Forward Error Correction Scheme Research Articles

Efficient Pipeline Conflict Resolution for Layered QC-LDPC Decoders in OFDM-PON

Efficient Pipeline Conflict Resolution for Layered QC-LDPC Decoders in OFDM-PON

Design of Autoconfigurable Random Access NOMA for URLLC Industrial IoT Networking

Low power devices are massively deployed to facilitate real time sensing and data transmission requested in low power wide-area network (LPWAN). However, the dominating signaling, i.e. continuous phase modulation (CPM), barely gains attention in the context of supporting massive connectivity, not to mention ultra-reliable low-latency communications (URLLC), a primary concern in industrial network automation. To this end, auto-configurable nonorthogonal multiple access (AC-NOMA) based on CPM signaling is proposed. The term auto-configuration is used since each device selects a setup from a pool of configurations whenever connecting to the access point in a random and distributive way. It is proven, using ideal power allocation and phase shaping technique, AC-NOMA offers drastically improved user load and near capacity performance even in finite blocklength regime. Moreover, to enable massive yet sporadic access, slotted ALOHA is combined with AC-NOMA. It is proven that the resultant scheme outperforms power-domain NOMA in terms of throughput even with reduced transmit power and simple forward error correction schemes such as repetition and convolutional coding. The throughput is further improved using semi AC-NOMA with slightly increased latency. It is demonstrated that both designs can support very high user load while enabling URLLC in finite blocklength regime, where the packet size is merely 256 bits while the error rate is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$10^{-5}$</tex-math></inline-formula> , which are also desirable in a number of applications including satellite communications, visible light communications, etc.

Post-FEC performance evaluation of optical SDM systems with mode-dependent loss

This work is focused on the bit error rate (BER) performance of spatial division multiplexing (SDM) systems over an optical channel with mode-dependent loss or gain (collectively referred to in this paper as MDL). When the latter is non-negligible, the BER has a random nature that introduces the outage probability as an important performance metric for the system design and also impacts on the selection of a forward-error correction (FEC) scheme. In MDL-impaired SDM systems, the pre-FEC BER is a random variable whose probability density function (PDF) and coding gain depend on the signal-to-noise ratio (SNR) at the receiver input. Hence, the common and simple approach of adding a coding gain factor to the pre-FEC BER to obtain the post-FEC BER is not adequate, and numerical simulations are needed. In this paper, we simulate and analyze the performance in terms of post-FEC BER for two proposals of applying low-density parity check (LDPC) FEC encoder/decoder in a SDM system MDL-impaired and an optimal linear multiple input multiple output (MIMO) receiver. In the first one, the LDPC is applied independently to each mode, and in the second one, the LDPC is applied among all SDM modes. Simulation results indicate that the first proposal outperforms the second. Simplifications in the log-likelihood ratio (LLR) computations have also been considered.

Efficient learning-driven data transmission algorithm for cloud-to-thing continuum

In the cloud-to-thing continuum paradigm, the efficient transmission of learning-driven data is critical for facilitating real-time decision-making and continuous learning processes. Fountain codes have gained popularity as Forward Error Correction (FEC) schemes in application layer networking due to their ability to recover lost data packets. Gaussian Elimination (GE) algorithms, which form the core of Fountain codes, can be optimized to improve transmission efficiency. We introduces techniques that leverage GE algorithms to enhance the transmission of learning-driven data within the cloud-to-thing continuum. A fast matrix element architecture is developed to improve computational speed. Additionally, a pipelined normalization component based on binary trees is introduced to enable parallel processing. A pipelined elimination component utilizing binary trees is also presented to further boost transmission speeds and efficiency. These techniques are implemented using Field Programmable Gate Array (FPGA) technology. Their performance is evaluated against existing methods, demonstrating significant gains in transmission efficiency. By effectively managing increasing Internet traffic loads and optimizing the flow of learning-driven data, these approaches facilitate more efficient communication between cloud-based AI systems and edge devices. Ultimately, this research supports enhanced real-time decision-making and continuous learning processes across the full cloud-to-thing continuum.

