This paper presents the design and realization of a compact ultra-wideband (UWB) antenna with a rectangular notch wireless area network (WLAN) band that has controllable notched bandwidth and center frequency. The UWB characteristics of the antenna are achieved by truncating the lower ends of the rectangular microstrip patch, and the notch characteristics are obtained by using electromagnetic bandgap (EBG) structures. EBGs consist of two rectangular metallic conductors loaded on the back of the radiator, which is connected to the patch by shorting pins. A rectangular notch at the WLAN band with high selectivity is realized by tuning the individual resonant frequencies of the EBGs and merging them. Furthermore, the results show that the bandwidth and frequency of the rectangular notch band could be controlled according to the on-demand rejection band applications. In the demonstration, the rectangular notch band was shifted to X-band satellite communication by tuning the EBG parameters. The simulated and measured results show that the proposed antenna has an operational bandwidth from 3.1–12.5 GHz for |S₁₁| < -10 with a rectangular notch band from 5–6 GHz, thus rejecting WLAN band signals. The antenna also has additional advantages: the overall size of the compact antenna is 16 × 25 × 1.52 mm³ and it has stable gain and radiation patterns.

In this article, a multiunmanned aerial vehicle-mobile-edge computing (UAV-MEC) network is proposed for mobile devices (MDs) located far from a terrestrial base station (BS)-MEC. In the UAV-MEC network, the MDs offload tasks to the UAV-MECs, followed by task offloading from the UAV-MECs to the BS-MEC. Each UAV-MEC aims to jointly optimize its energy consumption, queue stability, and the energy consumption of the MDs by controlling its trajectory and offloading ratio. Specifically, the trajectories of the UAV-MECs are controlled to locate themselves at the optimal positions where the transmission energy of the MDs is minimized. Additionally, the UAV-MECs consider the constraints of task processing time and queue stability in determining the amount of task to be offloaded. Thus, an independent proximal policy optimization (IPPO)-based offloading and trajectory control learning model (IM) is proposed to solve these problems, and a convex optimization model (CM) is also presented to show the optimality of the proposed IM. Specifically, in IM, a near-optimal trajectory control for the randomly located MDs is enabled by exploiting channel gain information only without resorting to accurate location information of the MDs. Furthermore, a dynamic offloading ratio control of each UAV-MEC is achieved by considering its queue dynamics. The simulation results show that the proposed IM jointly optimizes energy consumption and queue stability. Consequently, it outperforms other deep reinforcement learning (DRL)-based algorithms by achieving low energy consumption and long service duration. Moreover, it achieves similar performance to CM while requiring remarkably less time on action decision.

In this paper, we apply a reconfigurable intelligent surface (RIS) to a two-way (TW) full-duplex (FD) wireless communication system, where a RIS has N reflecting elements and operates as a relay station forwarding signals between two FD terminals. To demonstrate the advantages of RIS compared with traditional relay, we also present the system and signal models of the TW-FD amplify-and-forward relay (AFR) system. We mathematically analyze the performance of the TW-FD-RIS system by deriving the exact closed-form expressions of the average outage probability (AOP) and the average symbol error rate (ASER) in the case N=1, and approximate expressions of the AOP and the ASER in the case N ≥ 2. Besides, we provide the exact closed-form expression of the AOP and approximate expression of the ASER of the TW-FD-AFR system. Monte-Carlo simulations validate all derived mathematical expressions. Numerical results demonstrate that using the RIS greatly improves the TW-FD communication system's performance compared with using amplify-and-forward (AF) relay. Specifically, even the RIS with one element ( N=1), the AOP and ASER of the TW-FD-RIS system are still lower than those of the TW-FD-AFR system in the low signal-to-noise ratio (SNR) regime. However, in the high SNR regime, the AOP and ASER of the TW-FD-RIS system are higher. In the case N ≥ 2, the AOP and ASER of the TW-FD-RIS system are significantly reduced. On the other hand, the impact of residual self-interference (SI) due to FD transmission mode on the performance of TW-FD-RIS and TW-FD-AFR systems is remarkable, making the AOP and ASER of these two systems reach the error floor in the high SNR regime. Fortunately, the usage of RIS with N ≥ 2 can greatly reduce this impact and avoid the error floor for the TW-FD-RIS system.

