Deep learning-based semantic communication has achieved remarkable progress with CNNs and Transformers.However,CNNs exhibit constrained performance in high-resolution image transmission,while Transformers incur high c...Deep learning-based semantic communication has achieved remarkable progress with CNNs and Transformers.However,CNNs exhibit constrained performance in high-resolution image transmission,while Transformers incur high computational cost due to quadratic complexity.Recently,VMamba,a novel state space model with linear complexity and exceptional long-range dependency modeling capabilities,has shown great potential in computer vision tasks.Inspired by this,we propose MNTSCC,an efficient VMamba-based nonlinear joint source-channel coding(JSCC)model for wireless image transmission.Specifically,MNTSCC comprises a VMamba-based nonlinear transform module,an MCAM entropy model,and a JSCC module.In the encoding stage,the input image is first encoded into a latent representation via the nonlinear transformation module,which is then processed by the MCAM for source distribution modeling.The JSCC module then optimizes transmission efficiency by adaptively assigning transmission rate to the latent representation according to the estimated entropy values.The proposedMCAMenhances the channel-wise autoregressive entropy model with attention mechanisms,which enables the entropy model to effectively capture both global and local information within latent features,thereby enabling more accurate entropy estimation and improved rate-distortion performance.Additionally,to further enhance the robustness of the system under varying signal-to-noise ratio(SNR)conditions,we incorporate SNR adaptive net(SAnet)into the JSCCmodule,which dynamically adjusts the encoding strategy by integrating SNRinformationwith latent features,thereby improving SNR adaptability.Experimental results across diverse resolution datasets demonstrate that the proposed method achieves superior image transmission performance compared to existing CNN-and Transformer-based semantic communication models,while maintaining competitive computational efficiency.In particular,under an Additive White Gaussian Noise(AWGN)channel with SNR=10 dB and a channel bandwidth ratio(CBR)of 1/16,MNTSCC consistently outperforms NTSCC,achieving a 1.72 dB Peak Signal-to-Noise Ratio(PSNR)gain on the Kodak24 dataset,0.79 dB on CLIC2022,and 2.54 dB on CIFAR-10,while reducing computational cost by 32.23%.The code is available at https://github.com/WanChen10/MNTSCC(accessed on 09 July 2025).展开更多
Deep learning-based Joint Source-Channel Coding(JSCC)is a crucial component in semantic communication,and recent research has made significant progress in adapting to different channels.In this paper,we propose a mult...Deep learning-based Joint Source-Channel Coding(JSCC)is a crucial component in semantic communication,and recent research has made significant progress in adapting to different channels.In this paper,we propose a multi-stage progressive technique called Deep learning based Progressive Joint Source-Channel Coding(DP-JSCC).This approach partitions the source into multiple stages and transmits the signals continuously.The receiver gradually enhances the quality of image reconstruction by progressively receiving the signals,offering greater flexibility compared to existing dynamic rate transmission methods.The model adopts a lightweight architectural design,where we introduce an efficient module called the Inverted Shuffle Attention Bottleneck(ISAB)and incorporate self-attention mechanisms in the encoding and decoding process to capture signal correlations and establish long-range dependencies.Additionally,we introduce the Progressive Focus Weight Allocation(PFWA)method to improve the image reconstruction capability in progressive transmission tasks.These design enhance the expressive capacity of the model.Simulation results demonstrate that DP-JSCC can flexibly adjust the transmission rate according to requirements without the need for retraining or deployment,enabling continuous optimization of signals at different rates.Furthermore,compared to stateof-the-art JSCC methods,DP-JSCC exhibits advantages in terms of computational complexity,parameter count,and reconstruction performance.展开更多
Semantic secure communication is an emerging field that combines the principles of source-channel coding with the need for secure data transmission.It is of great significance in modern communications to protect the c...Semantic secure communication is an emerging field that combines the principles of source-channel coding with the need for secure data transmission.It is of great significance in modern communications to protect the confidentiality and privacy of sensitive information and prevent information leaks and malicious attacks.This paper presents a novel approach to semantic secure communication through the utilization of joint source-channel coding,which is based on the design of an automated joint source-channel coding algorithm and an encryption and decryption algorithm based on semantic security.The traditional and state-of-the-art joint source-channel coding algorithms are selected as two baselines for different comparison purposes.Experimental results demonstrate that our proposed algorithm outperforms the first baseline algorithm,the traditional source-channel coding,by 61.21%in efficiency under identical channel conditions(SNR=15 dB).In security,our proposed method can resist 2 more types of attacks compared to the two baselines,exhibiting nearly no increases in time consumption and error rate compared to the state-of-the-art joint source-channel coding algorithm while the secure semantic communication is supported.展开更多
Reversible data hiding in encrypted images(RDHEI)is essential for safeguarding sensitive information within the encrypted domain.In this study,we propose an intelligent pixel predictor based on a residual group block ...Reversible data hiding in encrypted images(RDHEI)is essential for safeguarding sensitive information within the encrypted domain.In this study,we propose an intelligent pixel predictor based on a residual group block and a spatial attention module,showing superior pixel prediction performance compared to existing predictors.Additionally,we introduce an adaptive joint coding method that leverages bit-plane characteristics and intra-block pixel correlations to maximize embedding space,outperforming single coding approaches.The image owner employs the presented intelligent predictor to forecast the original image,followed by encryption through additive secret sharing before conveying the encrypted image to data hiders.Subsequently,data hiders encrypt secret data and embed them within the encrypted image before transmitting the image to the receiver.The receiver can extract secret data and recover the original image losslessly,with the processes of data extraction and image recovery being separable.Our innovative approach combines an intelligent predictor with additive secret sharing,achieving reversible data embedding and extraction while ensuring security and lossless recovery.Experimental results demonstrate that the predictor performs well and has a substantial embedding capacity.For the Lena image,the number of prediction errors within the range of[-5,5]is as high as 242500 and our predictor achieves an embedding capacity of 4.39 bpp.展开更多