Implementation of Turbo Trellis Coding Modulation Scheme for Fading Channel

In the context of data communication, encountering fading channels can lead to errors occurring at the receiving end due to multipath propagation. To address this challenge, researchers have persistently worked towards developing Error Correction Schemes that effectively manage these errors and guarantee error-free data reception for the receiver. One area of focus lies in the implementation of Forward Error Correction Schemes directly at the transmitter end. Nonetheless, integrating error correction coding using these schemes comes with the drawback of increased bandwidth requirements since additional bits must be included to facilitate error correction. Fortunately, there exists a coding scheme known as Trellis Coded Modulation (TCM), which specifically tackles this concern. In the case of TCM, the modulation scheme has been chosen based on the rate of the convolutional coding scheme. Nevertheless, TCM has certain limitations when it comes to correcting a high number of errors, which prompted the emergence of Turbo Coding. Turbo Coding employs two coders at the transmitter, arranged either in a serial or parallel configuration, along with an appropriate decoder at the receiver. This paper introduces a Turbo Coding scheme design utilizing convolutional coders with a rate of 2/3, arranged in a serially concatenated configuration, resulting in an effective rate of 4/9. For preserving bandwidth, the Turbo Coding is applied to TCM scheme. Consequently, when employing the convolutional coding scheme with a rate of 2/3, the modulation scheme has to be 8-QAM. However, to maintain bandwidth after coding, when utilizing the Turbo coding scheme with a rate of 4/9, the modulation scheme is upgraded to 512-QAM. MATLAB simulations were conducted to evaluate the error correcting capabilities of the designed scheme compared to the convolutional coding scheme that uses the constituent convolutional encoder. The comparison has also been made with the uncoded data communication utilizing simple QPSK modulation scheme. The results indicate that under Rician fading channel conditions, the Turbo Trellis Coding Modulation Scheme provides an approximate gain of 5 dB compared to the convolutional coding scheme and approximately 8 dB gain compared to uncoded one.

Design of Turbo Trellis Coding Modulation Scheme of Rate 4/9 for Rician Fading Channel

When the fading channels are encountered during data communication, errors are likely to occur at the receiving end due to multipath propagation. Researchers have been consistently striving to develop Error Correction Schemes that can effectively handle these errors and ensure error-free data reception at the receiver end. Of particular interest are the Forward Error Correction Schemes that can be implemented at the transmitter end itself. However, the implementation of error correction coding through these schemes incurs additional costs in terms of bandwidth expansion, as extra bits need to be added to facilitate error correction. Fortunately, there exists one coding scheme called Trellis Coded Modulation (TCM), which addresses this issue. TCM selects a modulation scheme based on the rate of the convolutional coding scheme. However, this coding technique has limitations in correcting the number of errors, leading to the development of Turbo Coding. This scheme utilizes two coders at the transmitter, arranged in either serial or parallel configuration, and a suitable decoder at the receiver. A design of Turbo Coding scheme has been presented in this paper, that employs convolutional coders having rate 2/3, in a serially concatenated configuration, providing an effective rate of 4/9. This turbo coding scheme is then applied to TCM scheme in order to preserve the bandwidth. Therefore, if using the convolutional coding scheme of rate 2/3, the modulation scheme is 8-QAM and in order to preserve bandwidth after coding, using the Turbo coding scheme of rate 4/9, then the modulation scheme will be 512-QAM. The simulations have been conducted in MATLAB and the error correcting capabilities of the designed scheme in comparison with convolutional coding scheme using the constituent convolutional encoder have also been compared. It has been observed that in the Rician fading channel conditions, the Turbo Trellis Coding Modulation Scheme provides approximately 5 dB gain compared to the convolutional coding scheme.

