MEC-assisted Low Latency Communication for Autonomous Flight Control of 5G-Connected UAV

in MEC-assisted Low Latency Communication for Autonomous Flight Control of 5G-Connected UAV (in press)

Proliferating applications of unmanned aerial vehicles (UAVs) impose new service requirements, leading to several challenges. One of the crucial challenges in this vein is to facilitate the autonomous ... [more ▼]

Proliferating applications of unmanned aerial vehicles (UAVs) impose new service requirements, leading to several challenges. One of the crucial challenges in this vein is to facilitate the autonomous navigation of UAVs. Concretely, the UAV needs to individually process the visual data and subsequently plan its trajectories. Since the UAV has limited onboard storage constraints, its computational capabilities are often restricted and it may not be viable to process the data locally for trajectory planning. Alternatively, the UAV can send the visual inputs to the ground controller which, in turn, feeds back the command and control signals to the UAV for its safe navigation. However, this process may introduce some delays, which is not desirable for autonomous UAVs’ safe and reliable navigation. Thus, it is essential to devise techniques and approaches that can potentially offer low-latency solutions for planning the UAV’s flight. To this end, this paper analyzes a multi-access edge computing aided UAV and aims to minimize the latency of the task processing. More specifically, we propose an offloading strategy for a UAV by optimally designing the offloading parameter, local computational resources, and altitude of the UAV. The numerical and simulation results are presented to offer various design insights, and the benefits of the proposed strategy are also illustrated in contrast to the other baseline approaches. [less ▲]

Boosting Quantum Battery-Based IoT Gadgets via RF-Enabled Energy Harvesting

in Sensors (2022), 22(14), 1-19

The search for a highly portable and efficient supply of energy to run small-scale wireless gadgets has captivated the human race for the past few years. As a part of this quest, the idea of realizing a ... [more ▼]

The search for a highly portable and efficient supply of energy to run small-scale wireless gadgets has captivated the human race for the past few years. As a part of this quest, the idea of realizing a Quantum battery (QB) seems promising. Like any other practically tractable system, the design of QBs also involve several critical challenges. The main problem in this context is to ensure a lossless environment pertaining to the closed-system design of the QB, which is extremely difficult to realize in practice. Herein, we model and optimize various aspects of a Radio-Frequency (RF) Energy Harvesting (EH)-assisted, QB-enabled Internet-of-Things (IoT) system. Several RF-EH modules (in the form of micro- or nano-meter-sized integrated circuits (ICs)) are placed in parallel at the IoT receiver device, and the overall correspondingly harvested energy helps the involved Quantum sources achieve the so-called quasi-stable state. Concretely, the Quantum sources absorb the energy of photons that are emitted by a photon-emitting device controlled by a micro-controller, which also manages the overall harvested energy from the RF-EH ICs. To investigate the considered framework, we first minimize the total transmit power under the constraints on overall harvested energy and the number of RF-EH ICs at the QB-enabled wireless IoT device. Next, we optimize the number of RF-EH ICs, subject to the constraints on total transmit power and overall harvested energy. Correspondingly, we obtain suitable analytical solutions to the above-mentioned problems, respectively, and also cross-validate them using a non-linear program solver. The effectiveness of the proposed technique is reported in the form of numerical results, which are both theoretical and simulations based, by taking a range of operating system parameters into account. [less ▲]

Symbiotic Radio based Spectrum Sharing in Cooperative UAV-IRS Wireless Networks

in Proceedings of IEEE VTC2022-Spring (2022)

Ambient backscatter communication (AmBC) technology can potentially offer spectral- and energy-efficient solutions for future wireless systems. This paper proposes a novel design to facilitate the ... [more ▼]

Ambient backscatter communication (AmBC) technology can potentially offer spectral- and energy-efficient solutions for future wireless systems. This paper proposes a novel design to facilitate the spectrum sharing between a secondary system and a primary system based on the AmBC technique in intelligent reflective surface (IRS)-assisted unmanned aerial vehicle (UAV) networks. In particular, an IRS-aided UAV cooperatively relays the transmission from a terrestrial primary source node to a user equipment on the ground. On the other hand, leveraging on the AmBC technology, a terrestrial secondary node transmits its information to a terrestrial secondary receiver by modulating and backscattering the ambient relayed radio frequency (RF) signals from the UAV-IRS. The performance of such a system setup is analyzed by deriving the expressions of outage probability and ergodic spectral efficiency. Finally, we present the numerical results to provide useful insights into the system design and also validate the derived theoretical results using Monte Carlo simulations. [less ▲]

On the Exploration and Exploitation Trade-off in Cooperative Caching-enabled Networks

in IEEE WCNC 2021 proceeding (2021, April)

Edge-caching is considered as a promising solution to address network congestion and reduce delivery latency in the future by bringing the relevant contents close to users. In this context, the commonly ... [more ▼]

Edge-caching is considered as a promising solution to address network congestion and reduce delivery latency in the future by bringing the relevant contents close to users. In this context, the commonly used notion involves the storage of the most popular contents in the cache, while consequently increasing the cache hit ratio (CHR). In the majority of prior works, the content popularity is assumed to be perfectly known and often a priori. However, in reality, the content popularity has to be explored especially for uncertain contents, such as new entrants and fast varying items. In this paper, we develop a framework to analyze the joint exploration and exploitation trade-off by caching both popular and uncertain contents to enable more efficient content caching. Particularly, we formulate an optimization problem to maximize the trade-off between exploration and exploitation subject to the maximum storage capacity, guaranteed CHR, and back-haul energy budget constraints. Further, we solve the formulated mixed-integer combinatorial problem using branch-and-bound optimizer by relaxing the binary to box constraints. The superiority in performance of the proposed method over the state-of-the-art is demonstrated in terms of the CHR and back-haul energy on a realistic Movie-lens dataset. [less ▲]