Fair Data Collection and Energy-Efficient Data Transmission for Heterogeneous NAN in Smart Grid

Abstract

In smart grid, the neighborhood area network (NAN) serves as a bridge connecting smart meters and meter data management system (MDMS), and is one of the most important sections in smart grid communication. In this paper, we study the data collection and transmission issue for NAN in smart grid. Firstly, considering the communication range, the flexible and cost-effective deployment, we propose a heterogeneous NAN architecture with cognitive radio (CR)-based data collection and WiMAX-based data transmission in the first and second phase, respectively. Then, taking into account the almost uniform data volume and the disparate channel conditions, the data collection of smart meters is optimized with max-min fairness among them; while the data transmission of all the routers is optimized energy-efficiently with rate constraints, so as to save energy and assure the stability of the system. For the problem solution, the joint channel and power allocation algorithm for max-min fair data collection is achieved through relaxation, convex transformation and using the Lagrange method, and by introducing a subtractive transformation, the energy-efficient data transmission with rate constraints is obtained by applying an iterative algorithm, where the optimal joint channel allocation and power distribution algorithm based on relaxation and Lagrange method is developed for the inner loop problem. Compared with random schemes, numerical results demonstrate the effectiveness of the proposed data collection and data transmission algorithms, as well as the joint data collection and transmission scheme.