Real-Time FPGA Investigation of Potential FEC Schemes for 800G-ZR/ZR+ Forward Error Correction

Forward error correction (FEC) performance down to 1e-15 bit error rate (BER) of a open FEC code (OFEC), which was recently proposed for the 800G inter-data center interconnect (DCI) standard, is verified with a 100-piece-FPGA implementation at a record 400-Gbps throughput. Besides the OFEC, we also investigate the cons and pros of the concatenated staircase and Hamming code (CFEC) and multilevel codes (MLC) of a concatenated Low-Density Parity-Check (LDPC) and Turbo Product Code (TPC), which are the candidate schemes for the 800G-ZR FEC. The OFEC performance as a function of decoding iterations of Soft-in Soft-out (SISO) and Hard-in Hard-out (HIHO) is investigated, and FPGA emulations reveal the existence of an error flare of the OFEC with two SISO iterations and an severe error floor with one HIHO iteration even with four SISO iterations. Further investigations on different combinations of SISO and HIHO iterations, revealed that three SISO and two HIHO iterations are the optimal choice. Based on this iteration configuration, we studied the methods that decreasing the test patterns (TP) of SISO decoder and the soft bits to reduce the implementation complexity. Then we proposed the simplified OFEC scheme for 800G-ZR application, providing 1.81e-2 pre-FEC BER threshold with half power dissipation of standard OFEC, achieving a trade-off between the error correction performance and power dissipation. Finally, we investigated the performance of performance enhanced OFEC with 24.3% overhead and 2.5e-2 pre-FEC threshold, and finally, FEC candidates for the 800G-ZR+ applications are studied, indicating that the OFEC and channel polarized multilevel coding (CP MLC) are the most promising schemes.

Rate-Adaptive Concatenated Multi-Level Coding With Novel Probabilistic Amplitude Shaping

This paper proposes a new probabilistic amplitude shaping (PAS) approach for concatenated two-level multi-level coding (MLC). The proposed system is based on a concatenated forward error correction (FEC) scheme where outer codes are serially concatenated with inner two-level MLC. This concatenated two-level MLC scheme has recently been shown to have a potential for achieving better performance-complexity trade-offs than the conventional bit-interleaved coded modulation (BICM). Meanwhile, PAS has recently been demonstrated to offer remarkable performance gains as well as rate adaptivity. However, the majority of existing works on PAS assume the use of the binary reflected Gray code as a bit-labeling, and its application to coded modulation schemes with other bit-labelings, such as two-level MLC, may not be straightforward. In this paper, we devise a bit-labeling scheme and propose a new PAS structure for an efficient integration of PAS with two-level MLC systems. More specifically, we propose to generate <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">signed</i> amplitude symbols with the distribution matcher (DM) for maximizing both coding and shaping gains achieved by two-level MLC and PAS, respectively, while the conventional PAS generates <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">unsigned</i> amplitude symbols. It is demonstrated by simulation results that, with 256QAM and inner polar codes, the proposed two-level MLC with PAS simultaneously offers 75% reduction in the number of required inner encoding and soft-decision (SD) decoding operations for given outer and inner FEC code lengths, and up to 0.3 dB performance gain over the conventional PAS scheme.

Design of Robust Video Transmission System by Using Efficient Forward Error Correction Scheme

The advent of modern digital technologies has made multimedia communication systems one of the most demanding technologies of the time. The use of available bandwidth for efficient and errorless multimedia communication is the key challenge for the wireless communication research community. However, a wireless network has the disadvantage of being prone to random channel noise and data contamination. This paper proposes a robust video transmission framework by using an efficient forward error correction technique. In this work, the experimental performance of widely used forward error correction codes i.e., Convolution codes, LDPC codes, Turbo codes, and Concatenated codes, are compared based on their capability to compensate the channel noise and distortion. An efficient encoding scheme is devised for the transmission of YUV encoded frames by using the selected FEC codes in a noisy channel environment. The retrieved video is analysed by using the Peak Signal-to-Noise ratio and bit error rate as performance metrics. The results and cross comparison shows that concatenated codes have a handsome improvement in avoiding channel contamination and distortion.