Along with the proliferating research interest in semantic communication(Sem Com),joint source channel coding(JSCC)has dominated the attention due to the widely assumed existence in efficiently delivering information ...Along with the proliferating research interest in semantic communication(Sem Com),joint source channel coding(JSCC)has dominated the attention due to the widely assumed existence in efficiently delivering information semantics.Nevertheless,this paper challenges the conventional JSCC paradigm and advocates for adopting separate source channel coding(SSCC)to enjoy a more underlying degree of freedom for optimization.We demonstrate that SSCC,after leveraging the strengths of the Large Language Model(LLM)for source coding and Error Correction Code Transformer(ECCT)complemented for channel coding,offers superior performance over JSCC.Our proposed framework also effectively highlights the compatibility challenges between Sem Com approaches and digital communication systems,particularly concerning the resource costs associated with the transmission of high-precision floating point numbers.Through comprehensive evaluations,we establish that assisted by LLM-based compression and ECCT-enhanced error correction,SSCC remains a viable and effective solution for modern communication systems.In other words,separate source channel coding is still what we need.展开更多
In order to provide ultra low-latency and high energy-efficient communication for intelligences,the sixth generation(6G)wireless communication networks need to break out of the dilemma of the depleting gain of the sep...In order to provide ultra low-latency and high energy-efficient communication for intelligences,the sixth generation(6G)wireless communication networks need to break out of the dilemma of the depleting gain of the separated optimization paradigm.In this context,this paper provides a comprehensive tutorial that overview how joint source-channel coding(JSCC)can be employed for improving overall system performance.For the purpose,we first introduce the communication requirements and performance metrics for 6G.Then,we provide an overview of the source-channel separation theorem and why it may not hold in practical applications.In addition,we focus on two new JSCC schemes called the double low-density parity-check(LDPC)codes and the double polar codes,respectively,giving their detailed coding and decoding processes and corresponding performance simulations.In a nutshell,this paper constitutes a tutorial on the JSCC scheme tailored to the needs of future 6G communications.展开更多
An improved FGS (Fine Granular Scalability) coding method is proposed in this letter, which is based on human visual characteristics. This method adjusts FGS coding frame rate according to the evaluation of video sequ...An improved FGS (Fine Granular Scalability) coding method is proposed in this letter, which is based on human visual characteristics. This method adjusts FGS coding frame rate according to the evaluation of video sequences so as to improve the coding efficiency and subject perceived quality of reconstructed images. Finally, a fine granular joint source channel coding is proposed based on the source coding method, which not only utilizes the network resources efficiently, but guarantees the reliable transmission of video information.展开更多
Realtime speech communications require high efficient compression algorithms to encode speech signals. As the compressed speech parameters are highly sensitive to transmission errors, robust source and channel decodin...Realtime speech communications require high efficient compression algorithms to encode speech signals. As the compressed speech parameters are highly sensitive to transmission errors, robust source and channel decoding and demodulation schemes are both important and of practical use. In this paper, an it- erative joint souree-channel decoding and demodulation algorithm is proposed for mixed excited linear pre- diction （MELP） vocoder by both exploiting the residual redundancy and passing soft information through- out the receiver while introducing systematic global iteration process to further enhance the performance. Being fully compatible with existing transmitter structure, the proposed algorithm does not introduce addi- tional bandwidth expansion and transmission delay. Simulations show substantial error correcting perfor- mance and synthesized speech quality improvement over conventional separate designed systems in delay and bandwidth constraint channels by using the joint source-channel decoding and demodulation （JSCCM） algorithm.展开更多
Robust video streaming through high error prone wireless channel has attracted much attention. In this paper the authors introduce an effective algorithm by joining the Unequal Error Protection ability of the channel ...Robust video streaming through high error prone wireless channel has attracted much attention. In this paper the authors introduce an effective algorithm by joining the Unequal Error Protection ability of the channel multiplexing protocol H.223 Annex D, and the new H.263++ Annex V Data Partition together. Based on the optimal trade off of these two technologies, the Joint Source and Channel Coding algorithm can result in stronger error resilience. The simulation results have shown its superiority against separate coding mode and some Unequal Error Protection mode under recommended wireless channel error patterns.展开更多
The existing depth video coding algorithms are generally based on in-loop depth filters, whose performance are unstable and easily affected by the outliers. In this paper, we design a joint weighted sparse representat...The existing depth video coding algorithms are generally based on in-loop depth filters, whose performance are unstable and easily affected by the outliers. In this paper, we design a joint weighted sparse representation-based median filter as the in-loop filter in depth video codec. It constructs depth candidate set which contains relevant neighboring depth pixel based on depth and intensity similarity weighted sparse coding, then the median operation is performed on this set to select a neighboring depth pixel as the result of the filtering. The experimental results indicate that the depth bitrate is reduced by about 9% compared with anchor method. It is confirmed that the proposed method is more effective in reducing the required depth bitrates for a given synthesis quality level.展开更多
