Small-cell planning based on uplink interference and traffic in two-tier cellular system

Dense small cell deployment is promising to accommodate the explosive growth of cellular traffic, anticipated to have a 1000-fold increase in the following decade, driven by the Internet-of-Things (IoT). Different from traditional cellular traffic, emerging IoT applications will generate a large amount of uplink traffic. Considering uplink, how many small cells should be deployed and where they should be located to maximize the spectrum efficiency are critical, open issues. In this paper, we propose an analytical framework to quantify the uplink interferences between small cell users and macro users considering random node distance distribution, and obtain the overall uplink spectrum efficiency of the two-tier cellular system. Using the analytical framework, a greedy algorithm is proposed to obtain the best locations for deploying a given number of small cells and the optimal small cell number to maximize the spectrum efficiency. The approach is extended to consider arbitrary-shaped and heterogeneous small cells. Simulation results showed that the proposed framework and algorithm can achieve near-optimal performance with low computational cost and substantial performance gain comparing with other methods. The analytical framework and the performance evaluation results provide important guidelines for future small-cell planning.