Sliding-Window Forward Error Correction Based on Reference Order for Real-Time Video Streaming

In real-time video streaming, data packets are transported over the network from a transmitter to a receiver. The quality of the received video fluctuates as the network conditions change, and it can degrade substantially when there is considerable packet loss. Forward error correction (FEC) techniques can be used to recover lost packets by incorporating redundant data. Conventional FEC schemes do not work well when scalable video coding (SVC) is adopted. In this paper, we propose a novel FEC scheme that overcomes the drawbacks of these schemes by considering the reference picture structure of SVC and weighting the reference pictures more when FEC redundancy is applied. The experimental results show that the proposed FEC scheme outperforms conventional FEC schemes.

Experimental Demonstration of Rate-Adaptive Concatenated Codes for Flexible Optical Networks

We experimentally demonstrate a rate-adaptive concatenated forward error correction (FEC) scheme to minimize the information rate loss due to varying channel conditions. The concatenated coding scheme is based on inner soft-decision polar code and outer hard-decision staircase code. An experiment in a wavelength-division multiplexed (WDM) system with different SNR per WDM channel is performed by employing concatenated codes with various coded modulation schemes over a target distance of 140km which is relevant for extending the reach of data center interconnects. Experimental results show that the achieved data rate of the WDM system can be improved up to 37.6% with the proposed coding scheme w.r.t. the fixed code rate ZR FEC.

Satellite forward VDES channel modeling and impact on higher‐layer performance

SummaryVHF data exchange system (VDES) is an emerging maritime communications standard that is meant to provide ship‐to‐shore, shore‐to‐ship, and ship‐to‐ship information services. VDES also includes a satellite component to extend the service coverage also to the high sea. Ships can receive important information via VDES and access this service via satellite when they are far from the shore. This paper uses data taken during a measurement campaign to develop an ON‐OFF model for the VDE‐SAT downlink channel taking the multipath effects caused by sea reflections into account. This model has been used to evaluate the impact of packet‐level forward error correction (FEC) schemes (i.e., ideal codes, RaptorQ codes, and 2‐Dimension Reed‐Solomon codes) to further protect transmissions from deep fading events and to evaluate the impact at the transport level considering the possibility to adopt the transmission control protocol (TCP) for a file map delivery service.

Low complexity iterative decoding of Reed–Solomon convolutional concatenated codes

SummaryThe power limitation is the predominant challenge for achieving a reliable communication transmission for aerospace systems. Therefore, it is appealing to use robust channel coding techniques with a low decoding complexity. The robust forward error correction scheme that uses a Reed–Solomon as an outer code concatenated with a convolutional code as an inner code is an attractive scheme whose applications are widely used in wireless and space communications. However, iterative soft‐decision decoding of that concatenated code is still an open research challenge. This paper proposes a reduced complexity iterative decoding algorithm for this concatenated coding scheme. The soft‐output adaptive Viterbi algorithm with a dynamic discarding threshold has been adopted to decode the inner convolutional code while the outer decoder will be based on a bit‐level modified Chase algorithm. We have used the Hamming metric instead of the Euclidean metric, which is not only much less complex but also overcomes the lack of channel information on the outer decoder input. Simulation results using the proposed soft information exchange decoding mechanism show that a considerable performance enhancement over the classical decoding scheme as well as a significant reduction in complexity over the existing decoding algorithms that use an iterative process to decode this concatenated coding scheme. The adaptive decoding of the inner convolutional code can gain a complexity reduction of 90% after 5 iterations compared to the soft‐output Viterbi algorithm while maintaining the small performance loss from the maximum a posteriori decoding algorithm.

