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Delay-optimal fair scheduling and resource allocation in multiuser wireless relay networks

机译:多用户无线中继网络中的延迟最优公平调度和资源分配

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We consider fair delay-optimal user selection and power allocation for a relay-based cooperative wireless network. Each user (mobile station) has an uplink queue with heterogeneous packet arrivals and delay requirements. Our system model consists of a base station, a relay station, and multiple users working in a time-division multiplexing (TDM) fashion, where per-user queuing is employed at the relay station to make the analysis of such system tractable. We model the problem as an infinite-horizon average reward Markov decision problem (MDP) where the control actions are functions of the instantaneous channel state information (CSI) as well as the queue state information (QSI) at the mobile and relay stations. To address the challenge of centralized control and huge complexity of MDP problems, we introduce a distributive and low-complexity solution. A linear structure is employed which approximates the value function of the associated Bellman equation by the sum of per-node value functions. Our online stochastic value iteration solution converges to the optimal solution almost surely (with probability 1) under some realistic conditions. Simulation results show that the proposed approach outperforms the conventional delay-aware user selection and power allocation schemes.
机译:我们考虑基于中继的协作无线网络的公平延迟最优用户选择和功率分配。每个用户(移动站)都有一个上行队列,该队列具有异构的数据包到达和延迟要求。我们的系统模型由一个基站,一个中继站和多个以时分多路复用(TDM)方式工作的用户组成,其中在中继站采用了按用户排队的方式,以使对该系统的分析变得容易。我们将该问题建模为无限水平平均奖励马尔可夫决策问题(MDP),其中控制动作是移动站和中继站的瞬时信道状态信息(CSI)以及队列状态信息(QSI)的函数。为了解决集中控制和MDP问题的巨大复杂性的挑战,我们引入了一种分布式且低复杂度的解决方案。采用线性结构,该线性结构通过每个节点的值函数之和来近似关联的Bellman方程的值函数。在某些实际条件下,我们的在线随机值迭代解决方案几乎可以肯定地(以概率1)收敛到最优解。仿真结果表明,该方法优于传统的延迟感知用户选择和功率分配方案。

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