Recent Advances in Applications and Performance Improvement Schemes in Wireless Communication

1. Introduction

To this date, the Fifth Generation (5G) of mobile communications has been deployed and has opened a great number of opportunities by increasing transmission rates (partialy through the use of MIMO systems), decreasing latency, providing the amount of bandwidth required for video services, Virual and Augmented Reality applications, and social media and providing a solid ground for the massive implementation of the Internet of Things (IoT), which we believe is still in its initial phases of development. Indeed, the IoT will operate autonomously and with a high degree of intelligence, recognizing different users, routines, and special events in the lives of device owners, and communicating among different devices to provide seamless operation in people’s everyday lives. Furthermore, devices used by users will also communicate among themselves and with devices from cities, highways, rivers, and forests, enabling the monitoring of ecosystems and the prevention of flooding and fires, among many other applications. To this day, the IoT operates mainly from a user’s point of view, requiring manual configuration of many devices across various applications. Communication among devices and between different companies is extremely limited, not to mention communication with public devices.

From the works presented in this issue, we can confidently see that the design of wireless communications will require the use of one or more of these aspects in the near future:

• Energy consumption (energy harvesting, clean energies);
• Security guarantees (robust to attacks, privacy guarantees);
• Machine learning;
• Physical Layer improvements (antennas, modulation, and coding schemes) to reduce latency and increase transmission rates;
• IoT and social media services.

As such, the IoT is only one of many areas where communication systems must propose, analyze, and design new protocols, schemes, and systems on the path to the Sixth Generation (6G) of mobile communication systems. There are still many challenges that must be overcome to introduce the 6G seamlessly in the coming years, as detailed in one paper on this Special Issue, contribution 1. For instance, providing high-precision placement and high-speed transmission is crucial for various applications, such as autonomous vehicles, Drone-aided solutions in wireless networks, and event detection in Wireless Sensor Networks (WSNs), among others, where the use of Artificial Intelligence (AI) algorithms surely will play a prominent role. To this end, the use of Cloud and Edge resources will be required, as well as intelligent offloading schemes that allow for reducing energy consumption and increasing data processing efficiency, which is still an open research topic. We invite the reader to study the points provided in contribution 1 for an in-depth analysis of the challenges and open questions regarding the introduction of 6G mobile communications, as well as identifying new applications and services that are not yet implemented in our day-to-day digital life, such as digital twins. Additionally, regarding the physical layer, another paper presents invaluable details on the design of rectenas, antennas, and rectifiers for reduced and sustainable energy usage in communication systems, with a focus on Energy Harvesting (EH) techniques.

Not only are the physical layer challenges discussed in this issue, but many works also focus on providing a comprehensive view of the main challenges and technological issues that need to be solved before the introduction of 6G mobile communication systems. Issues such as security services, efficient resource allocation and utilization, including the use of Integrated Sensing and Communication Systems (ISACs), Unmanned Aerial Vehicles (UAVs), Device-to-Device (D2D) communications, Edge and Cloud computing, among others. From this, we believe that after a thorough read of this issue, the reader will have a clear idea of what has been done in recent years in these different areas and what is still required to investigate, and what are some of the issues that have not been tackled but will be required on the road to the development of the 6G. Hence, for a graduate student initiating their research or for a senior researcher with a clear and solid research trajectory seeking new opportunities to apply their expertise, this issue will be useful in providing a general vision of where telecommunication systems are headed.

We now discuss in detail the main works presented in this issue, which range from details in the physical layer, where coding, modulation, and waveforms are studied and analyzed. We then delve into MIMO systems, which, although primarily belonging to the physical layer, require special attention since they will be the fundamental technology that enables increased transmission rates and bandwidth required in 6G systems. We then present works on D2D and UAV-assisted systems, which significantly extend the coverage and capacity of classical communication systems, and also provide new services and applications that were previously unavailable. Then, we present works on advancements in sensing (the primary function of IoT devices). Next, we present advances in Edge and Cloud computing. We end this brief editorial with a discussion on energy harvesting schemes that will allow battery-reduced or even battery-free communication systems in the future. Some relevant conclusions are presented at the end.

2. Physical Layer: Antennas, Modulation, Coding, and Waveforms

In this special issue, a paper detailing the waveforms (shape, structure, and frequency) used in cellular systems from 0G to 6G and beyond provides an interesting overview of how wireless systems have evolved from purely analog systems to modern and future digital systems as stated in contribution 2. Aside from the parameters, the waveforms have a significant impact on key performance issues, including capacity, coverage, power consumption, battery life, spectral efficiency, bandwidth utilization, and resistance to interference and noise.

