Telecom, Volume 2, Issue 2 (June 2021) – 6 articles

The Jaya optimization algorithm is a simple, fast, robust, and powerful population-based stochastic metaheuristic that in recent years has been successfully applied in a variety of global optimization problems in various application fields. The essential idea of the Jaya algorithm is that the searching agents try to change their positions toward the best obtained solution by avoiding the worst solution at every generation. The important difference between Jaya and other metaheuristics is that Jaya does not require the tuning of its control, except for the maximum number of iterations and population size parameters. However, like other metaheuristics, Jaya still has the dilemma of an appropriate tradeoff between its exploration and exploitation abilities during the evolution process. To enhance the convergence performance of the standard Jaya algorithm in the continuous domain, chaotic Jaya (CJ) frameworks based on chaotic sequences are proposed in this paper. In order to obtain the performance of the standard Jaya and CJ approaches, tests related to electromagnetic optimization using two different benchmark problems are conducted. These are the Loney’s solenoid benchmark and a brushless direct current (DC) motor benchmark. Both problems are realized to evaluate the effectiveness and convergence rate. The simulation results and comparisons with the standard Jaya algorithm demonstrated that the performance of the CJ approaches based on Chebyshev-type chaotic mapping and logistic mapping can be competitive results in terms of both efficiency and solution quality in electromagnetics optimization. Full article

The design of a smart electromagnetic (EM) environment for next-generation wireless communication systems is addressed in this work. The proposed approach aims at synthesizing a desired EM field distribution over a target region, where the receiving terminals are located, through the opportunistic exploitation of the complex scattering interactions between the EM field generated by a reconfigurable primary source and the objects/scatterers present in the environment, which behave as application-driven passive metastructures. The effectiveness and the potentialities of the proposed design methodology are assessed with a proof-of-concept numerical result obtained by means of advanced and reliable simulation tools. Full article

Mobile networks are expected to face major problems such as low network capacity, high latency, and limited resources but are expected to provide seamless connectivity in the foreseeable future. It is crucial to deliver an adequate level of performance for network services and to ensure an acceptable quality of services for mobile users. Intelligent mobility management is a promising solution to deal with the aforementioned issues. In this context, modeling user mobility behaviour is of great importance in order to extract valuable information about user behaviours and to meet their demands. In this paper, we propose a hybrid user mobility prediction approach for handover management in mobile networks. First, we extract user mobility patterns using a mobility model based on statistical models and deep learning algorithms. We deploy a vector autoregression (VAR) model and a gated recurrent unit (GRU) to predict the future trajectory of a user. We then reduce the number of unnecessary handover signaling messages and optimize the handover procedure using the obtained prediction results. We deploy mobility data generated from real users to conduct our experiments. The simulation results show that the proposed VAR-GRU mobility model has the lowest prediction error in comparison with existing methods. Moreover, we investigate the handover processing and transmission costs for predictive and non-predictive scenarios. It is shown that the handover-related costs effectively decrease when we obtain a prediction in the network. For vertical handover, processing cost and transmission cost improve, respectively, by 57.14% and 28.01%. Full article

In recent years, propagation channel characteristics have been effectively used in several applications such as motion sensing and position detection. Considerable attention has been paid to channel-sounding methods that are easy to utilize using low-cost devices. This paper presents a device-free indoor location estimation method using the spatio-temporal features of radio propagation channels using a 2.4 GHz-band three-by-three multiple-input-multiple-output (MIMO) channel sounder developed using commodity wireless local area network (WLAN). The measurement results demonstrated a reasonable performance of the proposed method with a small number of antennas. Full article

Recent developments in both optical wireless communication (OWC) systems and implanted medical devices (IMDs) have introduced transdermal optical wireless (TOW) technology as a viable candidate for extremely high-speed in-body to out-of-body wireless data transmissions, which are growing in demand for many vital biomedical applications, including telemetry with medical implants, health monitoring, neural recording and prostheses. Nevertheless, this emerging communication modality is primarily hindered by skin-induced attenuation of the propagating signal bit carrier along with its stochastic misalignment-induced fading. Thus, by considering a typical modulated retroreflective (MRR) TOW system with spatial diversity and optimal combining (OC) for signal reception in this work, we focus, for the first time in the MRR TOW literature, on the stochastic nature of generalized pointing errors with non-zero boresight (NZB). Specifically, under these circumstances, novel analytical mathematical expressions were derived for the total average bit error rate (BER) of various system configurations. Their results revealed significant outage performance enhancements when spatial diversity was utilized. Moreover, taking into consideration the total transdermal pathloss along with the effects of stochastic NZB pointing errors, the critical average signal-to-noise ratio (SNR) metric was evaluated for typical power spectral-density values. Full article

Traditional education, particularly at a university level is not necessarily very engaging. Educational escape rooms are a recent game based learning approach which combines team based problem solving with a story-line and cryptic clues. In this paper, we apply the concept of educational escape rooms to the telecommunications engineering classroom by creating a series of two separate scenarios, each containing three puzzles. Our evaluation is based on survey results from telecommunication experts which suggest that this will be an engaging and challenging tool for teaching telecommunications engineering. Although educational escape rooms are rapidly being deployed in education, these are the first educational escape rooms that specifically addresses the field of telecommunications engineering. Full article