Cross-layer based erasure code to reduce the 802.11 performance anomaly: when FEC meets ARF
Proceedings of the 6th ACM international symposium on Mobility management and wireless access
Fault-Impact models based on delay and packet loss for IEEE 802.11g
QEST'13 Proceedings of the 10th international conference on Quantitative Evaluation of Systems
General all-Layers combined with Efficient WLAN MAC Layer Headers Compression
Proceedings of International Conference on Advances in Mobile Computing & Multimedia
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Bit Error Rate (BER) and Packet Error Rate (PER) are important Quality of Service Parameters for Wireless network. Most of researches in QoS have been devoted to the analysis of BER which gives insight to the mean behavior of the wireless network. However the mean behavior is not sufficient for PER evaluation and more precise characterization of the error process is needed. Residual errors at the output of physical layer are not uniformly distributed. This is due to error correcting mechanism used at physical layer as well as the correlation induced by the memory existing in fading channels. Not taking into account the correlation in the error process and assuming for example that errors are uniformly distributed, as done in most of the published paper in wireless networking, lead to gross overestimation of PER. This over-estimation can go to tenfold factors as will be shown in this paper. In a previous paper we presented a new analytic formula for predicting Packet Error rate in Wireless networks where convolutional codes are used jointly with Viterbi decoder over an AWGN channel. The approach was based on a precise analysis of the error process at the output of the Viterbi decoder. This formula was shown to precisely predict the PER as a function of convolutional code parameter and SNR over the AWGN channel. In this paper we extend the result obtained for the AWGN channel to the case of fading channel under block fading hypothesis. A closed form formulas approximation for derivation of PER in Fading channel is proposed and it is shown that it give very tight prediction for the PER.