Interference-aware channel segregation based dynamic channel assignment using SNR-based transmit power control

Yuki Matsumura, Katsuhiro Temma, Koichi Ishihara, B. A.Hirantha Sithira Abeysekera, Tomoaki Kumagai, Fumiyuki Adachi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

In any wireless network, the same channel must be reused at spatially separated access points (APs) or base stations (BSs) and hence, the co-channel interference (CCI) limits the transmission quality. Therefore, it is very important to reuse the channels so as to minimize the CCIs. We recently proposed an interference-aware channel segregation based dynamic channel assignment (IACS-DCA), which can form a stable channel reuse pattern in a distributed manner. The use of transmit power control (TPC) can avoid the excessive transmit power and hence, contributes to reducing the CCI. An interesting question is if the IACS-DCA can form a stable channel reuse pattern when TPC is used. In this paper, we give an answer to this question and show by computer simulation that a stable channel reuse pattern can be formed even if TPC is used and that the transmit power can be significantly reduced.

Original languageEnglish
Title of host publicationISPACS 2013 - 2013 International Symposium on Intelligent Signal Processing and Communication Systems
Pages792-796
Number of pages5
DOIs
Publication statusPublished - 2013 Dec 1
Event2013 21st International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2013 - Naha, Okinawa, Japan
Duration: 2013 Nov 122013 Nov 15

Publication series

NameISPACS 2013 - 2013 International Symposium on Intelligent Signal Processing and Communication Systems

Other

Other2013 21st International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2013
CountryJapan
CityNaha, Okinawa
Period13/11/1213/11/15

Keywords

  • channel segregation
  • co-channel interference
  • dynamic channel assignment
  • transmit power control

ASJC Scopus subject areas

  • Artificial Intelligence
  • Signal Processing

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