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This article presents a compact six-element multiple-input multiple-output (MIMO) antenna for vehicle-to-vehicle (V2V) communications. The proposed structure is planar, having a dimension of $1.28\lambda _{0} \boldsymbol {\times } 2.04\lambda _{0}$ , where $\lambda _{0}$ is the wavelength at 25.5 GHz, resonating in n258 and n260 bands. The antenna is a modified rectangular patch designed to generate TM10 and TM02 modes, resulting in vertical and horizontal polarization at 25.5 GHz and 38 GHz. The measured bandwidth of the MIMO antenna is 800 MHz at the n258 band, i.e., 25.1-25.9 GHz, and 850 MHz at the n260 band, i.e., 37.75-38.6 GHz. The isolation between the elements is improved by incorporating a novel open-ended decoupling structure. It resulted in an isolation that surpass 20 dB at both bands. The antenna has a broadside radiation pattern with a maximum realized gain of 9 dBi and 7.2 dBi at 25.5 and 38 GHz, respectively. The antenna is validated for various diversity parameters such as envelope correlation coefficient, diversity gain, channel capacity loss, and mean effective gain. Also, the performance of the proposed antenna for V2V communication is analyzed for line-of-sight and non-line-of-sight conditions. The estimated channel capacity, path loss, and link budget for the above-said condition suggest that the antenna is suitable for V2V communications.

As the process of envisioning, researching, and strategizing for 6G communications has commenced, we present our vision on the role of semantic communications (SemCom) in the beyond 5G era. In the following discourse, we delve into the factors that may impede the progress of research and implementation of 6G with the objective of catering to the semantically enriched communication requirements of the 2030s. In addition, we proceed to establish the fundamental attributes of SemCom and engage in an examination of the requisite technological modalities. In order to bolster this overarching vision, we introduce a semantic networking architecture that encapsulates and characterizes various application scenarios of SemCom. Expanding on the concept of point-to-point SemCom systems the semantic networking architecture focuses on extracting and filtering goal specific semantic information at the source before transmitting signals. It also involves decoding and post processing semantics at the destination. What sets this networking architecture apart is its transformation into a multi-user distributed, edge-to-cloud network with deadline constraint traffic. Given its complexity, implementing such an architecture necessitates frameworks for extracting and representing knowledge theoretical models to predict and manage multiple time varying deadline/delay constrained traffic flows that may cause significant congestion in the network as well, as innovative metrics infused with semantics to measure performance while encapsulating its inherent relevance. Finally, we provide research considerations and future directions towards the integration of semantics in the forthcoming 6G wireless systems.

Semantic information representation in image-based communication often employs feature vectors, lacking interpretability and posing challenges for human comprehension. This paper addresses this challenge by exploring the reconstruction of original images in the context of American sign language (ASL) transmission. The conventional method involves decoding feature vectors through neural networks, introducing inefficiencies and complexities. To overcome these challenges, a novel system model for image-based semantic communications is presented, which utilizes a variant of the quadrature amplitude modulation (QAM) scheme, named 24-QAM. This modulation scheme is derived from the original 32-QAM constellation by removing 8 peripheral symbols and is proven capable of attaining superior error performance in ASL applications. Additionally, a semantic encoder based on a convolutional neural network (CNN) which effectively utilizes the ASL alphabet is presented. An original dataset is created by superimposing red-green-blue landmarks and key-points on top of the captured images; hence, enhancing the representation of hand posture. Finally, the training, testing, and communication performance of the proposed system is quantified through numerical results that highlight the achievable gains and trigger insightful discussions.

Modern wireless communication systems have undergone a radical change with the introduction of multiple-input multiple-output (MIMO) antennas, which provide increased channel capacity, fast data rates, and secure connections. To achieve real-time requirements, such antenna technology needs to have good gains, wider bandwidths, satisfactory radiation characteristics, and high isolation. This article presents an eight-element CPW-fed antenna for the 5G mid-band. The proposed antenna consists of eight symmetrical, modified circular monopole antennas with a connected CPW-fed ground plane that offers 24 dB isolation over the operating range. The antenna is further investigated in terms of the scattering parameters, and radiation characteristics under both the x and y-axis bending scenarios. The antenna holds a volume of 83 × 129 × 0.1 mm3 and covers a measured impedance bandwidth of 4.5–5.5 GHz (20%) with an average gain of 4 dBi throughout the operating band. MIMO diversity performance of the antenna is performed, and the antenna exhibits good performance suitable for MIMO applications. Furthermore, the channel capacity (CC) is estimated, and the antenna gives a value of 41.8–42.6 bps/Hz within the operating bandwidth, which is very close to an ideal 8 × 8 MIMO system. The antenna shows an excellent match between the simulated and measured findings.

