The proposed paper presents a flexible antenna that is capable of operating in several frequency bands, namely 2.45 GHz, 5.8 GHz, and 8 GHz. The first two frequency bands are frequently utilized in industrial, scientific, and medical (ISM) as well as wireless local area network (WLAN) applications, whereas the third frequency band is associated with X-band applications. The antenna, with dimensions of 52 mm × 40 mm (0.79 λ × 0.61 λ), was designed using a 1.8 mm thick flexible kapton polyimide substrate with a permittivity of 3.5. Using CST Studio Suite, full-wave electromagnetic simulations were conducted, and the proposed design achieved a reflection coefficient below −10 dB for the intended frequency bands. Additionally, the proposed antenna achieves an efficiency value of up to 83% and appropriate values of gain in the desired frequency bands. In order to quantify the specific absorption rate (SAR), simulations were conducted by mounting the proposed antenna on a three-layered phantom. The SAR1g values recorded for the frequency bands of 2.45 GHz, 5.8 GHz, and 8 GHz were 0.34, 1.45, and 1.57 W/Kg respectively. These SAR values were observed to be significantly lower than the 1.6 W/Kg threshold set by the Federal Communication Commission (FCC). Moreover, the performance of the antenna was evaluated by simulating various deformation tests.

In disaster areas With growing number of user demands and the exponential growth and development of Internet of Everything (IoE), the improvement in the achieved spectrum efficiency in Unmanned Aerial Vehicles (UAVs) communication-enabled wireless networks in 6G and 5G are needed. This work aim to improve the spectrum efficiency when redundancies (e.g., correlations in the source like co-located video sensors) are exploited. While it is intuitive that redundancies can be exploited to enhance spectrum efficiency. Here, a linear program is formulated to optimally allocate bandwidth to the links according the demands on each link, while satisfying the spatial spectrum reuse constraints. The linear program is then used to analytically establish the enhancement in spectrum efficiency in the presence of source correlation. Then, different mechanisms are identified to exploit correlations to maximize the improvement in the spectrum efficiency with a trade-off between accuracy and computational complexity. Results indicate that the spectrum efficiency can be enhanced by one to two orders of magnitude by identifying the correct set of source correlations. In terms of network performance, almost 100% of delay intolerant traffic can be admitted into the network by suitably exploiting source correlations and the mean delay for delay tolerant traffic can be reduced by 50 − 88%.