Semantic communication(SemCom)aims to achieve high-fidelity information delivery under low communication consumption by only guaranteeing semantic accuracy.Nevertheless,semantic communication still suffers from unexpe...Semantic communication(SemCom)aims to achieve high-fidelity information delivery under low communication consumption by only guaranteeing semantic accuracy.Nevertheless,semantic communication still suffers from unexpected channel volatility and thus developing a re-transmission mechanism(e.g.,hybrid automatic repeat request[HARQ])becomes indispensable.In that regard,instead of discarding previously transmitted information,the incremental knowledge-based HARQ(IK-HARQ)is deemed as a more effective mechanism that could sufficiently utilize the information semantics.However,considering the possible existence of semantic ambiguity in image transmission,a simple bit-level cyclic redundancy check(CRC)might compromise the performance of IK-HARQ.Therefore,there emerges a strong incentive to revolutionize the CRC mechanism,thus more effectively reaping the benefits of both SemCom and HARQ.In this paper,built on top of swin transformer-based joint source-channel coding(JSCC)and IK-HARQ,we propose a semantic image transmission framework SC-TDA-HARQ.In particular,different from the conventional CRC,we introduce a topological data analysis(TDA)-based error detection method,which capably digs out the inner topological and geometric information of images,to capture semantic information and determine the necessity for re-transmission.Extensive numerical results validate the effectiveness and efficiency of the proposed SC-TDA-HARQ framework,especially under the limited bandwidth condition,and manifest the superiority of TDA-based error detection method in image transmission.展开更多
To improve the performance of MIMO-OFDM video transmission systems on the limitation of wireless bandwidth and transmitting power,we propose an adaptive joint resource allocation algorithm with unequal error protectio...To improve the performance of MIMO-OFDM video transmission systems on the limitation of wireless bandwidth and transmitting power,we propose an adaptive joint resource allocation algorithm with unequal error protection(UEP) based on joint source-channel coding(JSCC) according to H.264 video compression standard and RCPT channel coding.According to different thresholds of the average SNR of subchannels,the algorithm dynamically allocates the source coding parameters of original video data and the channel coding parameters of RCPT,which realizes UEP for the compressed video data of different importance.Through the bit and power allocation based on MQAM modulation and the subspace allocation based on beamforming technology for different subcarriers,an adaptive joint resource allocation making full use of space-frequency domain resources have been realized.The simulation results indicate that the algorithm improves the adaptability of video transmission systems in different wireless environments and the quality of video retrieval.展开更多
An adaptive joint source channel bit allocation method for video communications over error-prone channel is proposed.To protect the bit-streams from the channel bit errors,the rate compatible punctured convolution(RCP...An adaptive joint source channel bit allocation method for video communications over error-prone channel is proposed.To protect the bit-streams from the channel bit errors,the rate compatible punctured convolution(RCPC)code is used to produce coding rates varying from 4/5 to 1/2 using the same encoder and the Viterbi decoder.An expected end-to-end distortion model was presented to estimate the distortion introduced in compressed source coding due to quantization and channel bit errors jointly.Based on the proposed end-to-end distortion model,an adaptive joint source-channel bit allocation method was proposed under time-varying error-prone channel conditions.Simulated results show that the proposed methods could utilize the available channel capacity more efficiently and achieve better video quality than the other fixed coding-based bit allocation methods when transmitting over error-prone channels.展开更多
For two-way video communications over wireless channels using the automatic repeat request (ARQ) retransmission scheme, TMN8 rate control scheme is not effective in minimizing the number of frames skipped and cannot g...For two-way video communications over wireless channels using the automatic repeat request (ARQ) retransmission scheme, TMN8 rate control scheme is not effective in minimizing the number of frames skipped and cannot guarantee video quality during the retransmissions of error packets. This paper presents a joint source channel bit allocation scheme that allocates target bits according to encoder buffer fullness and estimation of channel condition by retransmission information. The results obtained from implementing our scheme in H.263+coder over wireless channel model show that our proposed scheme encodes the video sequences with lower and steadier buffer delay, fewer frames skipped and higher average PSNR compared to TMN8.展开更多
A novel joint source channel distortion model was proposed, which can essentially estimate the average distortion in progressive image transmission. To improve the precision of the model, the redundancy generated by a...A novel joint source channel distortion model was proposed, which can essentially estimate the average distortion in progressive image transmission. To improve the precision of the model, the redundancy generated by a forbidden symbol in the arithmetic codes is used to distinguish the quantization distortion and the channel distortion, all the coefficients from the first error one to the end of the sequence are set to be a value within the variance range of the coefficients instead of zero, then the error propagation coming from the entropy coding can be essentially estimated, which is disregarded in the most conventional joint source channel coding (JSCC) systems. The precision of the model in terms of average peak-signal-to-noise has been improved about 0.5 dB compared to classical works. An efficient unequal error protection system based on the model is developed, and can be used in the wireless communication systems.展开更多
