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An access optimization algorithm for cognitive networks with imperfect spectrum sensing

机译:具有不完美频谱感测的认知网络的访问优化算法

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Spectrum sensing has a major effect on spectrum access of cognitive networks. In the paper, considering imperfect spectrum sensing, opportunistic spectrum access (OSA) optimization is researched. Spectrum occupancy and spectrum sensing activity are modeled and analyzed with Markov process first, by which the no-collision probability between priamry and secondary users at each channel is derived. Then a cross-layer performance index termed effective transmission capacity (ETC) is introduced by combining the no-collision probability at the MAC layer with the channel capacity at the physical layer. Under the criteria to maximize the ETC of secondary networks subject to a collision probability constraint, an access optimization model is proposed, which leads to an optimal OSA algorithm. The maximum ETC obtained by secondary users is therefore calculated. Simulation results indicate that the proposed OSA algorithm can enhance the achievable ETC of secondary networks.
机译:光谱感测对认知网络的频谱访问具有重大影响。 在本文中,考虑到不完美的频谱感测,研究了机会主义频谱访问(OSA)优化。 频谱占用和频谱感测活动是用Markov过程进行建模和分析,首先,通过该过程,从中导出了每个信道处的次要用户和辅助用户之间的无碰撞概率。 然后,通过将MAC层的无碰撞概率与物理层处的信道容量组合来引入横梁性能指数称为有效的传输容量(ETC)。 在最大化对碰撞概率约束的辅助网络等的标准下,提出了一种访问优化模型,这导致了最佳的OSA算法。 因此计算由辅助用户获得的最大ETC。 仿真结果表明,所提出的OSA算法可以增强次要网络的可实现等。

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