Fast factorization architecture in soft-decision Reed-Solomon decoding
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
High-speed interpolation architecture for soft-decision decoding of Reed-Solomon codes
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Low-latency factorization architecture for algebraic soft-decision decoding of Reed-Solomon codes
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Algebraic soft-decision decoder architectures for long Reed-Solomon codes
IEEE Transactions on Circuits and Systems II: Express Briefs
Reduced complexity interpolation architecture for soft-decision reed-solomon decoding
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Backward interpolation architecture for algebraic soft-decision reed-solomon decoding
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Improved decoding of Reed-Solomon and algebraic-geometry codes
IEEE Transactions on Information Theory
Algebraic soft-decision decoding of Reed-Solomon codes
IEEE Transactions on Information Theory
Algebraic Soft-Decision Decoding of Reed–Solomon Codes Using Bit-Level Soft Information
IEEE Transactions on Information Theory
Algebraic soft-decision decoder architectures for long Reed-Solomon codes
IEEE Transactions on Circuits and Systems II: Express Briefs
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
A minimal search soft decision list decoding algorithm for Reed-Solomon codes
International Journal of Information and Communication Technology
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Reed---Solomon (RS) codes are widely used as error-correcting codes in digital communication and storage systems. Algebraic soft-decision decoding (ASD) of RS codes can achieve substantial coding gain with polynomial complexity. Among practical ASD algorithms, the low-complexity chase (LCC) algorithm that tests 2 驴 vectors can achieve similar or higher coding gain with lower complexity. For applications such as magnetic recording, the performance of the LCC decoding is degraded by the inter-symbol interference from the channel. Improving the performance of the LCC decoding requires larger 驴, which leads to higher complexity. In this paper, a modified LCC (MLCC) decoding is proposed by adding erasures to the test vectors. With the same 驴, the proposed algorithm can achieve much better performance than the original LCC decoding. One major step of the LCC and MLCC decoding is the interpolation. To reduce the complexity of the interpolation, this paper also proposed a prioritized interpolation scheme to test a small proportion of the vectors at a time, starting with the ones with higher reliabilities. For a (458, 410) RS code, by testing 1/8 of the vectors at a time, the area requirement of the MLCC decoder with 驴驴=驴8 can be reduced to 57%, and the average decoding latency is reduced to 73%.