Study of Wireless Sensor Network Performance under Different Channel Fading Models

This paper studies the influence of various environmental changes on transmitted signal between sensor nodes (SNs) within a wireless sensor network (WSN). The performance of network using bit error rate (BER) is considered under various channel fading effects. Hence, the relations for BER at different signal to noise ratio (SNR) are formulated under different channels based on distributions, namely: Rician, Rayleigh and Erlang. Thus, closed form expressions for BER analysis of WSN are derived under these channel fading distributions aided by Maple 7 environment. The derived closed form expressions results are compared with conventional channel model based on Nakagami-m distribution. The BER behavior is studied by changing the modulated signal parameters, such as spreading sequence length, M-ary signaling and bit duration. The obtained results confirm that channel based on Rayleigh distribution achieves lower BER at all SNR compared to other channel distributions (except at very low SNR, which is higher than Rician distribution-based model), while channel based on Nakagami distribution achieves lower BER at higher SNR only. It is observed that channels based on Rayleigh and Nakagami-m distributions give the lowest possible BER at higher SNR values, while the channels based on Erlang distribution have the highest BER at all SNR.