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Distributed Opportunistic Scheduling for Energy Harvesting Based Wireless Networks: A Two-Stage Probing Approach

机译:基于能量收集的无线网络的分布式机会调度:两阶段探测方法

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This paper considers a heterogeneous ad hoc network with multiple transmitter-receiver pairs, in which all transmitters are capable of harvesting renewable energy from the environment and compete for one shared channel by random access. In particular, we focus on two different scenarios: the constant energy harvesting (EH) rate model where the EH rate remains constant within the time of interest and the i.i.d. EH rate model where the EH rates are independent and identically distributed across different contention slots. To quantify the roles of both the energy state information (ESI) and the channel state information (CSI), a distributed opportunistic scheduling (DOS) framework with two-stage probing and save-then-transmit energy utilization is proposed. Then, the optimal throughput and the optimal scheduling strategy are obtained via one-dimension search, i.e., an iterative algorithm consisting of the following two steps in each iteration: First, assuming that the stored energy level at each transmitter is stationary with a given distribution, the expected throughput maximization problem is formulated as an optimal stopping problem, whose solution is proven to exist and then derived for both models; second, for a fixed stopping rule, the energy level at each transmitter is shown to be stationary and an efficient iterative algorithm is proposed to compute its steady-state distribution. Finally, we validate our analysis by numerical results and quantify the throughput gain compared with the best-effort delivery scheme.
机译:本文考虑了具有多个收发器对的异构ad hoc网络,其中所有的发送器都能够从环境中获取可再生能源,并通过随机访问竞争一个共享信道。特别是,我们专注于两种不同的情况:恒定能量收集(EH)速率模型,其中EH速率在感兴趣的时间内保持恒定,而i.d. EH速率模型,其中EH速率是独立的,并且在不同的竞争时隙之间相同地分布。为了量化能量状态信息(ESI)和信道状态信息(CSI)的作用,提出了一种具有两阶段探测并保存然后传输的能量利用的分布式机会调度(DOS)框架。然后,通过一维搜索获得最优吞吐量和最优调度策略,即在每次迭代中由以下两个步骤组成的迭代算法:首先,假设每个发射机的存储能量水平在给定分布下是平稳的,将预期吞吐量最大化问题公式化为最优停止问题,证明了该问题的解存在,然后针对两个模型推导得出;其次,对于固定的停止规则,每个发射器的能量水平显示为固定,并提出了一种有效的迭代算法来计算其稳态分布。最后,我们通过数值结果验证了我们的分析结果,并与尽力而为的交付方案相比,量化了吞吐量的增长。

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