Performances Analysis of Turbo Codes, LDPC Codes and Polar Codes using AWGN channel with and without Inter Symbol Interference

Cuc, Adriana-Maria; Morgoș, Florin Lucian; Grava, Cristian

doi:10.1109/isetc56213.2022.10010114

Cited by 3 publications

(3 citation statements)

References 12 publications

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“…LDPC codes offer advantages over traditional Reed-Solomon (RS) codes and convolutional codes due to their simpler coding structure and lower decoding complexity [9]. Compared with Turbo code, LDPC code is proven to have stronger error correction capability and lower error rate in long coding, and the iterative decoding algorithm of LDPC is a parallel algorithm with low decoding delay [10,11]. Moreover, LDPC codes have shown better performance relative to polar codes in optical communication systems, especially under high SNR conditions, where LDPC codes generally have lower bit error rates and higher reliability [12].…”

Section: Introductionmentioning

confidence: 99%

Investigation of IEEE 802.16e LDPC Code Application in PM-DQPSK System

Xue,

Li,

Zhang

et al. 2024

Electronics

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With the development of the Internet and information technology, optical fiber communication systems need to meet people’s information demand for large capacity and high speed. High-order phase modulation and channel multiplexing can improve the capacity and data rate of optical fiber communication systems, but they also bring the problem of bit error. To improve the transmission quality and reliability of optical fiber communication systems, forward error correction (FEC) coding techniques are commonly used, which serve as the fundamental approach to enhance the quality and reliability of fiber optic communication systems, ensuring that the received data remain accurate and reliable. The FEC in optical fiber communication systems is divided into three generations. The first generation FEC is mainly hard decision codewords, represented as RS code. The second generation FEC is mainly cascaded code, which stands for interleaved cascaded code. The third generation of FEC mainly refers to soft decision codes, which are represented as low-density parity-check (LDPC) codes. As a kind of FEC, LDPC codes stand out as pivotal contributors in the field of optical communication and have gained remarkable attention due to exceptional error correction performance and low decoding complexity. Based on IEEE802.16e standard, LDPC code with specific code length and rate is compiled and simulated in MATLAB and VPItransmissionMaker 10.1 and successfully incorporated into polarization multiplexed differential quadrature phase shift keying (PM-DQPSK) coherent optical transmission system. The simulation results indicate that the bit error rate (BER) can be reduced to 10−3 when the optical signal-to-noise ratio (OSNR) reaches 14.2 dB, and the BER experiences a reduction by nearly three orders of magnitude when the OSNR is 17.2 dB. These findings underscore the efficacy of LDPC codes in significantly improving the performance of optical communication systems, particularly in scenarios demanding robust error correction capabilities. This study provides valuable, significant results regarding the potential of LDPC codes for enhancing the reliability of optical transmission in real-world applications.

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Section: Introductionmentioning

confidence: 99%

Investigation of IEEE 802.16e LDPC Code Application in PM-DQPSK System

Xue,

Li,

Zhang

et al. 2024

Electronics

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“…Several criteria for optimizing these coefficients are recommended; the most used being that of minimizing the mean square error (MMSE). Although an MMSE equalizer provides a good performance, a simple approach to designing a zero forcing equalizer at the level of the receiver was considered in [ 12 ].…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis of Turbo Codes, LDPC Codes, and Polar Codes over an AWGN Channel in the Presence of Inter Symbol Interference

Cuc

Morgoș

Grava

2023

Sensors

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This paper discusses the results of simulations relating to the performances of turbo codes, low density parity check (LDPC) codes, and polar codes over an additive white Gaussian noise (AWGN) channel in the presence of inter symbol interference, denoting the disturbances that altered the original signal. To eliminate the negative effects of inter symbol interference (ISI), an equalizer was used at the level of the receiver. Practically, two types of equalizers were used: zero forcing (ZF) and minimum mean square error (MMSE), considering the case of perfect channel estimation and the case of estimation using the least square algorithm. The performance measure used was the modification of the bit error rate compared to a given signal to noise ratio; in this sense, the MMSE equalizer offered a higher performance than the ZF equalizer. The aspect of channel equalization considered here is not novel, but there have been very few works that dealt with equalization in the context of the use of turbo codes, especially LDPC codes and polar codes for channel coding. In this respect, this research can be considered a contribution to the field of digital communications.

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“…The current work is a continuation of the previous papers in which a performance comparison was made between the zero forcing (ZF) or MMSE equalization preceded the decoding process using different codes [13,14], intending to evaluate the performance of the equalization that takes place inside the decoding process as in the case of turbo equalization. In this respect, the contributions of this article can be summarized as follows:…”

Section: Introductionmentioning

confidence: 99%

Iterative Equalization and Decoding over an Additive White Gaussian Noise Channel with ISI Using Low-Density Parity-Check Codes

Cuc,

Morgoș,

Grava

et al. 2023

Applied Sciences

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In this article we present an iterative system of equalization and decoding to manage the intersymbol interference over an additive white Gaussian noise (AWGN) channel. Following the classic turbo equalization scheme, the proposed system consists of low-density parity-check (LDPC) coding at the transmitter side; we applied a Log maximum a posteriori probability (Log-MAP) equalizer and min-sum LDPC decoding at the receiver side. The equalizer and decoder, linked through interleaving and deinterleaving, iteratively update each other’s information. We performed the performance analysis of the proposed system, bit error rate (BER) vs. signal-to-noise ratio (SNR), considering three different impulse responses of the channel (h). Our experimental results indicated that increasing the number of iterations performed by the LDPC decoder from 10 to 20 during the iterative process of equalization and decoding leads to better outcomes. The proposed system was compared with turbo equalization and separate equalization, performed before the decoding process with minimum mean-square error (MMSE) and LDPC decoding, in terms of BER vs. SNR, considering the three different h. Based on the analyzed results, it can be concluded that the equalization performance depends on both the impulse responses of the channel and the chosen decoding and equalization method; therefore, the equalization method does not always offer good results for any h.

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Performances Analysis of Turbo Codes, LDPC Codes and Polar Codes using AWGN channel with and without Inter Symbol Interference

Cited by 3 publications

References 12 publications

Investigation of IEEE 802.16e LDPC Code Application in PM-DQPSK System

Investigation of IEEE 802.16e LDPC Code Application in PM-DQPSK System

Performance Analysis of Turbo Codes, LDPC Codes, and Polar Codes over an AWGN Channel in the Presence of Inter Symbol Interference

Iterative Equalization and Decoding over an Additive White Gaussian Noise Channel with ISI Using Low-Density Parity-Check Codes

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