Date Added: Nov 2012
It is well known that there are two kinds of causes, namely channel-errors and collisions, which lead to high probability of packet losses and errors in wireless networks. The ability of discriminating the above two causes provides many opportunities for implementing high efficient networking protocols in Wireless Sensor Networks (WSNs). This paper presents EasiPLED, a discriminator that can accurately and timely predict these two causes. EasiPLED has three salient features. First, it investigates F-BER patterns and statistic characteristics of RSSI in different indoor environments through extensive experimental studies. F-BER is the Frame-level Bit Error Rate measured at the receiver side by a coarse-grained method without incurring any overhead.