Ergodic Secrecy Rate of Randomly Deployed Cellular Networks Enhanced by Artificial Noise

As the future cellular networks tend to be randomly deployed and equipped with more antennas, we study the enhanced secrecy rate of multiple-input multiple-output (MIMO) systems with a stochastic geometry approach. To avoid intractable computational complexity and to have a deep insight into the security performance of such networks, we derive a closed-form lower bound on the ergodic secrecy rate, based on which the optimal power allocation parameter is derived. Analytic and Monte-Carlo simulation results show that the lower bound is quite tight. The density of base stations (BSs) and number of antennas both greatly infects the optimal power allocation parameter, e.g., positive secrecy rate may not achieved when the BSs density is small, otherwise the optimal power allocation will increase with the increase of the BSs density.