A double-stub matching technique is used to design a dual-band monopole antenna at 28 and 38 GHz. The transmission line stubs represent the matching elements. The first matching network comprises series capacitive and inductive stubs, causing impedance matching at the 28 GHz band with a wide bandwidth. On the other hand, the second matching network has two shunt inductive stubs, generating resonance at 38 GHz. A Smith chart is utilized to predict the stub lengths. While incorporating their dimensions physically, some of the stub lengths are fine-tuned. The proposed antenna is compact with a profile of 0.75λ1×0.66λ1 (where λ1 is the free-space wavelength at 28 GHz). The measured bandwidths are 27–28.75 GHz and 36.20–42.43 GHz. Although the physical series capacitance of the first matching network is a slot in the ground plane, the antenna is able to achieve a good gain of 7 dBi in both bands. The proposed antenna has a compact design, good bandwidth and gain, making it a candidate for 5G wireless applications.

Abstract Terahertz (THz) band offers a vast amount of bandwidth and is envisioned to become a key enabler for a number of next generation wireless applications. In this direction, appropriate channel models, encapsulating the large and small-scale fading phenomena, need to be developed for both indoor and outdoor communications environments. The THz large-scale fading characteristics have been extensively investigated for both indoor and outdoor scenarios. The study of indoor THz small-scale fading has recently gained the momentum, while the small-scale fading of outdoor THz wireless channels has not yet been investigated. Motivated by this, this contribution introduces Gaussian mixture (GM) distribution as a suitable small-scale fading model for outdoor THz wireless links. In more detail, multiple outdoor THz wireless measurements recorded at different transceiver separation distance are fed to an expectation-maximization fitting algorithm, which returns the parameters of the GM probability density function. The fitting accuracy of the analytical GMs is evaluated in terms of the Kolmogorov-Smirnov, Kullback-Leibler (KL) and root-mean-square-error (RMSE) tests. The results reveal that as the number of mixtures increases the resulting analytical GMs perform a better fit to the empirical distributions. In addition, the KL and RMSE metrics indicate that the increase of mixtures beyond a particular number result to no significant improvement of the fitting accuracy. Finally, following the same approach as in the case of GM, we examine the suitability of mixture Gamma to capture the small-scale fading characteristics of the outdoor THz channels.

When fully implemented, sixth generation (6G) wireless systems will constitute intelligent wireless networks that enable not only ubiquitous communication but also high-accuracy localization services. They will be the driving force behind this transformation by introducing a new set of characteristics and service capabilities in which location will coexist with communication while sharing available resources. To that purpose, this survey investigates the envisioned applications and use cases of localization in future 6G wireless systems, while analyzing the impact of the major technology enablers. Afterwards, system models for millimeter wave, terahertz and visible light positioning that take into account both line-of-sight (LOS) and non-LOS channels are presented, while localization key performance indicators are revisited alongside mathematical definitions. Moreover, a detailed review of the state of the art conventional and learning-based localization techniques is conducted. Furthermore, the localization problem is formulated, the wireless system design is considered and the optimization of both is investigated. Finally, insights that arise from the presented analysis are summarized and used to highlight the most important future directions for localization in 6G wireless systems.

