A study of the decision of control parameters for adaptive automatic-repeat request strategy

In many practical transmission systems, transmission error rate of the channel is time-varying. In previous works for controlling the time-varying channel, the state of the channel is estimated and is uniquely determined. Then, the optimum value is chosen as a control parameter for the determined state. However, there is a discrepancy between the actual channel state and estimated state. The optimum control parameter determined for the estimated state does not necessarily provide the best Performance presented by some object function in error control such as throughput efficiency. In this study, the expected value of throughput is calculated by using the posterior probability for each state and an algorithm in which the control parameter is selected to maximize the expected performance is proposed. From the viewpoint of the statistical decision theory, it is shown that this selection is the optimum in maximizing the throughput under the Bayes criterion. Using simulation, the proposed method is evaluated and its effectiveness is shown.