Low-Latency Network-Adaptive Error Control for Interactive Streaming

We introduce a novel network-adaptive algorithm that is suitable for alleviating network packet losses for low-latency interactive communications between a source and a destination. Our network-adaptive algorithm estimates in real-time the best parameters of a recently proposed streaming code that uses forward error correction (FEC) to correct both arbitrary and burst losses, which cause a crackling noise and undesirable jitters, respectively in audio. In particular, the destination estimates appropriate coding parameters based on its observed packet loss pattern and sends them back to the source for updating the underlying code. Besides, a new explicit construction of practical low-latency streaming codes that achieve the optimal tradeoff between the capability of correcting arbitrary losses and the capability of correcting burst losses is used. Simulation evaluations based on statistical losses and real-world packet loss traces reveal the following: (i) Our proposed network-adaptive algorithm combined with our optimal streaming codes can achieve significantly higher performance compared to uncoded and non-adaptive FEC schemes over UDP (User Datagram Protocol); (ii) Our explicit streaming codes can significantly outperform traditional MDS (maximum-distance separable) streaming schemes when they are used along with our network-adaptive algorithm. In addition, we study different factors that can affect the performance of our network-adaptive algorithm.

Low-Complexity Rate- and Channel-Configurable Concatenated Codes

A low-complexity rate- and channel-configurable forward error-correction (FEC) scheme is proposed, consisting of an inner low-density parity-check code concatenated with an outer zipper code. A tool is developed to optimize a multi-level code architecture so that it can operate at multiple transmission rates, channel qualities, and modulation orders. The optimization criterion is selected to maintain a low estimated data-flow in its decoding operation. A hardware-friendly quasi-cyclic structure is considered for the inner code and the performance and complexity is reported for various designed FEC configurations. Compared to existing FEC schemes, the proposed designs deliver a similar performance with up to 63% reduction in decoding complexity or provide up to 0.6 dB coding gain at a similar decoding complexity.

Error correction for low power sensors in asynchronous communication

We propose a forward error correction scheme for asynchronous sampling via level crossing (LC) sampling and time encoding, where the dominant errors consist of pulse deletions and insertions, and where encoding is required to take place in an instantaneous fashion. For LC sampling the presented scheme consists of a combination of an outer systematic convolutional code, an embedded inner marker code, and power-efficient frequency-shift keying modulation at the sensor node. Decoding is first obtained via a maximum a-posteriori (MAP) decoder for the inner marker code, which achieves synchronization for the insertion and deletion channel, followed by MAP decoding for the outer convolutional code. Besides investigating the rate trade-off between marker and convolutional codes, we also show that residual redundancy in the asynchronously sampled source signal can be successfully exploited in combination with redundancy only from a marker code. This provides a low complexity alternative for deletion and insertion error correction compared to using explicit redundancy. For time encoding, only the pulse timing is of relevance at the receiver, and the outer channel code is replaced by a quantizer to represent the relative position of the pulse timing. Numerical simulations show that LC sampling outperforms time encoding in the low to moderate signal-to-noise ratio regime by a large margin.

Efficient FEC Scheme for Solar-Powered WSNs Considering Energy and Link-Quality

In solar-powered wireless sensor networks (SP-WSNs), the best use of harvested energy is more important than minimizing energy consumption since energy can be supplied periodically. Meanwhile, as is well known, the reliability of the communication between sensor nodes is very limited due to the resource constraints of sensor nodes. In this paper, we propose an efficient forward error correction (FEC) scheme which can give solar-powered wireless sensor networks more reliable communication. First, the proposed scheme provides energy-adaptive operation for the best use of solar energy. It calculates the amount of surplus energy which can be used for extra operations and then determines the number of additional parity bits for FEC according to this amount of surplus energy. At the same time, it also provides a link quality model that is used to calculate the appropriate number of parity bits for error recovery required for the current data communication environment. Finally, by considering these two parity sizes, it is possible to determine the number of parity bits that can maximize the data reliability without affecting the blacking out of nodes. The evaluation of the performance of the approach was performed by comparing the amount of data collected at the sink node and the number of blackout nodes with other schemes.

