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The gantry crane, positioned atop the bridge pier cap for the installation of Super-T girders, is a specialized construction unit within the bridge construction industry. The article presents a summary of research results investigating dynamic parameters and their influence on the operation of gantry cranes with assembled structures on the cap of bridge piers, serving the installation of Super-T beams in two scenarios: lifting with pre-stressed cable and moving with load (Super-T beam). To examine the dynamic parameters affecting the operation of the gantry crane, the authors first constructed a dynamic model. Subsequently, the influential parameters were determined, and the Matlab Simulink software was employed to develop a survey model corresponding to different values of each parameter and under various working conditions of the gantry crane. This process aimed to identify patterns and unfavorable values of these parameters affecting the operation of the gantry crane. The research results revealed that in both scenarios of lifting with pre-stressed cable and moving with a load (loading), factors such as lifting speed (Vn), stiffness of the main steel structure (S3), conversion stiffness of the lifting cable (S1), oscillation mass of the main structure (m3), wind load acting on the beam (Pg2), wind load acting on the main steel structure (Pg1), and stiffness of the hanging cable (S1) significantly influence the operation of the gantry crane. The survey results also indicated reasonable values for these influential factors during the operation of the gantry crane. The obtained research results can serve as a basis for computational design problems and effective utilization of gantry cranes with assembled structures on the cap of bridge piers for the installation of Super-T beams. Through analysis and simulation using Matlab-Simulink software, specific data on cable tension, main structure acceleration, and structural deformation were collected. The results emphasize the importance of limiting the lifting speed to 2 m/min to ensure stability during cable tensioned lifting and restricting the crane's moving speed to 7.85 m/min to maintain safety and performance when moving loads with tensioned cables. [ABSTRACT FROM AUTHOR]

Summary: In practice, hardware impairments (HIs) often exist in wireless devices, especially in low‐cost device systems. However, previous reports usually ignored HIs due to the computational complexity in mathematical derivations, particularly in millimeter‐wave (mmWave) communications. This article proposes the usage of transmit antenna selection (TAS) and multiple reconfigurable intelligent surfaces (RISs) to address HIs in mmWave communications. In particular, TAS is utilized at the source to increase the received signal power at the destination and reduce the effects of HIs. Multiple channel gains from RISs are combined with the classical source‐destination channel gain at the destination. The symbol error probability (SEP) expression of the mmWave communications with TAS and RISs under the effects of HIs (shortened as the TAS‐RISs‐HIs communications) is formulated over Nakagami‐ m channels and verified through Monte Carlo simulations. The effects of HIs on the SEP of TAS‐RISs‐HIs communications are demonstrated through numerical illustrations. Specifically, the SEP of the TAS‐RISs‐HIs communications is significantly higher than the SEP of the ideal hardware communications with TAS and RISs, especially in the high transmit power regime. As a result, ignoring HIs when evaluating the SEP of the mmWave communications can result in some inappropriate conclusions. Moreover, the joint and separate advantages of TAS and RISs are thoroughly analyzed when comparing the SEPs in the cases with and without TAS, with and without RISs. [ABSTRACT FROM AUTHOR]

This paper studies the joint impact of simultaneous wireless information and power transfer (SWIPT) and nonorthogonal multiple access (NOMA) to the cooperative relay (CoR) network where direct links exist. Over Nakagami-m fading environments, the near users employ decode-and-forward (DF) and energy harvesting (EH) to assist the transmission from the source to the far users. Exploiting the time-switching protocol (TSP) and power-splitting protocol (PSP) to the CoR-based NOMA system, analytical results for the outage probability are derived, and the corresponding throughput is obtained. Comparative results show that the PSP outperforms the TSP at low transmit power, while at high-transmit-power regime, the TSP provides similar performance as the PSP. [ABSTRACT FROM AUTHOR]

Summary In this article, we exploit the huge advantages of full‐duplex (FD) transmission, nonorthogonal multiple access (NOMA) technique, unmanned aerial vehicle (UAV), and millimeter‐wave (mmWave) communications in an Internet of things (IoT) sensor network. Specifically, the UAV operates as a FD amplify‐and‐forward (AF) relay to aid communications between an IoT sensor and multiple NOMA users. Moreover, the FD‐UAV (FDU) adopts both fixed and variable gains. We obtain exact expressions of outage probability (OP) and throughput of IoT‐FDU‐NOMA‐mmWave network with fixed and variable gains at FDU over Nakagami‐m$$ m $$ fading channels. Numerical illustrations clearly show that the OP and throughput performance of the IoT‐FDU‐NOMA‐mmWave network with variable gain are considerably higher than those with fixed gain. Since mmWave bands are used, the OP and throughput of the IoT‐FDU‐NOMA‐mmWave network are greatly affected by carrier frequency and communication distances. Consequently, when the carrier frequency or/and the distances between the IoT sensor and the users increase, the transmit power of the IoT sensor and the FDU should be increased to maintain the network performance. On the other hand, the effects of residual loop interference (LI) induced by FD transmission are remarkable. Thus, more efforts to reduce the residual LI power have to be continuously performed. Moreover, the specific impacts of the key parameters such as fading order m$$ m $$, the positions of the FDU, and data rates are clarified. More importantly, in practice, according to the fixed gain or the variable gain that is used, we can locate the position of FDU to achieve the best performance for the IoT‐FDU‐NOMA‐mmWave network. [ABSTRACT FROM AUTHOR]