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Throughput Enhancement of Full-Duplex CSMA Networks via Adversarial Multi-Player Multi-Armed Bandit

机译:通过对抗性多层多层武装匪徒增强全双工CSMA网络的吞吐量

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This paper investigates the network-level throughput of a full-duplex (FD) enabled CSMA network, considering transmit power (TP) control and carrier-sensing threshold (CST) adjustment. With the FD technique, a transmitter-receiver pair can transmit and receive simultaneously in the same frequency band. The motivation is to find an optimal combination of TP and CST for each link so as to maximize the network throughput. The challenge is that adjusting each link's TP and CST will change the network's carrier-sensing relation and interference relation, which consequently leads to a computationally intractable network optimization problem. To overcome the complexity challenge, we model this network throughput maximum problem within a multi-player multi-armed bandit (MP-MAB) framework, in which the players are the FD-enabled links and the arms are the combinations of TP and CST. The proposed framework can also be viewed as an adversarial MP-MAB due to the hostile contention among links. Furthermore, we propose a refined Exponential-weight algorithm for Exploration and Exploitation (Exp3) to solve this adversarial MP-MAB problem. The refined Exp3 algorithm proceeds in epochs and starts with some prior knowledge. The numerical results show that the proposed method can improve the network throughput by more than 42%, compared with the random selection method. Meanwhile, the proposed algorithm exhibits a fast convergence rate in random network scenario.
机译:本文研究了启用了全双工(FD)的CSMA网络的网络级吞吐量,同时考虑了发射功率(TP)控制和载波侦听阈值(CST)调整。使用FD技术,一对收发器可以在同一频带中同时进行发送和接收。动机是为每个链路找到TP和CST的最佳组合,以使网络吞吐量最大化。挑战在于调整每个链路的TP和CST将改变网络的载波感知关系和干扰关系,从而导致计算上难以解决的网络优化问题。为了克服复杂性挑战,我们在多玩家多武装匪徒(MP-MAB)框架内对该网络吞吐量最大问题进行建模,在该框架中,玩家是启用FD的链接,而手臂是TP和CST的组合。由于链接之间存在敌意竞争,因此所提出的框架也可以被视为对抗性MP-MAB。此外,我们提出了一种改进的探索和开发指数权重算法(Exp3),以解决该对抗性MP-MAB问题。完善的Exp3算法以新纪元进行,并以一些先验知识开始。数值结果表明,与随机选择方法相比,该方法可以将网络吞吐量提高42%以上。同时,该算法在随机网络环境下具有较高的收敛速度。

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