| Summary: | 碩士 === 國立交通大學 === 電機學院IC設計產業專班 === 97 === Shuffled belief propagation (BP) algorithm for the decoding of low-density parity-check (LDPC) codes achieves a remarkable error performance and fast convergence. Nevertheless, it seems to be too complex for hardware implementation. The shuffled BP algorithm can be simplified by using the min-sum approximation, namely the min-sum shuffled BP algorithm; however, the min-sum shuffled BP algorithm suffers from remarkable performance degradation. In this thesis, to solve this problem, we explore some compensation techniques for the min-sum shuffled BP algorithm, including 1D-, 2D-normalization/-offset static schemes and the dynamic scaling approach. Simulations show that the compensated min-sum shuffled BP algorithm achieves the performance very close to that of the original shuffled BP algorithm in IEEE 802.11n system.
|
|---|
