Recently, with the users' growing demand for communication rate and capacity in wireless networks, Unmanned Aerial Vehicles (UAVs) have attracted widespread attention due to their mobility, flexibility, and robust line-of-sight communication links. By equipping UAVs with multiple communication payloads, we can construct an aerial wireless network with three-dimensional coverage. However, due to the limitations of UAV onboard energy and communication resources, the lifetime and performance of UAV-assisted wireless networks are significantly constrained. This paper mainly focuses on equipping UAVs with mobile base stations to enhance wireless communication coverage and capacity. We propose a Joint Optimization of 3D Trajectory and Resource Allocation (JOTRA) scheme to maximize energy efficiency in complex scenarios with multi-user mobility and diverse requirements (e.g., UAV-assisted post-disaster search and rescue). Specifically, we apply Dinkelbach's iterative method and Block Coordinate Descent (BCD) method to solve the formulated multivariable and non-convex maximization problem. The algorithm's convergence has been analyzed. According to the simulation, the proposed algorithm can converge faster while maximizing energy efficiency in complex wireless communication scenarios.

Although the integration between Unmanned Aerial Vehicles (UAVs) and Radio Access Network (RAN) applications is envisioned to enable a variety of new use cases and services, several practical aspects related to autonomous operations over cellular systems are still largely unexplored due to difficulties in testing and validating such integration in the real world. In this paper, we bridge the gap between simulation and real-world applications by introducing a new framework that combines real-world robotic controllers and 5th generation (5G) cellular stacks with channel and flight simulation. We consider a holistic approach where we use ArduPilot as the flight controller and OpenAirInterface (OAI) and srsRAN as the 5G cellular stacks to provide a unified solution for developing and experimenting with UAV s for cellular applications. We utilize ArduPilot Software-in-the-Loop (SITL) to simulate and control the mobility of UAVs, while OAI-RFSim and srsRAN are used to model channel conditions. Our framework is particularly useful for developing data-driven solutions that require (i) a large amount of data collected under realistic operational conditions to learn effective control policies; and (ii) a sandbox and safe testing environment that enables exploration of the action space. By addressing a UAV coverage problem and developing a greedy heuristic, we demonstrate how our framework can be used to create and test algorithms in a simulated environment, showcasing its potential as a bridge to real-world applications.

As the fifth generation (5G) of mobile communication systems are becoming a commercial reality, this paper attempts to investigate the reliability and propagation latency performance of UAV-assisted cellular systems that caters to a scalable, flexible and on-demand solution for differentiated 5G services. The reliability performance of the considered system is evaluated in terms of block error rates (BLER) along with the propagation latency for three classes of services: Ultra Reliable Low Latency Communications (URLLC), enhanced Mobile Broadband (eMBB), and massive Machine Type Communications (mMTC). Considering the impact of fading and shadowing, the closed-form approximate expressions for BLER and propagation latency are evaluated over Rician shadowed fading with various shadowing scenarios. The numerical results reveal important insights related to the achievable reliability performance for three different services under given fading and shadowing severity. Specifically, The tightness of the ap-proximation presented is validated through the Monte-Carlo simulations.

We consider a multi-hop cooperative network inside a factory environment with the number of devices which are placed uniformly in a strip-shaped manner. the randomly deployed multiple intermediate relay nodes serve source and destination using the opportunistic large array (OLA) cooperative communication protocol for packet transmission. However, the simultaneous transmission of packets results in interference when the multiple transmissions occur simultaneously in the multihop wireless network. This paper analyzes the impact of such interference in the considered factory automation scenario from the Industry 4.0 perspective. We analyze the system performance in terms of the outage probability, success rate and latency with various network parameters. Moreover, the key insights are obtained related to the impact of packet insertion rate and tiers of interference on the system performance. Specifically, it is observed that the success rate of considered cooperative OLA network significantly increases due to the spatial diversity gains. However, the interference of multiple packets transmission severely affects the network success rate.

In this article, we investigate the nonlinear energy harvesting (EH)-based unmanned aerial vehicle (UAV)-assisted full-duplex (FD) Internet of Things (IoT) network with infinite and finite blocklength (FBL) codes. The reliability performance of the considered network, having two half-duplex UAVs and an FD IoT device, is analyzed in terms of the block error rate (BLER) with given ultrareliable and low-latency communication constraints. With the assumption of the combined effect of fading and shadowing, the closed-form expressions for BLER and network goodput are obtained over the Rician shadowed fading channels considering various shadowing scenarios, EH receiver architecture, IoT device mobility, inter-UAV interference, and self-interference (SI) cancelation capabilities at FD IoT device. The obtained results over the Rician shadowed fading for the nonlinear EH receiver architecture are also compared with the linear EH and over the Rician fading channels. The numerical results reveal important observations related to the impact of time-selective fading channels with imperfect channel state information, shadowing severity in the suburban areas, SI cancelation capabilities, blocklength, and the number of channel uses on the reliability performance of the UAV-assisted FD IoT network. Furthermore, the tightness of the approximation presented is verified through the Monte-Carlo simulations.

A reconfigurable intelligent surface (RIS)-assisted wireless communication system with non-linear energy harvesting (EH) and ultra-reliable low-latency constraints is considered for its possible applications in industrial automation. A distant data-center (DC) communicates with the multiple destination machines with the help of a full-duplex (FD) server machine (SM) and RIS. Assuming the deficiency of enough transmission power at the FD-SM, the SM is considered in the near vicinity of the destinations in the industry to forward the data received from the distant DC. The reception at SM is assisted by the RIS and a non-linear hybrid power-time splitting (PTS) based EH receiver architecture is adopted to extend the lifespan of SM, thus increasing network lifetime. The scheduling of multiple destinations is done by SM based on the considered selection criteria namely, random (RND) scheduling, absolute (ABS) channel-power-based (CPB) scheduling and normalized (NRM) CPB scheduling. The end-to-end performance of the considered FD RIS-assisted network is analyzed, and the expressions for the block error rate (BLER) for all scheduling schemes are derived. Moreover, the effects of number of RIS elements, packet size, channel uses on the system performance are analyzed for the considered ultra-reliable and low-latency communication (URLLC) network. The scheduling fairness of all the scheduling schemes is also analyzed to study the performance-fairness trade-off. The derived analytical results are verified through Monte-Carlo simulations.

In this paper, a multi-user full-duplex (FD) two-way relaying system with decode-and-forward protocol is considered where all the nodes are assumed to be mobile and to have FD abilities. The residual self-interference (RSI) at each node is modeled as a Rician distributed random variable and the effect of mobility is incorporated by adopting the first order auto-regressive (AR) model. Then, the signal-to-interference-plus-noise-ratio (SINR) based scheduling schemes namely random scheduling, absolute channel power-based (CPB) scheduling, hybrid scheduling, and normalized CPB scheduling, are modified and the user pair selection is carried out on the basis of instantaneous channel statistics. The performance of the considered framework is analyzed for the modified scheduling schemes in terms of error probability and average rate. Next, the closed-form expressions for the symbol error probability (SEP) and average rate are derived for independent and non-identically distributed Rayleigh fading channels. Also, the numerical analysis highlighting the impact of user mobility and imperfect channel estimation on the scheduling strategies, fairness is presented. Furthermore, the impacts of the degree of traffic asymmetry, scheduling fairness, user mobility, channel estimation errors and RSI on the system performance are investigated. Numerical results are validated through the Monte Carlo simulations.