By Aliazam Abbasfar
This publication introduces rapid errors correcting thought in an easy language, together with a basic conception and the algorithms for interpreting turbo-like code. It offers a unified framework for the layout and research of rapid codes and LDPC codes and their deciphering algorithms.
A significant concentration is on excessive velocity rapid deciphering, which pursuits functions with facts premiums of a number of hundred million bits in keeping with moment (Mbps).
Read Online or Download Turbo-like Codes: Design for High Speed Decoding PDF
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Additional resources for Turbo-like Codes: Design for High Speed Decoding
Sample text
The simulated channel is an AWGN channel. Two interleavers with block length of 1,024 (M = 32, N = 32) and 4,096 (M = 128, N = 32) have been designed with the proposed algorithm. The BER performance of the decoders has been simulated and compared with that of the serial decoder with S-random interleaver. The maximum number of iterations for each case is 10. The performance comparison for the 1,024 case is illustrated in Figure 37. The proposed two-dimensional S-random interleaver is called S2 -random.
Figure 21 sketches the message passing between the constituent codes for a simple PCCC and SCCC. The decoding starts from one constituent code and proceeds to other constituent codes. This process is considered as one iteration. It takes several iterations to obtain u c1 SISO I c2 SISO c1 u c2 SISO I SISO Fig. 21 Message passing between the constituent codes of turbo codes 22 3 High-speed Turbo Decoders Fig. 22 The iterative decoding structure r1 a0 aN SISO b0 bN x y Interleaver yI xI a0 aN SISO b0 bN r2 very good performance for bit decisions.
The factors can be further simplified to: Speed gain = M × I0 /I Efficiency = I0 /I This is a very interesting result. The speed gain and the efficiency are proportional to the ratio between number of iterations needed for serial case and parallel case. If the number of iterations required for the parallel case is the same as the serial case, we enjoy a speed gain of M without degrading the efficiency, which is ideal parallelization. Therefore we should look at the number of iterations required for a certain performance to further quantify the characteristic factors.