Telecom, Volume 2, Issue 3 (September 2021) – 4 articles

This paper describes the development and evaluation of an on-body flexible antenna designed for an in-body application, as well as on-body communications at ISM and UWB frequency bands. The evaluation is performed via electromagnetic simulations using the Dassault Simulia CST Studio Suite. A planar tissue layer model, as well as a human voxel model from the human abdominal area, are used to study the antenna characteristics next to human tissues. Power flow analysis is presented to understand the power flow on the body surface as well as within the tissues. Simulation results show that this wearable flexible antenna is suitable for in-body communications in the intestinal area, e.g., for capsule endoscopy, in the industrial, scientific, and medical (ISM) band and at lower ultra-wideband (UWB). At higher frequencies, the antenna is suitable for on-body communications as well as in-body communications with lower propagation depth requirements. Additionally, an antenna prototype has been prepared and the antenna performance is verified with several on-body measurements. The measurement results show a good match with the simulation results. The novelty of the proposed antenna is a compact size and the flexible substrate material, which makes it feasible and practical for several different medical diagnosis and monitoring applications. Full article

Radio Frequency (RF) energy harvesting has been emerged as a potentially reliable method to replace the costly and difficult to maintain source of low-power wireless sensor networks. A plethora of dual-band rectifier designs has been proposed in the literature operating in various frequency bands. In this paper, a triple-band RF-to-DC rectifier that operates in the frequency bands of LoRaWAN, GSM-900, and WiFi 2.4 GHz is presented. The system is composed of an impedance-matching circuit, an RF-to-DC rectifier, that converts the ambient RF energy into DC voltage able to feed low-power devices, and an output load. The proposed system resonates at three different frequencies of 866 MHz, 948 MHz and 2423 MHz, which fall within the aforementioned frequency bands of interest. The feasible solution of the proposed system was based on a dual-band rectifier operating in the frequency bands of LoRaWAN and GSM-900. A series of shunt stubs was utilized in the initial design to form the feasible solution of the proposed system. The proposed triple-band rectifier was optimized using a powerful optimization algorithm, i.e., the genetic algorithm. The overall system exhibited improved characteristics compared to the initial design in terms of its resonance. Numerical results demonstrated that the overall system exhibited an efficiency of 81% with 3.23 V of the output voltage, for an input power of 0 dBm and a load of 13 kOhm. Full article

UAV path planning for remote sensing aims to find the best-fitted routes to complete a data collection mission. UAVs plan the routes and move through them to remotely collect environmental data from particular target zones by using sensory devices such as cameras. Route planning may utilize machine learning techniques to autonomously find/select cost-effective and/or best-fitted routes and achieve optimized results including: minimized data collection delay, reduced UAV power consumption, decreased flight traversed distance and maximized number of collected data samples. This paper utilizes a reinforcement learning technique (location and energy-aware Q-learning) to plan UAV routes for remote sensing in smart farms. Through this, the UAV avoids heuristically or blindly moving throughout a farm, but this takes the benefits of environment exploration–exploitation to explore the farm and find the shortest and most cost-effective paths into target locations with interesting data samples to collect. According to the simulation results, utilizing the Q-learning technique increases data collection robustness and reduces UAV resource consumption (e.g., power), traversed paths, and remote sensing latency as compared to two well-known benchmarks, IEMF and TBID, especially if the target locations are dense and crowded in a farm. Full article

The further growth of the Internet faces a crucial impediment related to the ossification problem. Network virtualization is a promising and emergent solution that has been introduced as a sophisticated diversifying attribute of the future network paradigm. However, there remain many issues standing in the way of its successful realization, such as the service provisioning efficiency in the network virtualization. Many approaches and schemes have been propounded to provide efficient resource management based on game theory. This paper presents a comprehensive overview of the existing game theory solutions designed for the different network virtualization environments. We propose a taxonomy for game-theoretical approaches classification. The scope of this survey is to provide a better understanding of the game-theoretical application for resource management in network virtualization. Thus, our inclusive classification considers the various game properties and characteristics as well as the purpose of applying the game theory to the virtualization context. Full article