Robust chance-constrained optimization algorithm design for secure wireless powered backscatter communication system

Abstract

For the channel uncertainty and security problems in wireless powered backscatter communication (WPBC) system, a robust chance-constrained optimization algorithm was proposed.Firstly, an optimization problem was established to maximize the minimum transmission rate of the system based on channel uncertainty considering eavesdropping data transmission rate constraints, minimum energy collection constraints and device reflectivity constraints.In order to solve the problem, the original uncertainty problem was transformed into a deterministic optimization problem by using the security approximation method based on Bernstein inequality.Then, combining the properties of inequality, the corresponding auxiliary variables were introduced to transform the deterministic optimization problem into a convex optimization problem, and the standard convex optimization algorithm was used to solve the problem.Finally, the simulation results show the effectiveness of the proposed algorithm.

Keywords

• wireless powered backscatter communication;Internet of things;security;robust optimization;Bernstein-type-inequality