Long range wide area networks (LoRaWANs) have recently received intense scientific, research, and industrial interest. LoRaWANs play a pivotal role in Internet of Things (IoT) applications due to their capability to offer large coverage without sacrificing the energy efficiency and, thus the battery life, of end-devices. Most published contributions assume that LoRaWAN gateways (GWs) are plugged into the energy grid; thus, neglecting the network lifetime constraint due to power storage limitations. However, there are several verticals, including precision agriculture, forest protection, and others, in which it is difficult or even impossible to connect the GW to the power grid or to perform battery replacement at the end-devices. Consequently, maximizing the networks’ energy efficiency is expected to have a crucial impact on maximizing the network lifetime. Motivated by this, as well as the observation that the overall LoRaWAN network energy efficiency is significantly affected by the selected communication protocol, in this paper, we identify and discuss critical aspects and research challenges involved in the design of a LoRaWAN communication protocol, under an energy efficiency perspective. Building upon our findings, research directions towards a novel GreenLoRaWAN communication protocol are given, focusing on achieving energy efficiency, robustness, and scalability.

Next generation in-to-out-of body biomedical applications have adopted optical wireless communications (OWCs). However, by delving into the published literature, a gap is recognized in modeling the in-to-out-of channel, since most published contributions neglect the particularities of different types of tissues. In this paper, we present a novel pathloss and scattering models for in-to-out-of OWC links. Specifically, we derive extract analytical expressions that accurately describe the absorption of the five main tissues’ constituents, namely fat, water, melanin, and oxygenated and de-oxygenated blood. Moreover, we formulate a model for the calculation of the absorption coefficient of any generic biological tissue. Next, by incorporating the impact of scattering in the aforementioned model, we formulate the complete pathloss model. The developed model is verified by means of comparisons between the estimated pathloss and experimental measurements from independent research works. Finally, we illustrate the accuracy of the proposed model in estimating the optical properties of any generic tissue based on its constitution. The extracted channel model is expected to enable link budget analysis, performance analysis, and theoretical framework development, which will boost the design of optimized communication protocols for a plethora of biomedical applications.

This contribution focuses on extracting the theoretical framework for the assessment and evaluation of the joint effect of rain, beam misalignment and hardware imperfections at long-range outdoor terahertz (THz) wireless systems. In this direction, we first report an appropriate system model for outdoor THz wireless systems that take into account the impact of different design parameters, including antenna gain and transceivers hardware imperfections, atmospheric conditions, such as rain, and parameters, like temperature, humidity and pressure, as well as stochastic beam misalignment that can be caused by thermal expansion, dynamic wind loads and/or weak earthquakes. For this model, we extract novel closed-form expressions for the probability density and cumulative distribution functions of the THz wireless channel that captures the impact of geometric loss, beam misalignment and rain attenuation. We capitalized the aforementioned expressions by presenting closed-form formulas for the outage probability and achievable throughput of the system. Finally, we document an analytical policy that returns the optimal transmission spectral efficiency that maximizes the achievable throughput.

The emergence of next-generation Internet-of-Things (NG-IoT) applications introduces several challenges for the sixth-generation (6G) mobile networks, such as massive connectivity, increased network capacity, and extremely low-latency. To countermeasure the aforementioned challenges, ultra-dense networking has been widely identified as a possible solution. However, the dense deployment of base stations (BSs) is not always possible or cost-efficient. Drone-base-stations (DBSs) can facilitate network expansion and efficiently address the requirements of NG-IoT. In addition, due to their flexibility, they can provide on-demand connectivity in emergency scenarios or address temporary increases in network traffic. Nevertheless, the optimal placement of a DBS is not a straightforward task due to the limited energy reserves and the increased signal quality degradation in air-to-ground links. To this end, swarm intelligence approaches can be attractive solutions for determining the optimal position of the DBS in the three-dimensional (3D) space. In this work, we explore well-known swarm intelligence approaches, namely the Cuckoo Search (CS), Elephant Herd Optimization (EHO), Grey Wolf Optimization (GWO), Monarch Butterfly Optimization (MBO), Salp Swarm Algorithm (SSA), and Particle Swarm Optimization (PSO) and investigate their performance and efficiency in solving the aforementioned problem. In particular, we investigate the performance of three scenarios in the presence of different swarm intelligence approaches. Additionally, we carry out non-parametric statistical tests, namely the Friedman and Wilcoxon tests, in order to compare the different approaches.

