achieved the best performance. This study proposes an ANN-based sparse channel state estimator. Regarding the bit error rate (BER) metric, the proposed estimator outperforms the channel estimation approach based on the SOMP. The simulation results confirm the efficacy of the proposed approach.

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An efficient pilot-symbol-aided and decision-directed hybrid channel estimation technique in OFDM systems

Cited by 3 publications

References 29 publications

Internal pilot insertion for polar codes

Internal pilot insertion for polar codes

Research and implementation of network communication based on embedded monitoring system

Artificial neural network-based sparse channel estimation for V2V communication systems

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