Waveforms in cellular networks are a major component in the operation and service provision in modern communication systems. By studying the evolution of waveforms that have been used, we will provide invaluable information for designing and developing new and improved waveforms in the future, considering that modulation schemes are designed in part by the waveform of the signals. Additionally, it is essential to note that as generations in mobile communications systems evolve, the primary services provided by these systems also evolve accordingly. As such, in future systems, it is highly relevant to consider the primary services and applications when designing and proposing well-suited waveforms to achieve optimal network performance.

The insights and lessons learned from this path in cellular networks can also be applied to other systems, such as the IoT, P2P networks, and many others, by considering parameters including the communication radio, transmission rate, and packet size, among others. As such, this paper is relevant not only in cellular networks but in all wireless communication systems. Of particular interest in this context is the use of terahertz communications, Visible Light Communications, ultramassive MIMO, and the use of Artificial Intelligence as a core technology at the core of 6G. Additionally, the use of sound is of great interest for providing additional security guarantees as detailed in contribution 3. These new transmission techniques would require drastically different waveforms and modulation schemes to implement practical/operational systems. Additionally, the rise of Integrated Sensing and Communication systems (which is discussed in another paper of this issue) is of major interest to modern applications, such as autonomous driving and the navigation of swarms of drones. This paper also describes emerging waveforms, such as orthogonal chirp division multiplexing, affine frequency division multiplexing, orthogonal time frequency space, and index modulation, and provides the fundamentals of each of these techniques to put them in context for beyond 6G systems.

Another issue addressed in this Special Issue is the use of clean energy to power up nodes in the IoT context. As such, the work presented in contribution 4 shows opportunities in the Energy Harvesting field, focusing on materials, AI techniques, hybrid EH, and novel architectures to obtain energy from RF sources, such that researchers working in this area can optimize the use of battery-free (and battery-based pollution-free) future communication systems.

In the context of Smart Cities and IoT, an interesting area is underwater communications. To monitor pollution in rivers, lakes, or dams, or to prevent flooding, nodes can be placed in strategic locations submerged in water, forcing communications in a denser medium than air, where most wireless communications are usually designed. In contribution 5, the authors propose efficient coding schemes for wireless underwater communications. To this end, they first characterized the noise in underwater communications and then proposed the use of polar coding to reduce the Bit Error Rate (BER). Conventional coding schemes are no longer adequate, as underwater channels suffer from severe multipath interference, high Doppler shifts, strong fading, low data rates, and limited bandwidth.

These papers open some opportunities to design WSNs located underwater, or the use of aquatic robots and swarms of aquatic robots to perform multiple tasks by having a reliable communication system in these conditions. For instance, consider a scenario where rivers are monitored with these sensor networks, such that in case of abnormal conditions (a rise in the water level or an unexpected change in the flow direction or velocity), nodes communicate among other nodes in the water or even with nodes on land to alert of possible emergency events. In such cases, nodes can be placed in remote areas, such as the middle of forests or mountains, where communication with central disaster management offices is difficult or even impossible. As such, nodes can perform long-range communications underwater through multiple multi-hop transmissions within the river, allowing them to communicate with a node on land that can then transmit to surrounding UAVs or vehicles passing by. Although this scenario may seem futuristic or impractical today, many of the works presented in this special issue tackle critical technical details to make it possible in the near future.

3. MIMO Systems

Although MIMO systems are part of the physical layer, they are of special relevance to future communication systems, so we present the works in this area in a separate section. MIMO systems are required for high data rate systems, and also, in the field of Energy Harvesting, for simultaneously transmitting information and recharging nodes in the IoT context, as mentioned and detailed in contribution 4.

Specifically, MIMO systems use multiple antennas for both transmission and reception. The authors in contribution 6 propose an antenna design for the 28 GHz band, featuring gains of 13 dBi and a bandwidth of 1 GHz. The development of MIMO systems is necessary to increase data rates, particularly in IoT, autonomous driving, and Smart City applications. Antenna design at 28 GHz is particularly challenging due to high path loss and atmospheric attenuation. In this regard, the authors design a four-port MIMO structure with reduced size by carefully selecting the element spacing and employing a decoupling strategy that reduces interference among the individual antennas.

Signal detection in MIMO systems is not straightforward due to the complexity of the channels. In this regard, the authors in contribution 7 present a Deep Neural Network (DNN) for detecting signals in MIMO systems, comparing their proposal to traditional methods such as maximum likelihood, minimum mean square error, and zero-forcing methods. They prove that the use of DNNs achieves better results in terms of computational complexity and accuracy. However, they also identify some issues that have to be studied in future designs, not only for DNN-based algorithms, but for the use of Machine Learning in MIMO system design in general, such as the use of activation functions for low-power communication systems, and the use of hybrid schemes integrating other AI methods with traditional methods.

