No abstract

In this paper, an antenna array for the X-band aerial landing system has been proposed. The proposed antenna is an ellipse-shaped leakywave array radiating in slow mode wave and has a scanning range of 75° for different inter-element spacing. Four antenna arrays were designed: two with 60 elements and two with 30 elements each, all operating from 9.3 GHz to 12.3 GHz providing a gain of 30 dBi and 20 dBi, respectively. To verify the performance, a 15-element sub-array having an overall size of 210 mm × 30 mm and achieving a total gain of 17 dBi was fabricated and tested. The proposed sub-array was fabricated using Rogers Duroid5880 (<i>εr</i> = 2.2 and h = 1.575 mm). It has been shown through comparison of radiation patterns that measured and simulation results are in good agreement.

Automatic modulation classification (AMC) has been identified to perform a key role to realize technologies such as cognitive radio, dynamic spectrum management, and interference identification that are arguably pivotal to practical SG communication networks. Random graphs (RGs) have been used to better understand graph behavior and to tackle combinatorial challenges in general. In this research article, a novel modulation classifier is presented to recognize M-Quadrature Amplitude Modulation (QAM) signals using random graph theory. The proposed method demonstrates improved recognition rates for multiple-input multiple-output (MIMO) and single-input single-output (SISO) systems. The proposed method has the advantage of not requiring channel/signal to noise ratio estimate or timing/frequency offset correction. Undirected RGs are constructed based on features, which are extracted by taking sparse Fourier transform (SFT) of the received signal. This method is based on the graph representation of the SFT of the 2nd, 4th, and 8th power of the received signal. The simulation results are also compared to existing state-of-the-art methodologies, revealing that the suggested methodology is superior.

In this paper, a trinotch band MIMO antenna is designed for upper and lower WLAN (5.1 GHz, 5.5 GHz) i.e., (802.11a/g/n/ac/ax) and satellite X-band (8.5 GHz). The placement of closely found notches at 5.1 GHz and 5.5 GHz is addressed by taking advantage from the placement of the same notch elements at appropriate distances from each other, to split single resonance into biresonances. Similarly, the third notch is produced at 8.5 GHz via a U-shaped slot added in the antenna. 2x1-MIMO antenna with notch bands is expected with better isolation by analysis of co-configurations and cross-configurations.

Unmanned air vehicle communication (UAV) systems have recently emerged as a quick, low-cost, and adaptable solution to numerous challenges in the next-generation wireless network. In particular, UAV systems have shown to be very useful in wireless communication applications with sudden traffic demands, network recovery, aerial relays, and edge computing. Meanwhile, non-orthogonal multiple access (NOMA) has been able to maximize the number of served users with the highest traffic capacity for future aerial systems in the literature. However, the study of joint optimization of UAV altitude, user pairing, and power allocation for the problem of capacity maximization requires further investigation. Thus, a capacity optimization problem for the NOMA aerial system is evaluated in this paper, considering the combination of convex and heuristic optimization techniques. The proposed algorithm is evaluated by using multiple heuristic techniques and deployment scenarios. The results prove the efficiency of the proposed NOMA scheme in comparison to the benchmark technique of orthogonal multiple access (OMA). Moreover, a comparative analysis of heuristic techniques for capacity optimization is also presented.