Optimal and suboptimal packet scheduling over correlated time varying flat fading channels
Optimal and suboptimal packet scheduling over correlated time varying flat fading channels
复制标题
DOI：
10.1109/twc.2006.1611068
复制
发表时间：
2006-11
影响因子：
10.4
通讯作者：
A. Karmokar;D. Djonin;V. Bhargava
中科院分区：
文献类型：
--
作者：
A. Karmokar;D. Djonin;V. Bhargava
我们解决了在相关衰落信道上的最优分组调度问题，该问题在最小化三个目标之间进行权衡：平均传输功率，平均延迟和平均丢包概率。我们证明了该问题形成了一个弱通信马尔可夫决策过程，并将问题表述为无约束问题和约束问题。采用相对值迭代（RVI）算法求解无约束问题的最优确定性策略，采用线性规划（LP）技术求解有约束问题的最优随机策略。RVI算法在可行延迟区域内只能获得有限数量的调度策略，而LP算法可以生成所有可行延迟的策略，并且具有固定的丢弃概率，计算速度快于RVI算法。我们展示了通道和缓冲区状态的最优确定性策略的结构，并形成了一个简单的日志函数次最优调度程序，它近似遵循最优结构。给出了恒定泊松到达和突发泊松到达的性能结果，并将所提出的次优调度程序与最优调度程序和通道阈值调度程序进行了比较。我们的次优调度程序对每个可行的延迟执行接近于最优调度程序，并且对不同的通道参数、操作数量和传入流量分布具有鲁棒性。
We address the issue of optimal packet scheduling over correlated fading channels which trades off between minimization of three goals: average transmission power, average delay and average packet dropping probability. We show that the problem forms a weakly communicating Markov decision process and formulate the problem as both unconstrained and constrained problem. Relative value iteration (RVI) algorithm is used to find optimal deterministic policy for unconstrained problem, while optimal randomized policy for constrained problem is obtained using linear programming (LP) technique. Whereas with RVI only a finite number of scheduling policies can be obtained over the feasible delay region, LP can produce policies for all feasible delays with a fixed dropping probability and is computationally faster than the RVI. We show the structure of optimal deterministic policy in terms of the channel and buffer state and form a simple log functional suboptimal scheduler that approximately follows the optimal structure. Performance results are given for both constant and bursty Poisson arrivals, and the proposed suboptimal scheduler is compared with the optimal and channel threshold scheduler. Our suboptimal scheduler performs close to the optimal scheduler for every feasible delay and is robust to different channel parameters, number of actions and incoming traffic distributions.