Several MAC protocols have been proposed forWireless Sensor Networks (WSNs). These include T-MAC , D-MAC and the more commonly utilized SMAC. In this paper, we propose a new MAC layer approach to support mobility in WSNs. The proposed technique utilizes an adaptive frame size approach to overcome the effect of frame losses caused by the Doppler shifts under mobile scenarios. An Extended Kalman Filter is used to predict the frame size for each transmission, which also directly enhances the energy efficiency of the system. Our results show that based on the adaptive frame size predictor and its comparison with the SMAC protocol, the proposed technique can improve overall system performance and deliver enhanced energy efficiency of 24% under mobility. The current implementation of ns-2 does not take into consideration the packet error rate. As another contribution of our work, we have developed a physical layer model for ns-2, which processes the received frame based not only on the fading characteristics of the signal but also the SNR and relative velocity between the nodes. To characterize a more accurate wireless sensor networks' physical layer, we have modeled the Mica-2 sensors in MATLAB and implemented the model in ns-2 for simulations.

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Cognitive radio sensor networks (CRSNs) exploit the cognitive radio concept to allow wireless sensor networks to dynamically access the available channels. However, existing channel sensing techniques developed for cognitive radios are not applicable to the energy-constrained sensor nodes. In this paper, we present two energy-efficient cooperation schemes for CRSNs. The proposed schemes use randomized channel sensing, implicit cooperation, and simplified aggregation to reduce the energy consumed in channel sensing. The proposed implicit OR and implicit AND save up to 55% of the energy, reduce the decision taking time by 30.6%-95%, and achieve similar miss-detection performance compared to their explicit counterparts.