Adnan Mohammad Arar

Spectrum sensing in cognitive radio (CR) is a critical process as it directly influences the accuracy of detection. Noise uncertainty affects the reliability of detecting vacant holes in the spectrum, thus limiting the access of that spectrum by secondary users (SUs). In such uncertain environment; SUs sense the received power of a primary user (PU) independently with different measures of signal-to-noise ratio (SNR). Long sensing time serves in mitigating the effect of noise uncertainty, but on the cost of throughput performance of CR system. In this paper, the scheme of an asynchronous and crossed sensing-reporting is presented. The scheme reduces energy consumption during sensing process without affecting the detection accuracy. Exploiting the included idle time (𝑇𝑖) in sensing time slot; each SU collects power samples with higher SNR directly performs the reporting process to a fusion center (FC) consecutively. The FC terminates the sensing and reporting processes at a specific sensing time that corresponds to the lowest SNR (𝑆𝑁𝑅𝑤𝑎𝑙𝑙). Furthermore, this integrated scheme aims at optimizing the total frame duration (𝑇𝑓). Mathematical expressions of the scheme are obtained. Analytical results show the efficiency of the scheme in terms of energy saving and throughput increment under noise uncerainty.

Radon concentrations were measured using CR-39 passive dosimeters in Beit Ummar city. 150 dosimeters were distributed over the study area dwellings according to the fraction of the population. The exposure started from October 2014 and lasted for 90 days. The city was divided into five sectors with six categories for each; corridor, kitchen, living room, saloon, bedroom and store. The influence of floor number and building type was introduced. Obtained results have recorded relatively high radon concentration in 73% of the studied houses. This is explained due to several factors such as poor ventilation, construction materials, and continuous usage of heating during this period and age of the building. Different parameters were calculated based on the measurements of track density of the distributed dosimeters in order to estimate the risk of radiation exposure; those parameters are: radon concentration (CRn), exposure to radon progeny (EP), indoor annual effective dose (AED) and number of lung cancer cases per year per million persons (LCC). The results showed that the radon concentrations and the resulting doses in the monitored chambers exceed the safe limits recommended by the WHO and EPA in some aspects. Therefore, health risk due to radon is possible.