인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
피인용 0
초록·키워드
LDPC codes improve error correction performance in soft-decision decoding by using the reliability of the received signal, offering greater accuracy than hard-decision decoding. The High Reliability Min-Max Algorithm leverages this advantage by using LLR to reduce computational complexity while improving decoding accuracy. The (837, 726) Min-Max code maintains performance similar to LDPC while being more efficient, reducing hardware resource usage and power consumption. Compared to the (4191, 3602) binary LDPC code, it offers better transmission efficiency. This paper presents the simulation results for a (512, 256) code, and the hardware implementation, using pipeline and parallel structures, highlights the high error correction capability of the proposed Min-Max code. This structure combines the error correction strengths of QC-LDPC with the simplicity of binary LDPC's hardware implementation. The proposed algorithm demonstrates similar error correction performance to LDPC codes but achieves lower complexity and higher transmission efficiency.
Future research will focus on comparing the performance through ASIC implementation to further assess its effectiveness in practical systems. This comparison will offer insights into how the proposed Min-Max code can be implemented for real-world applications requiring efficient and reliable error correction performance.
Future research will focus on comparing the performance through ASIC implementation to further assess its effectiveness in practical systems. This comparison will offer insights into how the proposed Min-Max code can be implemented for real-world applications requiring efficient and reliable error correction performance.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
최근 본 자료 전체보기
UCI(KEPA) : I410-151-25-02-091248297
