4.7 Article

Throughput and Energy Efficiency Analysis of Small Cell Networks with Multi-Antenna Base Stations

期刊

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
卷 13, 期 5, 页码 2505-2517

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TWC.2014.031714.131020

关键词

Poisson point process; stochastic geometry; cellular networks; outage probability; network throughput; energy efficiency

资金

  1. Hong Kong Research Grant Council [610311]
  2. Hong Kong RGC Direct Allocation Grant [DAG11EG03]

向作者/读者索取更多资源

Small cell networks have recently been proposed as an important evolution path for the next-generation cellular networks. However, with more and more irregularly deployed base stations (BSs), it is becoming increasingly difficult to quantify the achievable network throughput or energy efficiency. In this paper, we develop an analytical framework for downlink performance evaluation of small cell networks, based on a random spatial network model, where BSs and users are modeled as two independent spatial Poisson point processes. A new simple expression of the outage probability is derived, which is analytically tractable and is especially useful with multiantenna transmissions. This new result is then applied to evaluate the network throughput and energy efficiency. It is analytically shown that deploying more BSs can always increase the network throughput, but the throughput will scale with the BS density first linearly, then logarithmically, and finally converge to a constant. On the other hand, increasing the number of BS antennas can decrease the outage probability exponentially, thus can always increase the network throughput. However, increasing the BS density or the number of transmit antennas will first increase and then decrease the energy efficiency if the non-transmission power or the circuit power consumption is less than certain thresholds, and the optimal BS density and the optimal number of BS antennas can be found. Otherwise, the energy efficiency will always decrease. Simulation results shall demonstrate that our conclusions based on the random network model are general and also hold in a regular grid-based model.

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