Statistical Analysis of Noise Propagation Effect for Mixed RFFSO AF Relaying Application in Wireless Sensor Networks In this paper, we investigate the socalled noise propagation effect in a mixed radiofrequencyfreespace optical (RFFSO) amplifyingandforwarding (AF) relaying system that is applied for data transmission in wireless sensor networks. The noise propagation could be essentially severe when batterycharged sensor nodes have very limited transmit power. We provide an exact expression on the cumulative distribution function (CDF) of endtoend signaltonoise power ratio (SNR) for a dualhop mixed RFFSO AF relaying system. We assume a tightly powerconstrained amplifying gain at the relay, which has been usually ignored in existing performance studies for the mixed RFFSO AF system. It however should be considered to properly evaluate the noise propagation effect especially if the relaying power is not infinite or the sensor has a poor budget in transmit power. We apply the derived exact CDF to evaluate the system performances such as outage probability, average biterror rate, and ergodic capacity. Numerical investigation is used to justify that the proposed analysis is exactly matched with the simulation and shows that the performance gap caused by the inclusion of the noise propagation effect is significant (about 212%) especially when the SNR per hop is in the medium or the lowSNR ranges (i.e., at 1020 dB).

Modeling Transmission Degradation on FSO Links Caused by Weather Phenomena for WMN Optimization This work deals with wireless mesh networks (WMN) composed of FSO (free space optics) links. Although FSO links realize broadband transmission at low cost, their drawback is sensitivity to adverse weather conditions causing transmission degradation on multiple links. Hence, designing such FSO networks requires an optimization model to find the cheapest configuration of link capacities that will be able to carry an acceptable level of the demanded traffic in all weather states that can be foreseen in network operation. Such a model can be achieved using robust optimization techniques, and for that it is important to find a tractable way of characterizing possible link (capacity) degradation states corresponding to weather conditions not known in advance. In the paper we show how weather records can be translated to vectors of link capacity available (after degradation) in particular weather states, and how the resulting link degradation states may be represented mathematically in a compact and tractable way to be exploited in optimization. To solve the second task we will make use of a generalization of a combinatorial problem of finding a minimum hitting set to deduce a compact set approximating a given set of link degradation states. Finally, we illustrate the effectiveness of our model by means of a numerical study.