信道不确定下增强认知无线电网络有限时域自适应最优分布式功率分配
Finite Horizon Adaptive Optimal Distributed Power Allocation for Enhanced Cognitive Radio Network in the Presence of Channel Uncertainties
摘要：
本文提出了一种新的增强型认知无线电网络，该网络通过功率控制允许次用户在主用户被停用时使用主用户的无线资源，同时通过管理次用户对主用户的干扰，允许次用户在主用户被激活时与主用户共存。因此，针对增强型认知无线电网络，在两种信道不确定性情况下，考虑信道不确定性的影响，提出了一种新的有限时域自适应最优分布式功率分配方案。在情形1中，当主用户在有限时域内不进行通信时，该方案可以迫使次用户的信干比（SIR）收敛到一个更高的目标值，以提高网络吞吐量。一旦主用户被激活，如在情况2中，所提出的方案不仅可以迫使主用户的SIR收敛到一个更高的目标SIR，而且还可以迫使次用户的SIR收敛到一个较低值，以调节他们的干扰Pus在有限的时间段内。为了减轻信道不确定性对信干比的影响，提出了一种新的有限时域自适应最优分布式功率分配算法，该算法在有限时域内使主用户和次用户的信干比收敛到期望的目标信干比，同时使能量消耗最小。仿真结果表明，这种新的有限时域自适应最优分布式功率分配方案能够更好地适应信道变化，具有更快的收敛速度和更低的能耗。
英文摘要：
In this paper, novel enhanced Cognitive Radio Network is considered by using power control where secondary users are allowed to use wireless resources of the primary users when primary users are deactivated, but also allow secondary users to coexist with primary users while primary users are activated by managing interference caused from secondary users to primary users. Therefore, a novel finite horizon adaptive optimal distributed power allocation scheme is proposed by incorporating the effect of channel uncertainties for enhanced cognitive radio network in the presence of wireless channel uncertainties under two cases. In Case 1, proposed scheme can force the Signal-to-interference (SIR) of the secondary users to converge to a higher target value for increasing network throughput when primary users' are not communicating within finite horizon. Once primary users are activated as in the Case 2, proposed scheme can not only force the SIR of primary users to converge to a higher target SIR, but also force the SIR of secondary users to converge to a lower value for regulating their interference to Pus during finite time period. In order to mitigate the attenuation of SIR due to channel uncertainties the proposed novel finite horizon adaptive optimal distributed power allocation allows the SIR of both primary users' and secondary users' to converge to a desired target SIR while minimizing the energy consumption within finite horizon. Simulation results illustrate that this novel finite horizon adaptive optimal distributed power allocation scheme can converge much faster and cost less energy than others by adapting to the channel variations optimally.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
