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The extrinsic information is iteratively and concurrently exchanged between multiple component decoders via an on-chip communication network presented in [15].
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As described in Section 3.2.2, component-decoder parallelism takes advantage of the shuffled decoding technique that executes all component decoders in parallel and exchanges extrinsic information as soon as created.
Figure 7 Turbo MAP decoder based on two component decoders.
Such method, commonly referred to as iterative or turbo processing, was initially proposed for turbo decoding [2] where two component decoders exchange soft information to improve the system performance.
The basic idea of the shuffled decoding technique is to execute all component decoders in parallel and to exchange extrinsic information as soon as created.
Knowing the outputs of component decoders, we can specify the equations that govern turbo-decoding.
Recently, a new parallelism technique named shuffled decoding was introduced to process in parallel the component decoders [10, 11].
They also revolutionized the coding theory by establishing a new soft-iterative paradigm, where long powerful codes are constructed from short simple codes and decoded through iterative message exchange and successive refinement between component decoders.
It is known that in turbo decoding, the optimal algorithm for the soft-input/soft-output (SISO) component decoders is the maximum a posteriori (MAP) probability algorithm[3].
The turbo decoding is performed by two soft-input soft-output (SISO) component decoders that exchange soft information about their data sub-stream.
By definition, this latter is the iteration number required by a sequential execution of component decoders (using BCJR-SISO decoders) over the iteration number required with shuffled decoding (i.e., BCJR-SISO decoders working in parallel).
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