Sensor Networks for Estimating and Updating the Performance of Cellular Systems

We investigate the use of an auxiliary network of sensors to assist radio resource management in a cellular system. Specifically, we discuss the number and placement of sensors in a given cell for estimating its signal coverage. Here, an "outage" is said to occur at a location if the mobile receiver there has inadequate signal-to-noise ratio (SNR-based outage) or, using another criterion, inadequate signal-to-interference ratio (SIR-based outage); and the "outage probability" is the fraction of the cell area over which outage occurs. A design goal is to confine the number of sensors per cell to an acceptable level while accurately estimating the outage probability. The investigation uses a generic path loss model incorporating distance effects and spatially correlated shadow fading. Our emphasis is the performance prediction accuracy of the sensor network, rather than cellular system analysis per se. Through analysis and simulation, we assess several approaches to estimating the outage probability. Applying the principle of importance sampling to the sensor placement, we show that a cell outage probability of ~ Po can be accurately estimated using ~ 10/Po power-measuring sensors distributed in a random uniform way over base-mobile distances from 50% to 100% of the cell radius. This result applies to both SNR-based and SIR-based cases, in both indoor and outdoor environments.