Abstract As the wireless world moves towards the sixth generation (6G) era, the demand of supporting bandwidth-hungry applications in ultra-dense deployments becomes more and more imperative. Driven by this requirement, both the research and development communities have turned their attention into the terahertz (THz) band, where more than $$20\,{\text {GHz}}$$ 20 GHz of contiguous bandwidth can be exploited. As a result, novel wireless system and network architectures have been reported promising excellence in terms of reliability, massive connectivity, and data-rates. To assess their feasibility and efficiency, it is necessary to develop stochastic channel models that account for the small-scale fading. However, to the best of our knowledge, only initial steps have been so far performed. Motivated by this, this contribution is devoted to take a new look to fading in THz wireless systems, based on three sets of experimental measurements. In more detail, measurements, which have been conducted in a shopping mall, an airport check-in area, and an entrance hall of a university towards different time periods, are used to accurately model the fading distribution. Interestingly, our analysis shows that conventional distributions, such as Rayleigh, Rice, and Nakagami-m, lack fitting accuracy, whereas, the more general, yet tractable, $$\alpha $$ α – $$\mu $$ μ distribution has an almost-excellent fit. In order to quantify their fitting efficiency, we used two well-defined and widely-accepted tests, namely the Kolmogorov–Smirnov and the Kullback–Leibler tests. By accurately modeling the THz wireless channel, this work creates the fundamental tools of developing the theoretical and optimization frameworks for such systems and networks.

This work discusses the optimal reconfigurable intelligent surface placement in highly-directional millimeter wave links. In particular, we present a novel system model that takes into account the relationship between the transmission beam footprint at the RIS plane and the RIS size. Subsequently, based on the model we derive the end-to-end expression of the received signal power and, furthermore, provide approximate closed-form expressions in the case that the RIS size is either much smaller or at least equal to the transmission beam footprint. Moreover, building upon the expressions, we derive the optimal RIS placement that maximizes the end-to-end signal-to-noise ratio. Finally, we substantiate the analytical findings by means of simulations, which reveal important trends regarding the optimal RIS placement according to the system parameters.

The continuous positioning of a mobile user equipment (MU) in a prompt way is a fundamental requirement in several indoor applications related to ubiquitous computation, assisted living environments, and security/surveillance systems. Motivated by this fact, the current contribution reports a low-complexity visible light positioning (VLP) method suitable for indoor environments in the Big Data era. The proposed architecture consists of multiple light-emitting diodes (LEDs) as light sources and an MU equipped with a photodiode (PD). To guarantee higher spectral efficiency, the LEDs emit sinusoidal waveforms at slightly different predetermined frequencies. The light intensity received at the PD from every LED is continuously estimated after applying a short-time Fourier transformation. To this end, a grid-based numerical technique is proposed to recover the unknown MU position. Additionally, a closed-form solution is presented for the particular case of three LEDs that overrides the need for training points in the grid arrangement. Further, a method for handling noisy signals is proposed, based on averaging the calculated positions from densely overlapping received signals. Finally, a Kalman filter is employed as a post-processing precision improving tool. The proposed VLP efficiency is quantified through respective Monte Carlo simulations that allow the setting of different LED frequencies, received signal processing parameters, MU speed, and noise levels. The results reveal that the suggested approach is robust with significant tolerance in high ambient light levels, computationally efficient, and exhibits low positional error. Finally, to evaluate the performance improvements the new method introduces, we make comparisons against widely-used fingerprint approaches.

This paper presents a connectivity analysis of reconfigurable intelligent surface (RIS) assisted terahertz (THz) wireless systems. Specifically, a system model that accommodates the particularities of THz band links as well as the characteristics of the RIS is reported, accompanied by a novel general end-to-end (e2e) channel attenuation formula. Based on this formula, we derive a closed-form expression that returns the optimal phase shifting of each reflection unit (RU) of the RIS. Moreover, we provide a tractable e2e channel coefficient approximation that is suitable for analyzing the RIS-assisted THz wireless system performance. Building upon the aforementioned approximation as well as the assumption that the user equipments are located in random positions within a circular cluster, we present the theoretical framework that quantifies the coverage performance of the system under investigation. In more detail, we deliver a novel closed-form expression for the coverage probability that reveals that there exists a minimum transmission power that guarantees 100% coverage probability. Both the derived channel model as well as the coverage probability are validated through extensive simulations and reveal the importance of taking into account both the THz channel particularities and the RIS characteristics, when assessing the system's performance and designing RIS-assisted THz wireless systems.

