Measurement-driven performance analysis of indoor femtocellular networks

  • Authors:

  • Trung-Tuan Luong;Vigneshwaran Subbaraju;Archan Misra;Srinivasan Seshan

  • Affiliations:

  • Singapore Management University, Singapore, Singapore;Singapore Management University, Singapore, Singapore;Singapore Management University, Singapore, Singapore;Carnegie Mellon University, Pittsburgh, PA, USA

  • Venue:
  • Proceedings of the seventh ACM international workshop on Wireless network testbeds, experimental evaluation and characterization
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper describes initial empirical studies, performed on a 6-node 3G indoor femtocellular testbed, that investigate the impact of pedestrian mobility on network parameters, such as handoff behavior and data throughput. The studies establish that, owing to the small radii of cells, even modest changes in movement speed can have disproportionately large impact on handoff patterns and network throughput. By also revealing a strong temporal dependency effect, the studies motivate the need for algorithms to accurately predict RF signal strength distributions in dynamic indoor environments. We present such an RF prediction algorithm, based on crowd-sourced signal strength readings, and show that the algorithm can predict RF signal strengths with an average estimation error of 3 dBm.