Energy Efficient User Association and Power Allocation in Millimeter-Wave-Based Ultra Dense Networks With Energy Harvesting Base Stations

TLDR

Millimeter‑wave (mmWave) technology is emerging to meet the growing mobile data demand, and ultra‑dense networks (UDNs) using mmWave are expected to boost both energy and spectral efficiency. This study aims to design user association and power allocation strategies for mmWave‑based UDNs that satisfy load‑balance, energy‑harvesting, QoS, energy‑efficiency, and interference constraints. The joint problem is formulated as a mixed‑integer program, relaxed to a convex problem, and solved via Lagrangian dual decomposition with an iterative gradient algorithm that converges rapidly. Simulations show the algorithm converges quickly to an optimal point, with lower complexity and superior performance compared to existing methods.

Abstract

Millimeter wave (mmWave) communication technologies have recently emerged as an attractive solution to meet the exponentially increasing demand on mobile data traffic. Moreover, ultra dense networks (UDNs) combined with mmWave technology are expected to increase both energy efficiency and spectral efficiency. In this paper, user association and power allocation in mmWave-based UDNs is considered with attention to load balance constraints, energy harvesting by base stations, user quality of service requirements, energy efficiency, and cross-tier interference limits. The joint user association and power optimization problem are modeled as a mixed-integer programming problem, which is then transformed into a convex optimization problem by relaxing the user association indicator and solved by Lagrangian dual decomposition. An iterative gradient user association and power allocation algorithm is proposed and shown to converge rapidly to an optimal point. The complexity of the proposed algorithm is analyzed and its effectiveness compared with existing methods is verified by simulations.