Opportunistic scheduling for a two-way relay network using Markov decision process
Opportunistic scheduling for a two-way relay network using Markov decision process
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DOI：
10.1049/iet-com.2016.0076
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发表时间：
2016-09
期刊：
影响因子：
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通讯作者：
H. Meshgi;Dongmei Zhao
中科院分区：
文献类型：
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作者：
H. Meshgi;Dongmei Zhao
在本研究中，作者研究了时变衰落信道下双向中继网络的传输调度，其中中继节点可以机会地使用传统的单向中继技术或网络编码将流量转发到终端节点。他们制定了一个随机动态计划，目标是最小化长期成本，将其定义为传输功率和数据传输延迟的函数。建立了一个无约束马尔可夫决策过程模型，并对平均成本和贴现成本问题进行了求解。当状态空间较大时，最优解的计算和建模复杂度较高。出于这个原因，他们开发了具有较低复杂性的启发式解决方案。针对成本折现问题，提出了一种基于仿真的动态规划算法，不仅简化了建模过程，降低了计算复杂度，而且实现了成本接近最优。针对平均成本问题，提出了一种启发式调度方案，根据当前时隙和下一时隙的估计成本进行传输决策。启发式方案在极大降低计算复杂度的同时实现了接近最优的性能。
In this study, the authors study transmission scheduling for a two-way relay network in time-varying fading channels, where the relay node can opportunistically use traditional one-way relay technique or network coding to forward traffic to the end nodes. They formulate a stochastic dynamic programme with the objective of minimising the long-run cost, defined as a function of both the transmission power and data transmission delay. An unconstrained Markov decision process model is developed and solved for the average and discounted cost problems. The optimal solution requires high computational and modelling complexity when the state space is large. For this reason, they develop heuristic solutions with lower complexity. For the discounted cost problem, a simulation-based dynamic programming algorithm is proposed that not only simplifies the modelling process and reduces the computational complexity, but also achieves close-to-optimum cost. For the average cost problem, a heuristic scheduling scheme is proposed, which makes transmission decisions based on estimated costs in the current and next time slots. The heuristic scheme achieves close-to-optimum cost performance while greatly reducing the computational complexity.