In this paper, we consider a multi-hop cooperative network founded on two energy-harvesting (EH) decode-and-forward (DF) relays which are provided with harvest-store-use (HSU) architecture to harvest energy from the ambience using the energy buffers. For the sake of boosting the data delivery in this network, maximal ratio combining (MRC) at destination to combine the signals received from source and relays, as well as an opportunistic routing (OR) algorithm which considers channel status information, location and energy buffer status of relays is proposed. With applying discrete-time continuous-state space Markov chain model (DCSMC), the algorithm-based theoretical expression for limiting distribution of stored energy in infinite-size buffer is derived. Further more, with using both the limiting distributions of energy buffers and the probability of transmitter candidates set, the algorithm-based theoretical expressions for outage probability, throughput and timesolt cost for each data of the network are obtained. The simulation results are presented to validate the derived algorithm-based theoretical expressions.

翻译：本文研究了一种基于两个能量收集（EH）解码转发（DF）中继的多跳协作网络，这些中继采用“采集-存储-使用”（HSU）架构，通过能量缓冲区从环境中收集能量。为了提升该网络中的数据传递性能，本文提出在目的节点采用最大比合并（MRC）技术合并来自源节点和中继的信号，并结合一种考虑信道状态信息、位置以及中继能量缓冲区状态的机会路由（OR）算法。通过应用离散时间连续状态空间马尔可夫链模型（DCSMC），推导出基于该算法的无限容量缓冲区中存储能量的极限分布理论表达式。进一步，结合能量缓冲区的极限分布与发送候选集合的概率，得到了基于该算法的网络中断概率、吞吐量以及每数据时隙成本的理论表达式。仿真结果验证了所提出的基于算法的理论表达式的有效性。