In the present work, we investigate the impact of transceiver hardware imperfection on reconfigurable intelligent surface (RIS)-assisted wireless systems. In this direction, first, we present a general model that accommodates the impact of the transmitter (TX) and receiver (RX) radio frequency impairments. Next, we derive novel closed-form expressions for the instantaneous end-to-end signal-to-noise-plus-distortion-ratio (SNDR). Building upon these expressions, we extract an exact closed-form expression for the system's outage probability, which allows us not only to quantify RIS-assisted systems' outage performance but also reveals that the maximum allowed spectral efficiency of the transmission scheme is limited by the levels of the transceiver hardware imperfection. Likewise, a diversity analysis is provided. Moreover, in order to characterize the capacity of RIS-assisted systems, we report a new upper-bound for the ergodic capacity, which takes into account the number of the RIS's reflective units (RUs), the level of TX and RX hardware imperfection, as well as the transmission signal-to-noise-ratio (SNR). Finally, two insightful ergodic capacity ceilings are extracted for the high-SNR and high-RUs regimes. Our results highlight the importance of accurately modeling the transceiver hardware imperfection and reveals that they significantly limit the RIS-assisted wireless system performance.

In this paper, we provide the theoretical framework for the performance comparison of reconfigurable intelligent surfaces (RISs) and amplify-and-forward (AF) relaying wireless systems. In particular, after statistically characterizing the end-to-end (e2e) wireless channel coefficient of the RIS-assisted wireless system, in terms of probability density function (PDF) and cumulative density function (CDF), we extract novel closed-form expressions for the instantaneous and average e2e signal-to-noise ratio (SNR) for both the RIS-assisted and AF-relaying wireless systems. Building upon these expressions, we derive the diversity gain of the RIS-assisted wireless system as well as the outage probability (OP) and symbol error rate (SER) for a large variety of Gray-mapped modulation schemes of both systems under investigation. Additionally, the diversity order of the RIS-assisted wireless system is presented as well as the ergodic capacity (EC) of both the RIS-assisted and AF-relaying wireless systems. Likewise, high-SNR and high-number of metasurfaces (MS) approximations for the SER and EC for the RIS-assisted wireless system are reported. Finally, for the sake of completeness, the special case in which the RIS is equipped with only one MS is also investigated. For this case, the instantaneous and average e2e SNR are derived, as well as the OP, SER and EC. Our analysis is verified through respective Monte Carlo simulations, which reveal the accuracy of the presented theoretical framework. Moreover, our results highlight that, in general, RIS-assisted wireless systems outperform the corresponding AF-relaying ones in terms of average SNR, OP, SER and EC.

Over the recent years, an increasing amount of research effort has been directed toward the development and optimization of optical cell stimulation (OCS) techniques, while electrical cell stimulation (ECS) has been perfected. This article investigates the existing ECS and OCS methods from a communication perspective and, after summarizing the main breakthroughs in both fields, introduces a novel system model that treats the stimulation as a communication process. Additionally, we discuss the main particularities of ECS and OCS models and conduct a comparative analysis that quantifies the performance of the aforementioned methods based on suitable engineering metrics such as average latency, power consumption, transmission distance, as well as stimulation frequency, pulse width, and amplitude. Finally, future research directions emerge from the provided insightful discussion.

With the vision to transform the current wireless network into a cyber-physical intelligent platform capable of supporting bandwidth-hungry and latency-constrained applications, both academia and industry turned their attention to the development of artificial intelligence (AI) enabled terahertz (THz) wireless networks. In this article, we list the applications of THz wireless systems in the beyond fifth generation era and discuss their enabling technologies and fundamental challenges that can be formulated as AI problems. These problems are related to physical, medium/multiple access control, radio resource management, network and transport layer. For each of them, we report the AI approaches, which have been recognized as possible solutions in the technical literature, emphasizing their principles and limitations. Finally, we provide an insightful discussion concerning research gaps and possible future directions.

