We consider the on-time transmissions of a sequence of packets over a fading channel.Different from traditional in-time communications, we investigate how many packets can be received $\delta$-on-time, meaning that the packet is received with a deviation no larger than $\delta$ slots. In this framework, we first derive the on-time reception rate of the random transmissions over the fading channel when no controlling is used. To improve the on-time reception rate, we further propose to schedule the transmissions by delaying, dropping, or repeating the packets. Specifically, we model the scheduling over the fading channel as a Markov decision process (MDP) and then obtain the optimal scheduling policy using an efficient iterative algorithm. For a given sequence of packet transmissions, we analyze the on-time reception rate for the random transmissions and the optimal scheduling. Our analytical and simulation results show that the on-time reception rate of random transmissions decreases (to zero) with the sequence length.By using the optimal packet scheduling, the on-time reception rate converges to a much larger constant. Moreover, we show that the on-time reception rate increases if the target reception interval and/or the deviation tolerance $\delta$ is increased, or the randomness of the fading channel is reduced.
翻译:我们考虑在淡化的频道上实时传送一系列包件。 从传统的实时通讯中的不同角度, 我们调查有多少包件能够实时收到 $\delta$, 也就是说, 接收包的偏差不大于$\delta$ 空格。 在此框架内, 我们首先在不使用控制的情况下从淡化的频道上实时接收随机传输的接收率。 为了提高实时接收率, 我们进一步提议通过延迟、 下降或重复包件来安排传输时间。 具体地说, 我们用一个高效的迭接算法来模拟在淡化的频道上的列表, 然后获得最佳的列表政策 。 对于一个特定的包传输序列, 我们分析随机传输的实时接收率和最佳时间安排。 我们的分析和模拟结果表明, 随机传输的实时接收率会减少( 到零 ), 并且使用最佳的包件列表, 即时接收率会集中到一个大得多的固定点 。 此外, 我们显示, 节差的接收率是 或 快速的接收率会降低 美元 。