Fixed Reception Performance of FDM-based Transmission System for Advanced ISDB-T

With the aim of improving the quality and expanding the functions of digital terrestrial television broadcasting services, we have been developing an advanced transmission system that inherits key features of the current Integrated Services Digital Broadcasting-Terrestrial (ISDB-T) system, which employs hierarchical transmission based on frequency division multiplexing (FDM) and a segment structure. The advanced ISDB-T system has a new signal frame structure that enables bandwidth to be flexibly allocated to multiple services for different reception scenarios, such as fixed reception and mobile reception, compared with ISDB-T. By introducing transmission technologies such as the latest forward error correction and modulation scheme, this specification has high spectral efficiency and transmission robustness, i.e., the transmission capacity increases by about 10 Mbps for the same required carrier to noise ratio (CNR) in comparison with the current ISDB-T system, or the required CNR can be reduced by about 7 dB for the same transmission capacity. We describe the channel coding scheme and evaluated the performance of bit-interleaved coded modulation (BICM) in simulations. This paper provides a BICM selection guideline based on the simulation results for fixed reception scenarios toward the practical application of advanced ISDB-T.

Adaptive Coded Modulation for IM/DD Free-Space Optical Backhauling: A Probabilistic Shaping Approach

In this paper, we propose a practical adaptive coding modulation scheme to approach the capacity of free-space optical (FSO) channels with intensity modulation/direct detection based on probabilistic shaping. The encoder efficiently adapts the transmission rate to the signal-to-noise ratio, accounting for the fading induced by the atmospheric turbulence. The transponder can support an arbitrarily large number of transmission modes using a low complexity channel encoder with a small set of supported rates. Hence, it can provide a solution for FSO backhauling in terrestrial and satellite communication systems to achieve higher spectral efficiency. We propose two algorithms to determine the capacity and capacity-achieving distribution of the scheme with unipolar M-ary pulse amplitude modulation (M-PAM) signaling. Then, the signal constellation is probabilistically shaped according to the optimal distribution, and the shaped signal is channel encoded by an efficient binary forward error correction scheme. Extensive numerical results and simulations are provided to evaluate the performance. The proposed scheme yields a rate close to the tightest lower bound on the capacity of FSO channels. For instance, the coded modulator operates within 0.2 dB from the M-PAM capacity, and it outperforms uniform signaling with more than 1.7 dB, at a transmission rate of 3 bits per channel use.

Wide range rate adaptation of QAM-based probabilistic constellation shaping using a fixed FEC with blind adaptive equalization.

We investigate the rate adaptability of quadrature amplitude modulation (QAM)-based probabilistic constellation shaping (PCS) using a fixed forward error correction (FEC) scheme over a wide range of information rates (IRs). Blind adaptive equalization that does not sacrifice any of the IRs was adopted. We show that the conventional decision directed least mean square (DDLMS) algorithm can cause a problem of mis-convergence when it is applied to the PCS of a low IR. To avoid the mis-convergence of DDLMS, we propose a DDLMS-based algorithm that simultaneously minimizes the error between the average symbol power of filter outputs and that of a transmitted PCS signal. Using this technique, we conducted a wavelength-division multiplexed transmission experiment with 32-Gbaud 16/64QAM-based PCS and a fixed FEC of a low-density parity-check code for DVBS-2, where the IR of PCS was optimized at each transmission distance. We confirmed that the data rate of PCS with a fixed FEC and DSP configuration could be improved up to 1.9 times compared with that of QAM-only rate adaptation and that 64QAM-based PCS could provide a wider range of transmission distance and IR while almost covering that of the 16QAM-based one.