This letter proposes a sliced-gated-convolutional neural network with belief propagation(SGCNN-BP) architecture for decoding long codes under correlated noise. The basic idea of SGCNNBP is using Neural Networks(NN) to...This letter proposes a sliced-gated-convolutional neural network with belief propagation(SGCNN-BP) architecture for decoding long codes under correlated noise. The basic idea of SGCNNBP is using Neural Networks(NN) to transform the correlated noise into white noise, setting up the optimal condition for a standard BP decoder that takes the output from the NN. A gate-controlled neuron is used to regulate information flow and an optional operation—slicing is adopted to reduce parameters and lower training complexity. Simulation results show that SGCNN-BP has much better performance(with the largest gap being 5dB improvement) than a single BP decoder and achieves a nearly 1dB improvement compared to Fully Convolutional Networks(FCN).展开更多
A novel Joint Source and Channel Decoding (JSCD) scheme for Variable Length Codes (VLCs) concatenated with turbo codes utilizing a new super-trellis decoding algorithm is presented in this letter. The basic idea of ou...A novel Joint Source and Channel Decoding (JSCD) scheme for Variable Length Codes (VLCs) concatenated with turbo codes utilizing a new super-trellis decoding algorithm is presented in this letter. The basic idea of our decoding algorithm is that source a priori information with the form of bit transition probabilities corresponding to the VLC tree can be derived directly from sub-state transitions in new composite-state represented super-trellis. A Maximum Likelihood (ML) decoding algorithm for VLC sequence estimations based on the proposed super-trellis is also described. Simu-lation results show that the new iterative decoding scheme can obtain obvious encoding gain especially for Reversible Variable Length Codes (RVLCs),when compared with the classical separated turbo decoding and the previous joint decoding not considering source statistical characteristics.展开更多
Soft decode-and-forward(DF) can combine the advantages of both amplify-and-forward and hard DF in relay channels. In this paper, we propose a low-complexity soft DF scheme based on polar codes, which features two key ...Soft decode-and-forward(DF) can combine the advantages of both amplify-and-forward and hard DF in relay channels. In this paper, we propose a low-complexity soft DF scheme based on polar codes, which features two key techniques: a low-complexity cyclic redundancy check(CRC) aided list successive cancellation(CALSC) decoder and a soft information calculation method. At the relay node, a low-complexity CALSC decoder is designed to reduce the computational complexity by adjusting the list size according to the reliabilities of decoded bits. Based on the path probability metric of the CALSC decoder, we propose a method to compute the soft information of the decoded bits in CALSC. Simulation results show that our proposed scheme outperforms the soft DF based on low-density parity-check codes and the soft DF with belief propagation or soft cancellation decoder, especially in the case when the source-relay channel is at the high signal-to-ratio region.展开更多
To restrain the interference of co-channel users using space-time block coding (STBC), the proposed Gaussian-forcing soft decision multi-user detection (GFSDMUD) algorithm is applied in fiat-fading channels by usi...To restrain the interference of co-channel users using space-time block coding (STBC), the proposed Gaussian-forcing soft decision multi-user detection (GFSDMUD) algorithm is applied in fiat-fading channels by using the relation among the users' signals, which can enhance the capacity by introducing co-channel users. During iterations, extrinsic information is calculated and exchanged between a soft multi-user detector and a bank of turbo decoders to achieve refined estimates of the users' signals. The simulations show that the proposed iterative receiver techniques provide significant performance improvement around 2 dB over conventional noniterative methods. Furthermore, iterative multi-user space-time processing techniques offer substantial performance gains around 8 dB by adding the number of receiver antennas from 4 to 6, and the system performance can be enhanced by using this strategy in multi-user STBC systems, which is very important for enlarging the system capacity.展开更多
This paper derives a low-complexity turbo equalization algorithm for turbo coded multiple input multiple output/ orthogonal frequency division multiplexing systems. This algorithm consists of soft-output decision-feed...This paper derives a low-complexity turbo equalization algorithm for turbo coded multiple input multiple output/ orthogonal frequency division multiplexing systems. This algorithm consists of soft-output decision-feedback equalization with a probabilistic data association algorithm and a soft-input soft-output turbo channel decoder using iterative operations. In each iteration, extrinsic information extracted from the probabilistic data association algorithm detector and from the channel decoder is used as the prior information for the next iteration to realize iterative channel equalization and channel decoding, Our simulation results show that the algorithm improves the signal noise ratio around 1 dB with bit error rate reaching 10 -6 when the Eb/ N0 - 4 dB compared to minimum mean square error and match filter, and can greatly reduce the intersymbol interference at a low overall complexity of O( N^3) after 2 iterations.展开更多
基金supported by Beijing Natural Science Foundation (L202003)。
文摘This letter proposes a sliced-gated-convolutional neural network with belief propagation(SGCNN-BP) architecture for decoding long codes under correlated noise. The basic idea of SGCNNBP is using Neural Networks(NN) to transform the correlated noise into white noise, setting up the optimal condition for a standard BP decoder that takes the output from the NN. A gate-controlled neuron is used to regulate information flow and an optional operation—slicing is adopted to reduce parameters and lower training complexity. Simulation results show that SGCNN-BP has much better performance(with the largest gap being 5dB improvement) than a single BP decoder and achieves a nearly 1dB improvement compared to Fully Convolutional Networks(FCN).
