Performance Analysis of FFR based Non Orthogonal Spectrum Shared SIMO Systems

Deepak Saluja, Vansha Kher, Pankaj Kumar, Suman Kumar

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

2 Citations (Scopus)

Abstract

Spectrum sharing has been considered as a most promising solution to improve the spectrum efficiency of next-generation wireless networks. In particular, non orthogonal spectrum sharing allows the multiple operators to simultaneously use the available frequency bands, which leads to degradation of signal to interference ratio (SIR) at the intended receivers. To improve the SIR, we have proposed fractional frequency reuse (FFR) based structure for non-orthogonal spectrum shared (NOSS) systems. The coverage probability and average rate expressions are obtained for the proposed FFR based NOSS systems, and it is revealed that the proposed spectrum shared system ensures higher sum rate in comparison to no spectrum shared system, without any significant degradation in coverage probability. In particular, our analysis shows that FFR based NOSS system achieves 33% higher rate as compared to the case of no spectrum shared systems, however only 7% decrement is seen in coverage probability.

Original languageEnglish
Title of host publication2018 13th International Conference on Industrial and Information Systems, ICIIS 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages275-279
Number of pages5
ISBN (Electronic)9781538616765
DOIs
Publication statusPublished - 02-07-2018
Event13th International Conference on Industrial and Information Systems, ICIIS 2018 - Rupnagar, Punjab, India
Duration: 01-12-201802-12-2018

Publication series

Name2018 13th International Conference on Industrial and Information Systems, ICIIS 2018 - Proceedings

Conference

Conference13th International Conference on Industrial and Information Systems, ICIIS 2018
Country/TerritoryIndia
CityRupnagar, Punjab
Period01-12-1802-12-18

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Information Systems
  • Information Systems and Management
  • Industrial and Manufacturing Engineering
  • Artificial Intelligence

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