Stochastic Downlink Power Control for Various User Requirements

• Main Authors: Zhiyuan Li, Li Chen, Weidong Wang
• Format: Article
• Language: English
• Published: IEEE 2020-01-01
• Series: IEEE Access
• Subjects: Delay-sensitive-users; heterogeneous cellular networks; non-delay-sensitive-users; power control
• Online Access: https://ieeexplore.ieee.org/document/8946612/

Power Control (PC) can coordinate mutual interference between cells in heterogeneous cellular networks (HCNs). Most of the existing works focus on real-time PC problems based on instantaneous channel state information (CSI) for all users. However, such scheme may result in low feasible probability and high energy consumption. If the PC problem is frequently infeasible, the users that require low latency communications will fail to get services in time. In this paper, we classify the users into two categories according to their sensitivity to latency: delay-sensitive-users (DSUs) and non-delay-sensitive-users (NDSUs). We use instantaneous signal-to-interference-plus-noise-ratio (SINR) constraints to ensure the success of data transmission per time slot to meet DSUs' low latency requirements, and the long-term mean data rate constraints to ensure NDSUs' average data rate requirements. On the one hand, the long-term constraints allow the system to sacrifice NDSUs' short-term performance to guarantee DSUs' instantaneous performance when the channel condition is poor. On the other hand, the system will appropriately improve NDSUs' performance to ensure their target mean data rate when the channel condition is good. Under this scheme, we formulate the PC problems under perfect CSI, bounded CSI error and stochastic CSI error scenarios as a uniform problem, which is a non-convex stochastic constrained problem. The recently proposed constrained stochastic successive convex approximation (CSSCA) technique is utilized to handle this problem. Simulation results show that the proposed scheme can significantly improve the feasible probability of DSUs' instantaneous constraints and reduce the network's energy consumption.