Low Complexity State Metric Memory Reduction for Turbo Decoding With Stochastic Quantization

The size of the state metrics cache (SMC) has a predominant impact on the overall hardware consumption of the Turbo decoder. This brief presents a low complexity SMC reduction algorithm based on the proposed stochastic quantization (SQ) technique, which reduces the size of the SMC by randomly quantizing the state metrics to different small bit-width numbers. The selection of the random source and the updating method of the extrinsic information are further explored to minimize the performance loss caused by bit-width reduction. The simulation and synthesis results show that the proposed algorithm can achieve the best bit error rate (BER) performance with the lowest hardware consumption among the compared SMC reduction algorithms.