Another work in MIMO systems is presented in contribution 8, where the authors propose a transceiver design for a multiuser MIMO full-duplex amplify-and-forward relay downlink communication system. This is performed using an imperfect loop interference cancellation. Also, an iterative method is developed to solve the optimization problem. This work focuses on relay systems where data is sent from the transmitter to the relay and then from the relay to the receiver, with the objective of amplifying the signal. This is of particular interest in long-range distance communications or in environments with high noise and interference, typical in big cities.

4. Device-to-Device Communicartions

With the exponential growth of IoT infrastructure, the need for connected devices has also become increasingly relevant as the road to 6G implementation progresses. Even though 5G has been an important issue to study, to this date, many devices are still connected to a central unit, which poses some security risks and loss of efficiency (increased latency and energy consumption). Additionally, some applications rely absolutely on efficient D2D communications, such as connected vehicles and UAV swarms. Hence, the relevance of proposing novel schemes to enable direct connections among neighboring devices, such as the one proposed in contribution 9, where a low-energy consumption scheme is proposed. Their proposal allows nodes to determine whether direct communication or communication through the cellular network is advised, given the current system conditions. Specifically, the authors investigate a bandwidth-efficient scheme that enables nodes to communicate using licensed or unlicensed spectrum in either an underlay or overlay architecture. In this regard, the authors are concerned with power control and interference mitigation in the resource allocation scheme, utilizing machine learning algorithms to predict future scenarios in complex systems. In particular, they propose the use of a Reinforcement Learning algorithm to achieve adequate power management, selecting the instantaneous power transmission of each device and thereby reducing interference in the cellular system.

5. UAV-Assited Communications

Another relevant open research area is the use of UAVs to aid wireless systems, such as WSNs and Cellular Networks, as UAVs can provide temporal bandwidth to increase capacity and coverage, while also reducing energy consumption. To this end, the work presented in contribution 10 proposes a channel model for ground-to-UAV applications in the metropolitan context in Indian cities. The proposed model considers both LoS (Line-of-Sight) and NLoS (Non-Line-of-Sight) conditions, which are commonly found in these UAV-aided systems. The need for such models becomes increasingly relevant in modern and future communication systems, providing high-bandwidth and low-latency services in the context of smart cities, including autonomous driving and intelligent sensing services. Such models must consider the elevation angle, shadowing, and path loss phenomena, as well as horizontal and vertical polarization, among other parameters. Of particular interest is the work presented in contribution 10, where the model is compared to real propagation conditions, demonstrating an adequate match. The use of UAVs in this context represents a cost- and energy-efficient alternative to implementing fixed Base Stations, where traffic is not sufficiently high to justify the use of mobile channels that are continuously available, or where traffic only increases at specific events, such as zones close to stadiums or public places. Additionally, the use of swarms of UAVs, either for public figure displays (which will replace the use of fireworks in the near future) or to aid wireless systems, will definitely require communication models such as the one presented in this paper.

Although this work is primarily focused on Indian cities, where suburban, urban, dense urban, and high-rise urban environments coexist, it is clear that many other cities worldwide could benefit from such propagation models by adjusting for their specific conditions of shadowing and path loss. Especially considering that communication models for low-altitude devices have been largely overlooked.

6. Sensing

A relatively new research area in modern communication systems is Integrated Sensing and Communication Systems (ISAC), which enhances efficiency by combining two of the most energy-intensive and resource-consuming tasks into a single procedure: sensing and data transmission. To this end, the work developed in contribution 11 proposes the use of Physical Layer Abstraction (PLA) to simplify the system-level simulations, replacing link-level simulations. By using the PLA method, it is possible to determine the Signal-to-Noise Ratio (SNR) in the wireless channel, thereby enabling the acquisition of distance, positioning, and detection information. The paper details these algorithms under two different conditions: low and high noise, which in turn produce low and high errors. The authors study the system under an OFDM technique, clearly illustrating the number of symbols required to achieve an adequate performance.

In this regard, the development of ISAC mechanisms and the work presented in contribution 11, in particular, will be of great relevance for many services and applications in the near future, such as autonomous vehicles, swarms of UAVs to aid wireless systems, and energy reduction in WSNs, among others. All of these, in the context of Smart Cities, will require the implementation of thousands or millions of nodes that must perform both sensing and communication tasks, which have been performed separately to date.

