Theoretical Analysis of Interference Effect from Idle Cells in Ultra-Dense Small Cell Networks

Yosub Park, Daesik Hong

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

One of the key characteristics in ultra-dense small cell networks (UDNs) is the advent of idle cells which have no associated user equipment (UE). Indeed, idle cells always transmit the cell-specific reference signal (CRS), while they do not transmit data signals. In this paper, we focus on providing a theoretical analysis on the effect of idle cells in terms of the aggregate interference and signal-To-interference ratio (SIR). First, we investigate how idle cells affect the CRS interference (i.e., aggregate interference at the CRS) and data interference (i.e., aggregate interference at the data signals). Specifically, we derive the statistical distribution for the ratio of CRS interference to data interference. Second, by using the Kolmogorov-Smirnov statistic, we qualitatively measure the amount of SIR mismatch between CRS SIR and data SIR caused by idle cells in the UDN. In the numerical results, we show that CRS interference becomes larger than data interference with cell densification. We also illustrate that the SIR mismatch between CRS SIR and data SIR becomes severe, as base station (BS)-To-UE density ratio increases (i.e., idle BS ratio increases). Moreover, we can confirm that the SIR mismatch in indoor environment is weaker than outdoor owing to the multiple penetration losses such as outer walls and inner walls.

Original languageEnglish
Pages (from-to)26881-26894
Number of pages14
JournalIEEE Access
Volume6
DOIs
Publication statusPublished - 2018 May 3

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea Grant through the Korean Government (MSIT) under Grant 2018R1A2A1A05021029 and by the Institute for Information and Communications Technology Promotion Grant through the Korean Government (MSIP) (Development on the core technologies of transmission, modulation, and coding with low-power and low-complexity for massive connectivity in the IoT environment) under Grant 2016-0-00181.

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

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