Finite Horizon Adaptive Optimal Distributed Power Allocation for Enhanced Cognitive Radio Network in the Presence of Channel Uncertainties

TL;DR

This paper proposes a finite horizon adaptive distributed power allocation scheme for cognitive radio networks that manages interference and optimizes SIR under channel uncertainties, improving convergence speed and energy efficiency.

Contribution

It introduces a novel finite horizon adaptive optimal distributed power allocation method that accounts for channel uncertainties in cognitive radio networks.

Findings

Faster convergence of power allocation compared to existing schemes.

Reduced energy consumption during power control.

Effective management of interference with primary users.

Abstract

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.