基金Supported by the National Natural Science Foundation of China (No.90304003, No.60573112, No.60272056)the Foundation Project of China (No.A1320061262).
文摘A novel Joint Source and Channel Decoding (JSCD) scheme for Variable Length Codes (VLCs) concatenated with turbo codes utilizing a new super-trellis decoding algorithm is presented in this letter. The basic idea of our decoding algorithm is that source a priori information with the form of bit transition probabilities corresponding to the VLC tree can be derived directly from sub-state transitions in new composite-state represented super-trellis. A Maximum Likelihood (ML) decoding algorithm for VLC sequence estimations based on the proposed super-trellis is also described. Simu-lation results show that the new iterative decoding scheme can obtain obvious encoding gain especially for Reversible Variable Length Codes (RVLCs),when compared with the classical separated turbo decoding and the previous joint decoding not considering source statistical characteristics.
基金supported by the National Natural Science Foundation of China(No.61171099,No.61671080),Nokia Beijing Bell lab
文摘Soft decode-and-forward(DF) can combine the advantages of both amplify-and-forward and hard DF in relay channels. In this paper, we propose a low-complexity soft DF scheme based on polar codes, which features two key techniques: a low-complexity cyclic redundancy check(CRC) aided list successive cancellation(CALSC) decoder and a soft information calculation method. At the relay node, a low-complexity CALSC decoder is designed to reduce the computational complexity by adjusting the list size according to the reliabilities of decoded bits. Based on the path probability metric of the CALSC decoder, we propose a method to compute the soft information of the decoded bits in CALSC. Simulation results show that our proposed scheme outperforms the soft DF based on low-density parity-check codes and the soft DF with belief propagation or soft cancellation decoder, especially in the case when the source-relay channel is at the high signal-to-ratio region.
文摘To restrain the interference of co-channel users using space-time block coding (STBC), the proposed Gaussian-forcing soft decision multi-user detection (GFSDMUD) algorithm is applied in fiat-fading channels by using the relation among the users' signals, which can enhance the capacity by introducing co-channel users. During iterations, extrinsic information is calculated and exchanged between a soft multi-user detector and a bank of turbo decoders to achieve refined estimates of the users' signals. The simulations show that the proposed iterative receiver techniques provide significant performance improvement around 2 dB over conventional noniterative methods. Furthermore, iterative multi-user space-time processing techniques offer substantial performance gains around 8 dB by adding the number of receiver antennas from 4 to 6, and the system performance can be enhanced by using this strategy in multi-user STBC systems, which is very important for enlarging the system capacity.
文摘This paper derives a low-complexity turbo equalization algorithm for turbo coded multiple input multiple output/ orthogonal frequency division multiplexing systems. This algorithm consists of soft-output decision-feedback equalization with a probabilistic data association algorithm and a soft-input soft-output turbo channel decoder using iterative operations. In each iteration, extrinsic information extracted from the probabilistic data association algorithm detector and from the channel decoder is used as the prior information for the next iteration to realize iterative channel equalization and channel decoding, Our simulation results show that the algorithm improves the signal noise ratio around 1 dB with bit error rate reaching 10 -6 when the Eb/ N0 - 4 dB compared to minimum mean square error and match filter, and can greatly reduce the intersymbol interference at a low overall complexity of O( N^3) after 2 iterations.