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 iterative detection/decoding algorithm of correlated sources for the LDPC-based relay systems is presented. The signal from the source-destination(S-D) link is formulated as a highly correlated counterpart from the...An iterative detection/decoding algorithm of correlated sources for the LDPC-based relay systems is presented. The signal from the source-destination(S-D) link is formulated as a highly correlated counterpart from the relay-destination(R-D) link. A special XOR vector is defined using the correlated hard decision information blocks from two decoders and the extrinsic information exchanged between the two decoders is derived by the log-likelihood ratio(LLR) associated with the XOR vector. Such the decoding scheme is different from the traditional turbo-like detection/decoding algorithm, where the extrinsic information is computed by the side information and the soft decoder outputs. Simulations show that the presented algorithm has a slightly better performance than the traditional turbo-like algorithm(Taking the(255,175) EG-LDPC code as an example, it achieves about 0.1 dB performance gains aroundBLER=10^(-4)). Furthermore, the presented algorithm requires fewer computing operations per iteration and has faster convergence rate. For example, the average iteration of the presented algorithm is 33 at SNR=1.8 dB, which is about twice faster than that of the turbo-like algorithm, when decoding the(961,721) QC-LDPC code. Therefore, the presented decoding algorithm of correlated sources provides an alternative decoding solution for the LDPC-based relay systems.展开更多
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 NSF of China (No.61362010,61661005)NSF of Guangxi (No.2015GXNSFAA139290,2014GXNSFBA118276,2012GXNSFAA053217)
文摘An iterative detection/decoding algorithm of correlated sources for the LDPC-based relay systems is presented. The signal from the source-destination(S-D) link is formulated as a highly correlated counterpart from the relay-destination(R-D) link. A special XOR vector is defined using the correlated hard decision information blocks from two decoders and the extrinsic information exchanged between the two decoders is derived by the log-likelihood ratio(LLR) associated with the XOR vector. Such the decoding scheme is different from the traditional turbo-like detection/decoding algorithm, where the extrinsic information is computed by the side information and the soft decoder outputs. Simulations show that the presented algorithm has a slightly better performance than the traditional turbo-like algorithm(Taking the(255,175) EG-LDPC code as an example, it achieves about 0.1 dB performance gains aroundBLER=10^(-4)). Furthermore, the presented algorithm requires fewer computing operations per iteration and has faster convergence rate. For example, the average iteration of the presented algorithm is 33 at SNR=1.8 dB, which is about twice faster than that of the turbo-like algorithm, when decoding the(961,721) QC-LDPC code. Therefore, the presented decoding algorithm of correlated sources provides an alternative decoding solution for the LDPC-based relay systems.
