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5. Enhanced IoT Batteryless D2D Communications Using Reconfigurable Intelligent Surfaces

Author

Ahmed, Shakil, Selim, Mohamed Y., and Kamal, Ahmed E.

Subjects
FOS: Electrical engineering, electronic engineering, information engineering, Systems and Control (eess.SY), Electrical Engineering and Systems Science - Systems and Control
Abstract

Recent research on reconfigurable intelligent surfaces (RIS) suggests that the RIS panel, containing passive elements, enhances channel performance for the internet of things (IoT) systems by reflecting transmitted signals to the receiving nodes. This paper investigates RIS panel assisted-wireless network to instigate minimal base station (BS) transmit power in the form of energy harvesting for batteryless IoT sensors to maximize bits transmission in the significant multi-path environment, such as urban areas. Batteryless IoT sensors harvest energy through the RIS panel from external sources, such as from nearby BS radio frequency (RF) signal in the first optimal time frame, for a given time frame. The bits transmission among IoT sensors, followed by a device-to-device (D2D) communications protocol, is maximized using harvested energy in the final optimal time frame. The bits transmission is at least equal to the number of bits sampled by the IoT sensor. We formulate a non-convex mixed-integer non-linear problem to maximize the number of communicating bits subject to energy harvesting from BS RF signals, RIS panel energy consumption, and required time. We propose a robust solution by presenting an iterative algorithm. We perform extensive simulation results based on the 3GPP Urban Micro channel model to validate our model.

Published
2022

6. X-haul Outage Compensation in 5G/6G Using Reconfigurable Intelligent Surfaces

Author

Selim, Mohamed Y., Kamal, Ahmed E., and Nait-Abdesselam, Farid

Subjects
FOS: Computer and information sciences, Emerging Technologies (cs.ET), Information Theory (cs.IT), Computer Science - Information Theory, Computer Science - Emerging Technologies
Abstract

5G network operators consider the dense deployment of small base-stations (SBSs) to increase network coverage and capacity. Hence, operators face the challenge of X-hauling, i.e., backhauling or fronthauling, their traffic to the core network. Also, SBSs densification will increase the possibility of failure of these X-haul links. To cope with this problem, an X-haul outage compensation scheme with the assistance of Reconfigurable Intelligent Surfaces (RIS) is proposed to mitigate or at least alleviate the effect of X-haul failure. The RIS is a newly adopted technology that is able to improve the performance of wireless networks. In this paper, we present and evaluate an X-haul outage compensation scheme based on placing a number of RIS panels in pre-planned locations to mitigate the effect of X-haul failure. This evaluation is done using frequencies below and beyond 6 GHz. Based on our analytical results, the proposed RIS scheme shows that placing a sufficient number of RIS elements in proximity to the failed SBS under certain conditions can help acquire the same X-haul rate before the occurrence of the failure. Also, we show that for high X-haul spectral density, the RIS-assisted transmission with a certain number of elements can be more energy-efficient than line-of-sight and non-line-of-sight transmissions. Finally, the system's energy efficiency is addressed with and without RIS, and the optimal number of RIS reflecting elements is derived., This paper was submitted to a conference May 2022

Published
2022

26. Spatial and Temporal Management of Cellular HetNets with Multiple Solar Powered Drones.

Author

Alsharoa, Ahmad, Ghazzai, Hakim, Kadri, Abdullah, and Kamal, Ahmed E.

Subjects
LINEAR programming, ENERGY management, INTEGER programming, ENERGY consumption, LINEAR orderings, CELL phone systems
Abstract

This paper proposes an energy management framework for cellular heterogeneous networks (HetNets) supported by dynamic solar powered drones. A HetNet composed of a macrocell base station (BS), micro cell BSs, and drone small cell BSs are deployed to serve the networks’ subscribers. The drones can land at pre-planned locations defined by the mobile operator and at the macrocell BS site where they can charge their batteries. The objective of the framework is to jointly determine the optimal trips of the drones and the MBSs that can be safely turned off in order to minimize the total energy consumption of the network. This is done while considering the cells’ capacities and the minimum receiving power guaranteeing successful communications. To do so, an integer linear programming problem is formulated and optimally solved for three cases based on the knowledge level about future renewable energy statistics of the drones. A low complex relaxed solution is also developed. Its performances are shown to be close to those of the optimal solutions. However, the gap increases as the network becomes more congested. Numerical results investigate the performance of the proposed drone-based approach and show notable improvements in terms of energy saving and network capacity. [ABSTRACT FROM AUTHOR]

Published
2020
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