We present an unequal decoding power allocation （UDPA） approach for minimization of the receiver power consumption subject to a given quality of service （QoS）, by exploiting data partitioning and turbo decoding. W...We present an unequal decoding power allocation （UDPA） approach for minimization of the receiver power consumption subject to a given quality of service （QoS）, by exploiting data partitioning and turbo decoding. We assign unequal decoding power of forward error correction （FEC） to data partitions with different priority by jointly considering the source coding, channel coding and receiver power consumption. The proposed scheme is applied to H.264 video over additive white Gaussion noise （AWGN） channel, and achieves excellent tradeoff between video delivery quality and power consumption, and yields significant power saving compared with the conventional equal decoding power allocation （EDPA） approach in wireless video transmission.展开更多
Utilizing commercial off-the-shelf(COTS) components in satellites has received much attention due to the low cost. However, commercial memories suffer severe reliability problems in radiation environments. This paper ...Utilizing commercial off-the-shelf(COTS) components in satellites has received much attention due to the low cost. However, commercial memories suffer severe reliability problems in radiation environments. This paper studies the low-density parity-check(LDPC) coding scheme for improving the reliability of multi-level-cell(MLC) NAND Flash memory in radiation environments. Firstly, based on existing physical experiment works, we introduce a new error model for heavyion irradiations; secondly, we explore the optimization of writing voltage allocation to maximize the capacity of the storage channel; thirdly, we design the degree distribution of LDPC codes that is specially suitable for the proposed model; finally, we propose a joint detection-decoding scheme based on LDPC codes, which estimates the storage channel state and executes an adaptive log-likelihood ratio(LLR) calculation to achieve better performance. Simulation results show that, compared with the conventional LDPC coding scheme, the proposed scheme may almost double the lifetime of the MLC NAND Flash memory in radiation environments.展开更多
In the future development direction of the sixth generation(6G)mobile communication,several communication models are proposed to face the growing challenges of the task.The rapid development of artificial intelligence...In the future development direction of the sixth generation(6G)mobile communication,several communication models are proposed to face the growing challenges of the task.The rapid development of artificial intelligence(AI)foundation models provides significant support for efficient and intelligent communication interactions.In this paper,we propose an innovative semantic communication paradigm called task-oriented semantic communication system with foundation models.First,we segment the image by using task prompts based on the segment anything model(SAM)and contrastive language-image pretraining(CLIP).Meanwhile,we adopt Bezier curve to enhance the mask to improve the segmentation accuracy.Second,we have differentiated semantic compression and transmission approaches for segmented content.Third,we fuse different semantic information based on the conditional diffusion model to generate high-quality images that satisfy the users'specific task requirements.Finally,the experimental results show that the proposed system compresses the semantic information effectively and improves the robustness of semantic communication.展开更多
With the development of deep learning(DL),joint source-channel coding(JSCC)solutions for end-to-end transmission have gained a lot of attention.Adaptive deep JSCC schemes support dynamically adjusting the rate accordi...With the development of deep learning(DL),joint source-channel coding(JSCC)solutions for end-to-end transmission have gained a lot of attention.Adaptive deep JSCC schemes support dynamically adjusting the rate according to different channel conditions during transmission,enhancing robustness in dynamic wireless environment.However,most of the existing adaptive JSCC schemes only consider different channel conditions,ignoring the different feature importance in the image processing and transmission.The uniform compression of different features in the image may result in the compromise of critical image details,particularly in low signal-to-noise ratio(SNR)scenarios.To address the above issues,in this paper,a dual attention mechanism is introduced and an SNR-adaptive deep JSCC mechanism with a convolutional block attention module(CBAM)is proposed,in which matrix operations are applied to features in spatial and channel dimensions respectively.The proposed solution concatenates the pooling feature with the SNR level and passes it sequentially through the channel attention network and spatial attention network to obtain the importance evaluation result.Experiments show that the proposed solution outperforms other baseline schemes in terms of peak SNR(PSNR)and structural similarity(SSIM),particularly in low SNR scenarios or when dealing with complex image content.展开更多
A robust progressive image transmission scheme over broadband wireless fading channels is developed for 4th generation wireless communication systems （4G） in this paper. The proposed scheme is based on space-time bl...A robust progressive image transmission scheme over broadband wireless fading channels is developed for 4th generation wireless communication systems （4G） in this paper. The proposed scheme is based on space-time block coded orthogonal frequency-division multiplexing （OFDM） with 4 transmit antennas and 2 receive antennas and uses a simplified minimum mean square error （MMSE） detector instead of maximum likelihood （ML） detectors. Considering DCT is simpler and more widely applied in the industry than wavelet transforms, a progressive image compression method based on DCT called mean-subtract embedded DCT （MSEDCT） is developed, with a simple mean-subtract method for the redundancy of reorganized DC blocks in addition to a structure similar to the embedded zerotree wavelet coding （EZW） method. Then after analyzing and testing bit importance of the progressive MSEDCT bitstreams, the layered unequal error protection method of joint source-channels coding based on Reed-Solomon （RS） codes is used to protect different parts of bitstreams, providing different QoS assurances and good flexibility. Simulation experiments show our proposed scheme can effectively degrade fading effects and obtain better image transmission effects with 10 -20 dB average peak-sig- nal-noise-ratio （PSNR） gains at the median Eb/No than those schemes without space-time coded OFDM or equal error protections with space-time coded OFDM.展开更多
