标题： 基于主动位置的时延约束业务在衰落信道上的调度 显示英文标题

标题： Proactive Location-Based Scheduling of Delay-Constrained Traffic Over Fading Channels

摘要： 在本文中，引入了基于用户位置的主动资源分配方法，用于衰落信道上的点对点通信，其中源必须在单个时隙的时间限制内传输数据包当用户请求时。 我们引入了一个预测模型，其中源预测请求到达时间提前$T_p$个时隙，其中$T_p$表示预测窗口（PW）大小。 源在PW的每个时隙中主动分配能量以传输一些比特，目的是减少非预测情况下的传输能量。 请求是根据用户位置进行预测的，利用每个位置上用户请求的先验统计信息。 我们还假设预测并不完美。 我们提出了主动调度策略，在源处关于信道状态信息的两种不同假设下，以最小化传输所需的数据包预期能量消耗。 在第一种场景中，离线调度，我们假设在PW开始时源已知信道状态。 在第二种场景中，在线调度，假设源具有因果性的信道状态知识。 数值结果展示了使用主动调度策略相比经典（反应式）网络所获得的优势。 仿真结果还表明，即使预测不完美，增加PW大小也会显著减少消耗的传输能量。 显示英文摘要

摘要： In this paper, proactive resource allocation based on user location for point-to-point communication over fading channels is introduced, whereby the source must transmit a packet when the user requests it within a deadline of a single time slot. We introduce a prediction model in which the source predicts the request arrival $T_p$ slots ahead, where $T_p$ denotes the prediction window (PW) size. The source allocates energy to transmit some bits proactively for each time slot of the PW with the objective of reducing the transmission energy over the non-predictive case. The requests are predicted based on the user location utilizing the prior statistics about the user requests at each location. We also assume that the prediction is not perfect. We propose proactive scheduling policies to minimize the expected energy consumption required to transmit the requested packets under two different assumptions on the channel state information at the source. In the first scenario, offline scheduling, we assume the channel states are known a-priori at the source at the beginning of the PW. In the second scenario, online scheduling, it is assumed that the source has causal knowledge of the channel state. Numerical results are presented showing the gains achieved by using proactive scheduling policies compared with classical (reactive) networks. Simulation results also show that increasing the PW size leads to a significant reduction in the consumed transmission energy even with imperfect prediction.