This paper presents a description and performance evaluation of a new bit-level, lossless, adaptive, and asymmetric data compression scheme that is based on the adaptive character wordlength （ACW（n）） algorithm. Th...This paper presents a description and performance evaluation of a new bit-level, lossless, adaptive, and asymmetric data compression scheme that is based on the adaptive character wordlength （ACW（n）） algorithm. The proposed scheme enhances the compression ratio of the ACW（n） algorithm by dividing the binary sequence into a number of subsequences （s）, each of them satisfying the condition that the number of decimal values （d） of the n-bit length characters is equal to or less than 256. Therefore, the new scheme is referred to as ACW（n, s）, where n is the adaptive character wordlength and s is the number of subsequences. The new scheme was used to compress a number of text files from standard corpora. The obtained results demonstrate that the ACW（n, s） scheme achieves higher compression ratio than many widely used compression algorithms and it achieves a competitive performance compared to state-of-the-art compression tools.展开更多
Huffman[Huffman(1952)]encoding is one of the most known compression algorithms.In its basic use,only one encoding is given for the same letter in text to compress.In this paper,a text compression algorithm that is bas...Huffman[Huffman(1952)]encoding is one of the most known compression algorithms.In its basic use,only one encoding is given for the same letter in text to compress.In this paper,a text compression algorithm that is based on Huffman encoding is proposed.Huffman encoding is used to give different encodings for the same letter depending on the prefix preceding it in the word.A deterministic finite automaton(DFA)that recognizes the words of the text is constructed.This DFA records the frequencies for letters that label the transitions.Every state will correspond to one of the prefixes of the words of the text.For every state,a different Huffman encoding is defined for the letters that label the transitions leaving that state.These Huffman encodings are then used to encode the letters of the words in the text.This algorithm was implemented and experimental study showed significant reduction in compression ratio over the basic Huffman encoding.However,more time is needed to construct these codes.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
文摘This paper presents a description and performance evaluation of a new bit-level, lossless, adaptive, and asymmetric data compression scheme that is based on the adaptive character wordlength （ACW（n）） algorithm. The proposed scheme enhances the compression ratio of the ACW（n） algorithm by dividing the binary sequence into a number of subsequences （s）, each of them satisfying the condition that the number of decimal values （d） of the n-bit length characters is equal to or less than 256. Therefore, the new scheme is referred to as ACW（n, s）, where n is the adaptive character wordlength and s is the number of subsequences. The new scheme was used to compress a number of text files from standard corpora. The obtained results demonstrate that the ACW（n, s） scheme achieves higher compression ratio than many widely used compression algorithms and it achieves a competitive performance compared to state-of-the-art compression tools.
文摘Huffman[Huffman(1952)]encoding is one of the most known compression algorithms.In its basic use,only one encoding is given for the same letter in text to compress.In this paper,a text compression algorithm that is based on Huffman encoding is proposed.Huffman encoding is used to give different encodings for the same letter depending on the prefix preceding it in the word.A deterministic finite automaton(DFA)that recognizes the words of the text is constructed.This DFA records the frequencies for letters that label the transitions.Every state will correspond to one of the prefixes of the words of the text.For every state,a different Huffman encoding is defined for the letters that label the transitions leaving that state.These Huffman encodings are then used to encode the letters of the words in the text.This algorithm was implemented and experimental study showed significant reduction in compression ratio over the basic Huffman encoding.However,more time is needed to construct these codes.
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.
