TSA: Time Series Adaptation for enhanced Cell Reselection in UMTS

Abstract

Mobile Stations (MSs) operate in either idle mode or connected mode. However, previous studies have mainly focused on the connected mode even though the MSs remain their most of time in the idle mode. In this paper, we propose an efficient Cell Reselection algorithm, namely TSA (Time Series Adaptation), to decide the best cell in UMTS (Universal Mobile Telecommunication Systems). The proposed algorithm has the advantage of selecting the strongest RSCP cell out of neighboring cells for the cell reselection by utilizing time series parameters (e.g., β <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</inf> and β <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</inf> ). We evaluate the proposed cell reselection with TSA through the real-system testbed (Stand Alone Simulator). As a result, the TSA provides a proper decision for the cell reselection thereby avoiding the occurrence of unnecessary ping-pong cell reselection.