Robust Power Control for Multiuser Underlay Cognitive Radio Networks Under QoS Constraints and Interference Temperature Constraints

Abstract

Since the nature of mobility and unreliability in wireless communication system may degrade the communication performance, robustness is one of the main concerns in cognitive radio networks (CRNs). In CRNs, the existing power control algorithms based on the assumption of exact system information may not guarantee the communication requirements due to the parameter uncertainties in real system. In this paper, we propose a robust distributed power control algorithm for underlay CRNs. The novelty in our paper is that we consider all possible parameter uncertainties: channel uncertainty and interference uncertainty. Our objective is to maximize the total throughput of secondary users while channel gain and interference plus noise are uncertain. According to the robust optimization theory, uncertain parameters are modeled by additive uncertainties with bounded errors. Through the worst case principle, we transform the robust power control problem into a deterministic optimization one, which is solved by using Lagrange dual decomposition method. Numerical simulation results show that the proposed algorithm can satisfy the QoS requirements of both secondary users and primary users for all uncertainty realizations.