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Advanced Hardware Design for Error Correcting Codes by Cyrille Chavet, Philippe Coussy

By Cyrille Chavet, Philippe Coussy

This publication offers thorough insurance of errors correcting options. It comprises crucial easy techniques and the newest advances on key subject matters in layout, implementation, and optimization of hardware/software structures for mistakes correction. The book’s chapters are written by means of the world over well-known specialists during this box. issues comprise evolution of mistakes correction ideas, business person wishes, architectures, and layout methods for the main complicated errors correcting codes (Polar Codes, Non-Binary LDPC, Product Codes, etc). This ebook presents entry to fresh effects, and is appropriate for graduate scholars and researchers of arithmetic, laptop technology, and engineering.

• Examines tips to optimize the structure of layout for mistakes correcting codes;
• offers errors correction codes from thought to optimized structure for the present and the subsequent iteration standards;
• offers insurance of commercial consumer wishes complex errors correcting techniques.

Advanced layout for blunders Correcting Codes contains a foreword by way of Claude Berrou.

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For example, the throughput of 10 Gbit/s can already be fulfilled by the presented decoder running at less than 20 MHz. 6 V can be applied. This increases the energy efficiency by at least a factor of three and allows for a better energy efficiency than any other state-of-the-art decoder. 2 Very High Throughput Decoder Architectures for Soft-Decoding 29 Conclusion In this chapter, we presented soft decision Reed–Solomon, turbo, and LDPC decoder implementations with high throughput. The introduced soft decision decoder architecture for Reed–Solomon codes is based on information set decoding.

Before the decoding process starts, instructions are loaded into the instruction memory. Channel LLR values are loaded into the channel RAM via the channel loader. The controller fetches the first instruction and the decoding process starts. α values are read from α -RAM and channel RAM and written to α -RAM. Similarly, β values are written to and read from β -RAM and the estimated codeword is written to the codeword RAM. Using separate memories for internal α values and the channel LLR values is required to enable loading-while-decoding, which is required to prevent the decoder from stalling and to maintain throughput.

Search for the L least reliable bits in the previous half-iteration output vector R′it such that λi represents the ith minimum, 1 < i < L. 2. Compute the syndrome S(t0 ) of R′it , 3. Compute the parity of R′it , 4. Generate p test patterns τi obtained by inverting some of the L least reliable bits (p ≤ 2L ). 5. For each test pattern (1 ≤ i ≤ p − 1) • Compute the syndrome S(τi ), • Correct the potential error by inverting the bit position S(τi ), • Recompute the parity considering the detection of an error and the parity of R′it , • Compute the square Euclidean distance (metric) Mi between R′it and the considered test pattern τi .

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