文摘Deep learning-based semantic communication has achieved remarkable progress with CNNs and Transformers.However,CNNs exhibit constrained performance in high-resolution image transmission,while Transformers incur high computational cost due to quadratic complexity.Recently,VMamba,a novel state space model with linear complexity and exceptional long-range dependency modeling capabilities,has shown great potential in computer vision tasks.Inspired by this,we propose MNTSCC,an efficient VMamba-based nonlinear joint source-channel coding(JSCC)model for wireless image transmission.Specifically,MNTSCC comprises a VMamba-based nonlinear transform module,an MCAM entropy model,and a JSCC module.In the encoding stage,the input image is first encoded into a latent representation via the nonlinear transformation module,which is then processed by the MCAM for source distribution modeling.The JSCC module then optimizes transmission efficiency by adaptively assigning transmission rate to the latent representation according to the estimated entropy values.The proposedMCAMenhances the channel-wise autoregressive entropy model with attention mechanisms,which enables the entropy model to effectively capture both global and local information within latent features,thereby enabling more accurate entropy estimation and improved rate-distortion performance.Additionally,to further enhance the robustness of the system under varying signal-to-noise ratio(SNR)conditions,we incorporate SNR adaptive net(SAnet)into the JSCCmodule,which dynamically adjusts the encoding strategy by integrating SNRinformationwith latent features,thereby improving SNR adaptability.Experimental results across diverse resolution datasets demonstrate that the proposed method achieves superior image transmission performance compared to existing CNN-and Transformer-based semantic communication models,while maintaining competitive computational efficiency.In particular,under an Additive White Gaussian Noise(AWGN)channel with SNR=10 dB and a channel bandwidth ratio(CBR)of 1/16,MNTSCC consistently outperforms NTSCC,achieving a 1.72 dB Peak Signal-to-Noise Ratio(PSNR)gain on the Kodak24 dataset,0.79 dB on CLIC2022,and 2.54 dB on CIFAR-10,while reducing computational cost by 32.23%.The code is available at https://github.com/WanChen10/MNTSCC(accessed on 09 July 2025).
文摘Deep learning-based Joint Source-Channel Coding(JSCC)is a crucial component in semantic communication,and recent research has made significant progress in adapting to different channels.In this paper,we propose a multi-stage progressive technique called Deep learning based Progressive Joint Source-Channel Coding(DP-JSCC).This approach partitions the source into multiple stages and transmits the signals continuously.The receiver gradually enhances the quality of image reconstruction by progressively receiving the signals,offering greater flexibility compared to existing dynamic rate transmission methods.The model adopts a lightweight architectural design,where we introduce an efficient module called the Inverted Shuffle Attention Bottleneck(ISAB)and incorporate self-attention mechanisms in the encoding and decoding process to capture signal correlations and establish long-range dependencies.Additionally,we introduce the Progressive Focus Weight Allocation(PFWA)method to improve the image reconstruction capability in progressive transmission tasks.These design enhance the expressive capacity of the model.Simulation results demonstrate that DP-JSCC can flexibly adjust the transmission rate according to requirements without the need for retraining or deployment,enabling continuous optimization of signals at different rates.Furthermore,compared to stateof-the-art JSCC methods,DP-JSCC exhibits advantages in terms of computational complexity,parameter count,and reconstruction performance.
基金supported in part by the National Key R&D Program of China under Grant 2022YFB3103500in part by the National Natural Science Foundation of China under Grant 62302195.
文摘Semantic secure communication is an emerging field that combines the principles of source-channel coding with the need for secure data transmission.It is of great significance in modern communications to protect the confidentiality and privacy of sensitive information and prevent information leaks and malicious attacks.This paper presents a novel approach to semantic secure communication through the utilization of joint source-channel coding,which is based on the design of an automated joint source-channel coding algorithm and an encryption and decryption algorithm based on semantic security.The traditional and state-of-the-art joint source-channel coding algorithms are selected as two baselines for different comparison purposes.Experimental results demonstrate that our proposed algorithm outperforms the first baseline algorithm,the traditional source-channel coding,by 61.21%in efficiency under identical channel conditions(SNR=15 dB).In security,our proposed method can resist 2 more types of attacks compared to the two baselines,exhibiting nearly no increases in time consumption and error rate compared to the state-of-the-art joint source-channel coding algorithm while the secure semantic communication is supported.
基金Project supported by the Scientific Research Project of Liaoning Provincial Department of Education,China(No.JYTMS20231039)the Liaoning Provincial Educational Science Planning Project,China(No.JG22CB252)。
文摘Reversible data hiding in encrypted images(RDHEI)is essential for safeguarding sensitive information within the encrypted domain.In this study,we propose an intelligent pixel predictor based on a residual group block and a spatial attention module,showing superior pixel prediction performance compared to existing predictors.Additionally,we introduce an adaptive joint coding method that leverages bit-plane characteristics and intra-block pixel correlations to maximize embedding space,outperforming single coding approaches.The image owner employs the presented intelligent predictor to forecast the original image,followed by encryption through additive secret sharing before conveying the encrypted image to data hiders.Subsequently,data hiders encrypt secret data and embed them within the encrypted image before transmitting the image to the receiver.The receiver can extract secret data and recover the original image losslessly,with the processes of data extraction and image recovery being separable.Our innovative approach combines an intelligent predictor with additive secret sharing,achieving reversible data embedding and extraction while ensuring security and lossless recovery.Experimental results demonstrate that the predictor performs well and has a substantial embedding capacity.For the Lena image,the number of prediction errors within the range of[-5,5]is as high as 242500 and our predictor achieves an embedding capacity of 4.39 bpp.