Access to clean water is vital to human health, communities’ development, and economic prosperity. Nowadays, more than 10% of the global population lacks access to clean water. This has created the so-called “water crisis” and set, as a key goal for communities, the protection and optimization of water usage. In this direction, technological concepts, like internet-of-things (IoT) and artificial intelligence (AI) assisted recommendation, which enables real-time monitoring and efficient exploitation of water resources, have been identified as fundamental pillars of the solution. This inspired the design, development, and testing of several breakthrough concepts in this domain; however, to the best of our knowledge, none of them lies in real-time intelligent exploitation of mixing clean and recycled water for crops irrigation. Motivated by this, in this paper, we present a holistic next-generation IoT approach, namely AUGEIAS, for optimal clean and treated wastewater usage in precision agriculture. In more detail, we present AUGEIAS architecture and explain its features and functionalities. Moreover, the AUGEIAS intelligent mechanisms that allow accurate crops water demand and weather prediction, as well as optimization, are documented. Finally, the front end of AUGEIAS platform is presented.

This paper is focused on providing the analytical framework for the quantification and evaluation of the joint effect of misalignment fading and hardware imperfections in the presence of multipath fading at terahertz (THz) wireless fiber extenders. In this context, we present the appropriate system model that incorporates the different operation, design, and environmental parameters. In more detail, it takes into account the transceivers antenna gains, the operation frequency, the distance between the transmitter (TX) and the receiver (RX), the environmental conditions, i.e., temperature, humidity, and pressure, the spatial jitter between the TX and RX antennas that results to antennas misalignment, the level of transceivers' hardware imperfections, and the stochastic characteristics of the wireless channel. Based on this model, we analyze and quantify the joint impact of misalignment and multipath fading by providing novel closed-form expressions for the probability and cumulative density functions of the composite channel. Moreover, we derive exact closed-form expressions for the outage probability for both cases of ideal and non-ideal radio frequency (RF) front-end. In addition, in order to quantify the detrimental effect of misalignment fading, we analytically obtain the outage probability in the absence of misalignment cases for both cases of ideal and non-ideal RF front-end. In addition, we extract the novel closed-form expressions for the ergodic capacity for the case of the ideal RF front-end and tight upper bounds for both the cases of ideal and non-ideal RF front-end. Finally, an insightful ergodic capacity ceiling for the non-ideal RF front-end case is provided.

The development of timelapse videos for the investigation of growing microbial colonies has gained increasing interest due to its low cost and complexity implementation. In the present study, a simple experimental setup is proposed for periodic snapshot acquisition of a petri dish cultivating a fungus of the genus Candida SPP, thus creating a timelapse video. A computational algorithm, based on image processing techniques is proposed for estimating the microbial population and for extracting the experimental population curves, showing the time evolution of the population of microbes at any region of the dish. Likewise, a novel mathematical population evolution modeling approach is reported, which is based on the logistic function (LF). Parameter estimation of the aforementioned model is described and visually assessed, in comparison with the conventional and widely-used LF method. The effect of the image analysis parameterization is also highlighted. Our experiments take into account different area sizes, i.e., the number of pixels in the neighborhood, to generate population curves and calculate the model parameters. Our results reveal that, as the size of the area increases, the curve becomes smoother, the signal-to-noise-ratio increases and the estimation of model parameters becomes more accurate.

In this paper, we assess the signal quality of the out-body to in-body optical communication link, which can be used as a fundamental enabler of novel biomedical appliances, such as medical implants, as well as biological and chemical components monitoring. In particular, we present a mathematical understanding of the transdermal system, which takes into account the optical channel characteristics, the integrated area limitations of the in-body unit, the transceivers’ pointing errors and the particularities of the optical units. Moreover, to accommodate the propagation characteristics, we present a novel simplified, but accurate, transdermal path-gain model. Finally, we extract low-complexity closed-form expressions for the instantaneous and average signal to noise ratio of the transdermal optical link (TOL). Numerical and simulation results are provided for several insightful scenarios and reveal that pointing errors can significantly affect the reliability and effectiveness of the TOL; hence, it should be taken into account in the analysis and design of such systems.