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Exploration vs exploitation for distributed channel access in cognitive radio networks: A multi-user case study

机译:认知无线电网络中分布式信道访问的探索与开发:多用户案例研究

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In this paper, we consider the design of efficient strategies that allow multiple secondary users to choose channels with unknown idle probabilities to sense and access without centralized control. Due to the limited sensing capability of CR, the secondary user cannot sense all the channels simultaneously. How to design intelligent sensing strategy is crucial to track the varying spectrum opportunities. However, the availability probability of each channel is not known a prior. The need to learning the information creates a fundamental trade-off between exploration and exploitation. First, the scenario in which a single cognitive user wishes to opportunistically exploit the availability of idle spectrum is considered. An index based strategy from the classical multi-armed bandit problem is efficient to achieve asymptotically optimal performance. Then, the multiuser case is considered. However, the index based strategy for the single user cannot be applied to multiuser scenario directly. If so, collisions among secondary users degrade the overall network performance greatly. We find that randomized selection of the channel to sense is essential to avoid collisions. We extend the exploration and exploitation idea to the multiuser scenario and come up with a randomization based mixed strategy which takes the activity of other secondary users into consideration in the learning process and at the same time achieves exploration and exploitation tradeoff. Numerical simulation results show that the proposed scheme can achieve near optimal in terms of total network performance as the centralized scenario without any information exchange among cognitive users.
机译:在本文中,我们考虑了高效策略的设计,该策略允许多个二级用户选择具有未知空闲概率的通道来进行感知和访问,而无需集中控制。由于CR的感测能力有限,因此次要用户无法同时感测所有通道。如何设计智能传感策略对于跟踪变化的频谱机会至关重要。但是,每个信道的可用性概率不是先验的。学习信息的需求在勘探和开发之间产生了根本的权衡。首先,考虑单个认知用户希望机会性地利用空闲频谱的情况。来自经典多臂匪问题的基于索引的策略可以有效地实现渐近最优性能。然后,考虑多用户情况。但是,针对单用户的基于索引的策略不能直接应用于多用户方案。如果是这样,辅助用户之间的冲突将大大降低整体网络性能。我们发现,随机选择要感知的通道对于避免冲突至关重要。我们将探索和开发思想扩展到多用户场景,并提出了一种基于随机化的混合策略,该策略在学习过程中考虑了其他二级用户的活动,同时实现了探索和开发的权衡。数值仿真结果表明,所提出的方案作为集中场景,在总网络性能方面几乎可以达到最佳,而认知用户之间无需任何信息交换。

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