基金supported in part by the National Key Research and Development Program of China under Grant No.2024YFE0200600the Zhejiang Provincial Natural Science Foundation of China under Grant No.LR23F010005the Huawei Cooperation Project under Grant No.TC20240829036。
文摘Along with the proliferating research interest in semantic communication(Sem Com),joint source channel coding(JSCC)has dominated the attention due to the widely assumed existence in efficiently delivering information semantics.Nevertheless,this paper challenges the conventional JSCC paradigm and advocates for adopting separate source channel coding(SSCC)to enjoy a more underlying degree of freedom for optimization.We demonstrate that SSCC,after leveraging the strengths of the Large Language Model(LLM)for source coding and Error Correction Code Transformer(ECCT)complemented for channel coding,offers superior performance over JSCC.Our proposed framework also effectively highlights the compatibility challenges between Sem Com approaches and digital communication systems,particularly concerning the resource costs associated with the transmission of high-precision floating point numbers.Through comprehensive evaluations,we establish that assisted by LLM-based compression and ECCT-enhanced error correction,SSCC remains a viable and effective solution for modern communication systems.In other words,separate source channel coding is still what we need.
基金supported by National Natural Science Foundation of China(No.92067202,No.62001049,&No.62071058)Beijing Natural Science Foundation under Grant 4222012Beijing University of Posts and Telecommunications-China Mobile Research Institute Joint Innovation Center。
文摘In order to provide ultra low-latency and high energy-efficient communication for intelligences,the sixth generation(6G)wireless communication networks need to break out of the dilemma of the depleting gain of the separated optimization paradigm.In this context,this paper provides a comprehensive tutorial that overview how joint source-channel coding(JSCC)can be employed for improving overall system performance.For the purpose,we first introduce the communication requirements and performance metrics for 6G.Then,we provide an overview of the source-channel separation theorem and why it may not hold in practical applications.In addition,we focus on two new JSCC schemes called the double low-density parity-check(LDPC)codes and the double polar codes,respectively,giving their detailed coding and decoding processes and corresponding performance simulations.In a nutshell,this paper constitutes a tutorial on the JSCC scheme tailored to the needs of future 6G communications.
基金Supported by National Natural Science Foundation of China (No.90104013) and 863 project(2001AA121061)
文摘An improved FGS (Fine Granular Scalability) coding method is proposed in this letter, which is based on human visual characteristics. This method adjusts FGS coding frame rate according to the evaluation of video sequences so as to improve the coding efficiency and subject perceived quality of reconstructed images. Finally, a fine granular joint source channel coding is proposed based on the source coding method, which not only utilizes the network resources efficiently, but guarantees the reliable transmission of video information.
基金Supported by the National Natural Science Foundation of China （No. 60572081 ）
文摘Realtime speech communications require high efficient compression algorithms to encode speech signals. As the compressed speech parameters are highly sensitive to transmission errors, robust source and channel decoding and demodulation schemes are both important and of practical use. In this paper, an it- erative joint souree-channel decoding and demodulation algorithm is proposed for mixed excited linear pre- diction （MELP） vocoder by both exploiting the residual redundancy and passing soft information through- out the receiver while introducing systematic global iteration process to further enhance the performance. Being fully compatible with existing transmitter structure, the proposed algorithm does not introduce addi- tional bandwidth expansion and transmission delay. Simulations show substantial error correcting perfor- mance and synthesized speech quality improvement over conventional separate designed systems in delay and bandwidth constraint channels by using the joint source-channel decoding and demodulation （JSCCM） algorithm.
文摘Robust video streaming through high error prone wireless channel has attracted much attention. In this paper the authors introduce an effective algorithm by joining the Unequal Error Protection ability of the channel multiplexing protocol H.223 Annex D, and the new H.263++ Annex V Data Partition together. Based on the optimal trade off of these two technologies, the Joint Source and Channel Coding algorithm can result in stronger error resilience. The simulation results have shown its superiority against separate coding mode and some Unequal Error Protection mode under recommended wireless channel error patterns.
基金Supported by the National Natural Science Foundation of China(61462048)
文摘The existing depth video coding algorithms are generally based on in-loop depth filters, whose performance are unstable and easily affected by the outliers. In this paper, we design a joint weighted sparse representation-based median filter as the in-loop filter in depth video codec. It constructs depth candidate set which contains relevant neighboring depth pixel based on depth and intensity similarity weighted sparse coding, then the median operation is performed on this set to select a neighboring depth pixel as the result of the filtering. The experimental results indicate that the depth bitrate is reduced by about 9% compared with anchor method. It is confirmed that the proposed method is more effective in reducing the required depth bitrates for a given synthesis quality level.
基金supported in part by the National Key Research and Development Program of China under Grant 2024YFE0200600in part by the National Natural Science Foundation of China under Grant 62071425+3 种基金in part by the Zhejiang Key Research and Development Plan under Grant 2022C01093in part by the Zhejiang Provincial Natural Science Foundation of China under Grant LR23F010005in part by the National Key Laboratory of Wireless Communications Foundation under Grant 2023KP01601in part by the Big Data and Intelligent Computing Key Lab of CQUPT under Grant BDIC-2023-B-001.
