Feng Jianyuan, Feng Zhiyong
School of Information and Communication Engineering, Beijing University of Posts and Telecommunications (BUPT), Beijing 100876, China.
Sensors (Basel). 2017 Sep 11;17(9):2077. doi: 10.3390/s17092077.
Network densification is attracting increasing attention recently due to its ability to improve network capacity by spatial reuse and relieve congestion by offloading. However, excessive densification and aggressive offloading can also cause the degradation of network performance due to problems of interference and load. In this paper, with consideration of load issues, we study the optimal base station density that maximizes the throughput of the network. The expected link rate and the utilization ratio of the contention-based channel are derived as the functions of base station density using the Poisson Point Process (PPP) and Markov Chain. They reveal the rules of deployment. Based on these results, we obtain the throughput of the network and indicate the optimal deployment density under different network conditions. Extensive simulations are conducted to validate our analysis and show the substantial performance gain obtained by the proposed deployment scheme. These results can provide guidance for the network densification.
网络致密化近来因其能够通过空间复用提高网络容量以及通过卸载缓解拥塞而受到越来越多的关注。然而，过度致密化和激进卸载也可能由于干扰和负载问题导致网络性能下降。在本文中，考虑到负载问题，我们研究使网络吞吐量最大化的最优基站密度。利用泊松点过程（PPP）和马尔可夫链，推导出期望链路速率和基于竞争的信道利用率作为基站密度的函数。它们揭示了部署规则。基于这些结果，我们得到网络吞吐量并指出不同网络条件下的最优部署密度。进行了大量仿真以验证我们的分析，并展示所提出的部署方案获得的显著性能提升。这些结果可为网络致密化提供指导。