In this sense, the paper in contribution 3 presents a work where sensing is performed by nodes in certain regions where cyber-attacks are expected. For instance, to monitor restricted natural areas where logging or hunting is prohibited, but illegal trespassers are equipped with jamming devices and have previously disabled the WSN by interfering with the alarm transmission of nodes. Since most nodes communicate using the RF spectrum, it is expected that the jamming attacks would occur in this part of the electromagnetic spectrum. To prevent the disabling of event reporting, the authors propose a technique that utilizes the sounds of native bird species as a means of communication. Specifically, the authors propose inserting the monitoring data into the prerecorded sounds of birds commonly found in the region in a way that transmits information using sound that is not distorted, allowing it to pass undetected to people on the ground, even people familiar with the specific bird’s sounds of the region. Specifically, the work presented in contribution 3 develops a covert channel utilizing steganography techniques to conceal information within sound waves. To this end, a robust system is analyzed and designed, where nodes must be turned on and off according to the specific nature of the natural sounds of birds. A teletraffic analysis is developed to carefully select the system’s parameters to achieve a high throughput WSN. This proposal focuses on utilizing the sound of birds, but it could be extended to provide robust WSNs against jamming attacks using other types of sounds. For instance, in big cities, the sounds of vehicles or construction equipment can be used to conceal data transmissions.

7. EDGE and Cloud Computing

EDGE and Cloud computing are a major area that was primarily viewed as a computational field. However, in recent years, telecommunication systems have benefited from the advantages posed by having higher processing and storage capabilities. In particular, the use of EDGE computing provides low-latency and increased bandwidth services close to users, which are invaluable for many modern and future systems. However, integrating EDGE services into 5G and 6G systems requires detailed design. Specifically, in 6G systems, where increased data rates and the number of connected devices are expected, EDGE capabilities would enable hyper-connected and autonomous operation in a scalable manner. In contribution 12, the authors outline the benefits of utilizing EDGE computing in mobile networks, including enhanced Quality of Service (QoS), reduced latency, and decreased computational load. First, the work in contribution 12 provides details on the integration of 5G mobile networks with Multi-Access Edge Computing (MEC), analyzing the software components and their architecture, and then it performs an integration between MEC and 5G technology, which is validated in a virtualized environment with a 5G core using a Kubernetes cluster.

8. Reduced and Sustainable Energy Consumption and Harvesting

With the exponential growth of autonomous nodes in the IoT context, the use of alternative energy sources, other than batteries that could leak hazardous and toxic substances into natural zones or in residential homes, is of extreme importance. It is crucial to study the use of alternative and clean sources to power millions of devices for various applications. As such, Energy Harvesting is a key technology that can deliver a solution in present and future communication systems, avoiding frequent battery changes, potential leaks, and service interruptions due to energy shortages in the nodes. Building on this, in this Special Issue, some techniques and methods are studied and identified in contribution 4. Energy Harvesting is of special interest, given the possibility of wirelessly recharging from already present signals, such as those from TV, WiFi, and cellular systems’ waves, which can be found pervasively in modern cities. As mentioned in this work, EH requires an antenna, a rectifier circuit that converts RF signals into DC voltage, and a storage unit. As such, in this work, the reader will find recent innovations in EH techniques and architectures, highlighting the main challenges and issues hindering the massive adoption of this technology in IoT applications, such as rectenna design, power management circuits, the use of AI algorithms, and materials’ properties that have to be improved for an efficient transformation of RF signals, making an emphasis on smart cities and biomedial applications, where certain wearables that report critical hrlath-related data must continuously operate.

The authors of this work first describe the main components of an EH system, including techniques for efficiently storing energy from RF signals. They then provide a general overview of recent advancements and applications, placing the reader in context and enabling a clear understanding of the direction of this research topic. From this, it is then easy to understand the main challenges and limitations of this technology, which are discussed in detail in Section 9 of the paper.

9. Conclusions and Discussion

After a detailed review of this special issue, the reader will gain a clear understanding of how communication systems have evolved to reach the already implemented 5G mobile communication systems in various areas, including waveforms and energy harvesting techniques. Then, the reader will have a clear understanding of a specific proposal to enhance system performance, such as advances in the areas of MEC, UAVs, ISAC, and MIMO. Throughout this special issue, the reader will also identify the use of Machine Learning algorithms in the communication system context, which will be increasingly used in the years to come to optimize various operational and design issues.

We would like to extend our sincere gratitude to all the authors and the editorial team who made this special issue possible, as reflected in the publication of these papers.