文摘Semantic communication(SemCom)aims to achieve high-fidelity information delivery under low communication consumption by only guaranteeing semantic accuracy.Nevertheless,semantic communication still suffers from unexpected channel volatility and thus developing a re-transmission mechanism(e.g.,hybrid automatic repeat request[HARQ])becomes indispensable.In that regard,instead of discarding previously transmitted information,the incremental knowledge-based HARQ(IK-HARQ)is deemed as a more effective mechanism that could sufficiently utilize the information semantics.However,considering the possible existence of semantic ambiguity in image transmission,a simple bit-level cyclic redundancy check(CRC)might compromise the performance of IK-HARQ.Therefore,there emerges a strong incentive to revolutionize the CRC mechanism,thus more effectively reaping the benefits of both SemCom and HARQ.In this paper,built on top of swin transformer-based joint source-channel coding(JSCC)and IK-HARQ,we propose a semantic image transmission framework SC-TDA-HARQ.In particular,different from the conventional CRC,we introduce a topological data analysis(TDA)-based error detection method,which capably digs out the inner topological and geometric information of images,to capture semantic information and determine the necessity for re-transmission.Extensive numerical results validate the effectiveness and efficiency of the proposed SC-TDA-HARQ framework,especially under the limited bandwidth condition,and manifest the superiority of TDA-based error detection method in image transmission.
基金Sponsored by the Fundamental Research Funds for the Central Universities (Grant No. HIT. NSRIF. 201149)the National Natural Science Foundation of China (Grant No. 61071104)
文摘To improve the performance of MIMO-OFDM video transmission systems on the limitation of wireless bandwidth and transmitting power,we propose an adaptive joint resource allocation algorithm with unequal error protection(UEP) based on joint source-channel coding(JSCC) according to H.264 video compression standard and RCPT channel coding.According to different thresholds of the average SNR of subchannels,the algorithm dynamically allocates the source coding parameters of original video data and the channel coding parameters of RCPT,which realizes UEP for the compressed video data of different importance.Through the bit and power allocation based on MQAM modulation and the subspace allocation based on beamforming technology for different subcarriers,an adaptive joint resource allocation making full use of space-frequency domain resources have been realized.The simulation results indicate that the algorithm improves the adaptability of video transmission systems in different wireless environments and the quality of video retrieval.
基金National High-Tech Research and Development Plan of China(No.2003AA1Z2130)Science and Technology Project of Zhejiang Province,China(No.2006C11200)
文摘An adaptive joint source channel bit allocation method for video communications over error-prone channel is proposed.To protect the bit-streams from the channel bit errors,the rate compatible punctured convolution(RCPC)code is used to produce coding rates varying from 4/5 to 1/2 using the same encoder and the Viterbi decoder.An expected end-to-end distortion model was presented to estimate the distortion introduced in compressed source coding due to quantization and channel bit errors jointly.Based on the proposed end-to-end distortion model,an adaptive joint source-channel bit allocation method was proposed under time-varying error-prone channel conditions.Simulated results show that the proposed methods could utilize the available channel capacity more efficiently and achieve better video quality than the other fixed coding-based bit allocation methods when transmitting over error-prone channels.
文摘For two-way video communications over wireless channels using the automatic repeat request (ARQ) retransmission scheme, TMN8 rate control scheme is not effective in minimizing the number of frames skipped and cannot guarantee video quality during the retransmissions of error packets. This paper presents a joint source channel bit allocation scheme that allocates target bits according to encoder buffer fullness and estimation of channel condition by retransmission information. The results obtained from implementing our scheme in H.263+coder over wireless channel model show that our proposed scheme encodes the video sequences with lower and steadier buffer delay, fewer frames skipped and higher average PSNR compared to TMN8.
基金The National Natural Science Foundation of China (No. 60202006)
文摘A novel joint source channel distortion model was proposed, which can essentially estimate the average distortion in progressive image transmission. To improve the precision of the model, the redundancy generated by a forbidden symbol in the arithmetic codes is used to distinguish the quantization distortion and the channel distortion, all the coefficients from the first error one to the end of the sequence are set to be a value within the variance range of the coefficients instead of zero, then the error propagation coming from the entropy coding can be essentially estimated, which is disregarded in the most conventional joint source channel coding (JSCC) systems. The precision of the model in terms of average peak-signal-to-noise has been improved about 0.5 dB compared to classical works. An efficient unequal error protection system based on the model is developed, and can be used in the wireless communication systems.
基金supported by the Scientific Research Innovation Project of the Shanghai Municipal Education Commission (Grant No.08YZ18)the Key Project of Natural Science Foundation of China (Grant No.60832003)+2 种基金the National Natural Science Foundation of China (Grant Nos.60972137,60672052)the Innovation Foundation Project of Shanghai Universitythe Special Research Foundation of Shanghai Excellent Youth University Teacher Training
文摘We present an unequal decoding power allocation （UDPA） approach for minimization of the receiver power consumption subject to a given quality of service （QoS）, by exploiting data partitioning and turbo decoding. We assign unequal decoding power of forward error correction （FEC） to data partitions with different priority by jointly considering the source coding, channel coding and receiver power consumption. The proposed scheme is applied to H.264 video over additive white Gaussion noise （AWGN） channel, and achieves excellent tradeoff between video delivery quality and power consumption, and yields significant power saving compared with the conventional equal decoding power allocation （EDPA） approach in wireless video transmission.
