%0 Journal Article
%T Finite Horizon Adaptive Optimal Distributed Power Allocation for Enhanced Cognitive Radio Network in the Presence of Channel Uncertainties
%A Hao Xu
%A S. Jagannathan
%J International Journal of Computer Networks & Communications
%D 2013
%I Academy & Industry Research Collaboration Center (AIRCC)
%X In this paper, novel enhanced Cognitive Radio Network (CRN) is considered by using power controlwhere secondary users (SUs) are allowed to use wireless resources of the primary users (PUs) when PUsare deactivated, but also allow SUs to coexist with PUs while PUs are activated by managinginterference caused from SUs to PUs. Therefore, a novel finite horizon adaptive optimal distributedpower allocation (FH-AODPA) scheme is proposed by incorporating the effect of channel uncertaintiesfor enhanced CRN in the presence of wireless channel uncertainties under two cases. In Case 1,proposed scheme can force the Signal-to-interference (SIR)of the SUs to converge to a higher targetvalue for increasing network throughput when PU¡¯s are not communicating within finite horizon. OncePUs are activated as in the Case 2, proposed scheme cannot only force the SIR¡¯s of PUs to converge to ahigher target SIR, but also force the SIR¡¯s of SUs to converge to a lower value for regulating theirinterference to Pus during finite time period. In order to mitigate the attenuation of SIR¡¯s due to channeluncertainties the proposed novel FH-AODPA allows the SIR¡¯s of both PUs¡¯ and SUs¡¯ to converge to adesired target SIR while minimizing the energy consumption within finite horizon. Simulation resultsillustrate that this novel FH-AODPA scheme can converge much faster and cost less energy than othersby adapting to the channel variations optimally.
%K Adaptive optimal distributed power allocation (AODPA)
%K Signal-to-interference ratio (SIR)
%K Channel uncertainties
%K Cognitive Radio Network
%U http://airccse.org/journal/cnc/0113cnc01.pdf