A lung nodule is a tiny growth that develops in the lung. Non-cancerous nodules do not spread to other sections of the body. Malignant nodules can spread rapidly. One of the numerous dangerous kinds of cancer is lung cancer. It is responsible for taking the lives of millions of individuals each year. It is necessary to have a highly efficient technology capable of analyzing the nodule in the pre-cancerous phases of the disease. However, it is still difficult to detect nodules in CT scan data, which is an issue that has to be overcome if the following treatment is going to be effective. CT scans have been used for several years to diagnose nodules for future therapy. The radiologist can make a mistake while determining the nodule’s presence and size. There is room for error in this process. Radiologists will compare and analyze the images obtained from the CT scan to ascertain the nodule’s location and current status. It is necessary to have a dependable system that can locate the nodule in the CT scan images and provide radiologists with an automated report analysis that is easy to comprehend. In this study, we created and evaluated an algorithm that can identify a nodule by comparing multiple photos. This gives the radiologist additional data to work with in diagnosing cancer in its earliest stages in the nodule. In addition to accuracy, various characteristics were assessed during the performance assessment process. The final CNN algorithm has 84.8% accuracy, 90.47% precision, and 90.64% specificity. These numbers are all relatively close to one another. As a result, one may argue that CNN is capable of minimizing the number of false positives through in-depth training that is performed frequently.

In this paper, we investigate the secrecy performance of a full-duplex (FD) non-orthogonal multiple access (NOMA) relay system under the presence of multiple non-colluding eavesdroppers over Rayleigh fading channels. Furthermore, to improve legitimate link's capacity, the partial relay selection (PRS) scheme is applied to choose the best relay. To evaluate the secrecy performance, we derive the closed-form expressions of the secure outage probability (SOP) of each user, the overall SOP and the sum effective secrecy throughput (EST) of the considered FD-NOMA relay system. We compare the SOP of the FD-NOMA relay system with that of the half-duplex (HD)-NOMA system and the SOPs of FD-NOMA relay system in the cases that PRS and multiple-relay (MR) schemes are employed at multiple relays. Monte-Carlo simulations verify the correctness of all derived mathematical expressions. Numerical results show that thanks to utilizing FD relays and PRS scheme, the considered FD-NOMA relay system has superior secrecy performance than other systems. Furthermore, increasing the number of FD relays, enhancing their self-interference cancellation capability, and selecting a suitable transmission power help to reduce the SOP of the considered FD-NOMA relay system. Meanwhile, the EST rapidly increases with the equivocation rate of the eavesdropping channel then gradually reaches the saturated maximum value.

For physical layer security with multiple antennas over wireless channels, we consider an artificial noise-aided secure beamforming system. A transmitter can send the confidential information to the legitimate user more securely without eavesdropping when an artificial jamming signal interfering eavesdroppers is transmitted with the confidential information signal. The transmitter splits its transmit power for both the information and jamming signals with a power splitting factor. Under such a system model, we investigate the impacts on secrecy performance of a power splitting factor, the numbers of antennas and eavesdroppers, and noise variance at the legitimate receivers and eavesdroppers by analyzing the expected secrecy rate. The optimal power splitting factor and limiting secrecy rate with large number of antennas are also derived. Moreover, we examine the expected secrecy rate loss caused by channel variation over time. It is shown that the secrecy rate loss is independent of system parameters like a power splitting factor, the numbers of antennas and eavesdroppers in a high signal to interference plus noise ratio (SINR) region. In a low SINR region, on the other hand, the secrecy rate loss changes with system parameters. Simulation results verify these observations on ergodic secrecy rate and its loss due to time-varying channels.