基金supported by the National Basic Research Project of China(973)(2013CB329006)National Natural Science Foundation of China(NSFC,91538203)the new strategic industries development projects of Shenzhen City(JCYJ20150403155812833)
文摘Utilizing commercial off-the-shelf(COTS) components in satellites has received much attention due to the low cost. However, commercial memories suffer severe reliability problems in radiation environments. This paper studies the low-density parity-check(LDPC) coding scheme for improving the reliability of multi-level-cell(MLC) NAND Flash memory in radiation environments. Firstly, based on existing physical experiment works, we introduce a new error model for heavyion irradiations; secondly, we explore the optimization of writing voltage allocation to maximize the capacity of the storage channel; thirdly, we design the degree distribution of LDPC codes that is specially suitable for the proposed model; finally, we propose a joint detection-decoding scheme based on LDPC codes, which estimates the storage channel state and executes an adaptive log-likelihood ratio(LLR) calculation to achieve better performance. Simulation results show that, compared with the conventional LDPC coding scheme, the proposed scheme may almost double the lifetime of the MLC NAND Flash memory in radiation environments.
基金supported in part by the National Natural Science Foundation of China under Grant(62001246,62231017,62201277,62071255)the Natural Science Foundation of Jiangsu Province under Grant BK20220390+3 种基金Key R and D Program of Jiangsu Province Key project and topics under Grant(BE2021095,BE2023035)the Natural Science Research Startup Foundation of Recruiting Talents of Nanjing University of Posts and Telecommunications(Grant No.NY221011)National Science Foundation of Xiamen,China(No.3502Z202372013)Open Project of the Key Laboratory of Underwater Acoustic Communication and Marine Information Technology(Xiamen University)of the Ministry of Education,China(No.UAC202304)。
文摘In the future development direction of the sixth generation(6G)mobile communication,several communication models are proposed to face the growing challenges of the task.The rapid development of artificial intelligence(AI)foundation models provides significant support for efficient and intelligent communication interactions.In this paper,we propose an innovative semantic communication paradigm called task-oriented semantic communication system with foundation models.First,we segment the image by using task prompts based on the segment anything model(SAM)and contrastive language-image pretraining(CLIP).Meanwhile,we adopt Bezier curve to enhance the mask to improve the segmentation accuracy.Second,we have differentiated semantic compression and transmission approaches for segmented content.Third,we fuse different semantic information based on the conditional diffusion model to generate high-quality images that satisfy the users'specific task requirements.Finally,the experimental results show that the proposed system compresses the semantic information effectively and improves the robustness of semantic communication.
基金This work was supported in part by the National Natural Science Foundation of China(62293481)in part by the Young Elite Scientists Sponsorship Program by CAST(2023QNRC001)+1 种基金in part by the National Natural Science Foundation for Young Scientists of China(62001050)in part by the Fundamental Research Funds for the Central Universities(2023RC95).
文摘With the development of deep learning(DL),joint source-channel coding(JSCC)solutions for end-to-end transmission have gained a lot of attention.Adaptive deep JSCC schemes support dynamically adjusting the rate according to different channel conditions during transmission,enhancing robustness in dynamic wireless environment.However,most of the existing adaptive JSCC schemes only consider different channel conditions,ignoring the different feature importance in the image processing and transmission.The uniform compression of different features in the image may result in the compromise of critical image details,particularly in low signal-to-noise ratio(SNR)scenarios.To address the above issues,in this paper,a dual attention mechanism is introduced and an SNR-adaptive deep JSCC mechanism with a convolutional block attention module(CBAM)is proposed,in which matrix operations are applied to features in spatial and channel dimensions respectively.The proposed solution concatenates the pooling feature with the SNR level and passes it sequentially through the channel attention network and spatial attention network to obtain the importance evaluation result.Experiments show that the proposed solution outperforms other baseline schemes in terms of peak SNR(PSNR)and structural similarity(SSIM),particularly in low SNR scenarios or when dealing with complex image content.
文摘A robust progressive image transmission scheme over broadband wireless fading channels is developed for 4th generation wireless communication systems （4G） in this paper. The proposed scheme is based on space-time block coded orthogonal frequency-division multiplexing （OFDM） with 4 transmit antennas and 2 receive antennas and uses a simplified minimum mean square error （MMSE） detector instead of maximum likelihood （ML） detectors. Considering DCT is simpler and more widely applied in the industry than wavelet transforms, a progressive image compression method based on DCT called mean-subtract embedded DCT （MSEDCT） is developed, with a simple mean-subtract method for the redundancy of reorganized DC blocks in addition to a structure similar to the embedded zerotree wavelet coding （EZW） method. Then after analyzing and testing bit importance of the progressive MSEDCT bitstreams, the layered unequal error protection method of joint source-channels coding based on Reed-Solomon （RS） codes is used to protect different parts of bitstreams, providing different QoS assurances and good flexibility. Simulation experiments show our proposed scheme can effectively degrade fading effects and obtain better image transmission effects with 10 -20 dB average peak-sig- nal-noise-ratio （PSNR） gains at the median Eb/No than those schemes without space-time coded OFDM or equal error protections with space-time coded OFDM.
