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Decentralized Dynamic Rate and Channel Selection Over a Shared Spectrum
IEEE Transactions on Communications ( IF 8.3 ) Pub Date : 2021-03-15 , DOI: 10.1109/tcomm.2021.3066002
Alireza Javanmardi , Muhammad Anjum Qureshi , Cem Tekin

We consider the problem of distributed dynamic rate and channel selection in a multi-user network, in which each user selects a wireless channel and a modulation and coding scheme (corresponds to a transmission rate) in order to maximize the network throughput. We assume that the users are cooperative, however, there is no coordination and communication among them, and the number of users in the system is unknown. We formulate this problem as a multi-player multi-armed bandit problem and propose a decentralized learning algorithm that performs almost optimal exploration of the transmission rates to learn fast. We prove that the regret of our learning algorithm with respect to the optimal allocation increases logarithmically over rounds with a leading term that is logarithmic in the number of transmission rates. Finally, we compare the performance of our learning algorithm with the state-of-the-art via simulations and show that it substantially improves the throughput and minimizes the number of collisions.

中文翻译:

共享频谱上的分散动态速率和信道选择

我们考虑多用户网络中的分布式动态速率和信道选择问题,其中每个用户选择一个无线信道和调制和编码方案(对应于传输速率)以最大化网络吞吐量。我们假设用户是合作的,但是他们之间没有协调和沟通,系统中的用户数量是未知的。我们将此问题表述为多人多臂老虎机问题,并提出了一种分散式学习算法,该算法对传输速率进行几乎最佳的探索以快速学习。我们证明了我们的学习算法在最优分配方面的遗憾在轮次中以对数方式增加,前导项在传输速率的数量上是对数的。最后,
更新日期:2021-03-15
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