Robust Power Allocation for NOMA Heterogeneous Networks with EH under Imperfect CSI

A robust power allocation is proposed for downlink non-orthogonal multiple access (NOMA) heterogeneous networks with EH (Energy harvesting) under imperfect channel state information (CSI). In order to achieve green communication, an EH-aided scheme by leveraging energy from macro base station (MBS) signal and interference signal transmitted from other SBSs is proposed, which reduces the power burden and energy consumption of the SBS. In order to conform to the actual communication scenario, we construct an energy efficiency optimization function under imperfect CSI with considering the constraint of the outage probability interference power in macro cell user (MCU). However, the formulated optimization problem is non-convex due to the fractional form of the objective function and the probabilistic constraints of the outage probability limit. To cope with this problem, we propose a robust power allocation scheme. Firstly, the probabilistic problem is converted into a robust non-probabilistic problem by the minimax probability machine (MPM) and robust optimization theory. Then, the robust non-probabilistic problem can be transformed into the convex optimization problem via Dinkelbach method and sequential convex programming. Finally, the optimal transmission powers of the small cell users (SCUs) are obtained by Lagrange dual approach. The simulation results show that the robust power allocation scheme for NOMA heterogeneous networks with EH under imperfect CSI can significantly improve energy efficiency compared with traditional power allocation algorithms.

Robust Power Allocation for Cooperative Localization in Jammed Wireless Sensor Networks

In this paper, we propose robust power allocation strategies to improve the localization performance in cooperative wireless sensor localization systems when suffering interference of jammer nodes. In wireless sensor localization systems, transmitting power strategies will affect the localization accuracy and determine the lifetime of wireless sensor networks. At the same time, the power allocation problem will be evolution to a new challenge when there are jammed nodes. So in this paper, we first present the optimization framework in jammed cooperative localization systems. Moreover, the imperfect parameter estimations of agent and jammer nodes are considered to develop robust power allocation strategies. In particular, this problem can be transformed into second-order cone programs (SOCPs) to obtain the end solution. Numerical results show the proposed power allocation strategies can achieve better performance than uniform power allocation and the robust schemes can ensure lower localization error than nonrobust power control when systems are subject to uncertainty.