Abstract-In this letter, we design an association strategy to maximize the weighted sum energy efficiency (EE) for massive multiple-input and multiple-output (MIMO)-enabled heterogeneous cellular networks. Considering that the final formulated problem is in a sum-of-ratio form, we first need to transform it into a parametric nonfractional form, by which we can achieve its solution through a two-layer iterative algorithm. The outer layer searches the EE parameters and the multipliers associated with signal-interference-plus-noise ratio constraints using Newton-like method, and the inner layer optimizes the association indices using Lagrange multiplier method. Then, we give some convergence and complexity analyses for the proposed algorithm. Numerical results show that the proposed scheme significantly outperforms the existing one on the system throughput and network EE under a certain condition. In addition, we also investigate the impacts of the number of massive antennas and the transmit power of each pico base station on the association performance.
In REF , the designers developed a two-layer iterative algorithm for the BS assignment to maximize the weighted sum energy efficiency in the downlink.
User Association With Maximizing Weighted Sum Energy Efficiency for Massive MIMO-Enabled Heterogeneous Cellular Networks
IEEE Communications Letters
IEEE Communications Letters
Computer Science Mathematics