In this paper, we propose a new dynamic load balancing scheme according to load threshold adjustment and incentives mechanism. The proposed scheme adjusts the load threshold of a node by comparing it with a mean threshold of adjacent nodes, thereby increasing the threshold evenly. We also assign the incentives and penalties to each node through a comparison of the mean threshold of all the nodes in order to increase autonomous load balancing participation.

In this letter, we propose a two-bit representation method for turbo decoder extrinsic information based on bit error count minimization and parameter reset. We show that the performance of the proposed system approaches that of the full precision decoder within 0.17 dB and 0.48 dB at 1 % packet error rate for packet lengths of 500 and 10,000 information bits. The idea of parameter reset we introduce can be used not only in turbo decoder but also in many other iterative algorithms.