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Joint Optimization of Interference Coordination Parameters and Base-Station Density for Energy-Efficient
Yanzan Sun1, Han Xu2, Shunqing Zhang3
1Shanghai Institute for Advanced Communication and Data Science, Key laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, Shanghai University, Shanghai 200072, China. yanzansun@shu.edu.cn.
Sensors (Basel, Switzerland)
|May 12, 2019
Summary
This study optimizes heterogeneous networks (HetNets) for better energy efficiency (EE). A heuristic algorithm jointly tunes pico-cell range expansion bias, almost blank subframe power, and base station density for significant EE gains.
Area of Science:
- Telecommunications Engineering
- Wireless Communication Systems
- Network Optimization
Background:
- Heterogeneous networks (HetNets) with macro-cells and pico-cells are crucial for handling increasing data traffic and improving energy efficiency (EE).
- Two-tier HetNet deployments face challenges with inter-tier interference.
- Time domain further-enhanced inter-cell interference coordination (FeICIC) using almost blank subframes (ABS) is essential for mitigating this interference.
Purpose of the Study:
- To jointly optimize key factors influencing network EE in HetNets: pico-cell range expansion (CRE) bias, ABS power, and pico base station (PBS) density.
- To develop algorithms for maximizing network EE in two-tier HetNets.
Main Methods:
- Derivation of a closed-form expression for network EE using a stochastic geometry model.
- Development of linear search algorithms for optimizing CRE bias, ABS power, and PBS density.
- Proposal of a heuristic algorithm for joint optimization of all three factors to maximize global network EE.
Main Results:
- A closed-form expression for network EE was established as a function of CRE bias, ABS power reduction factor, and PBS density.
- Separate and joint optimization algorithms were developed and analyzed.
- Numerical simulations demonstrated significant network EE enhancement with the proposed heuristic algorithm.
Conclusions:
- The joint optimization approach using the heuristic algorithm effectively maximizes network EE in HetNets.
- The proposed method achieves substantial EE improvements with low computational complexity.
- This research provides a practical framework for optimizing HetNet deployment for energy efficiency.
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