A survey on UAV placement optimization for UAV-assisted communication in 5G and beyond networks

With the increase in capacity demands and the requirement of ubiquitous coverage in the fifth generation and beyond wireless communications networks, unmanned aerial vehicles (UAVs) have acquired a great attention owing to their outstanding characteristics over traditional base stations and relays. UAVs can be deployed faster and with much lower expenditure than ground base stations. In addition, UAVs can enhance the network performance thanks to their strong line-of-sight link conditions with their associated users and their dynamic nature that adapts to varying network conditions. Optimization of the UAV 3D locations in a UAV-assisted wireless communication network was considered in a large body of research as it is a critical design issue that greatly affects communication performance. Although the topic of UAV placement optimization was considered in few surveys, these surveys reviewed only a small part of the growing literature. In addition, the surveys were brief and did not discuss many important design issues such as the objectives of the optimization problem, the adopted solution techniques, the air-to-ground channel models, the transmission media for access and backhaul links, the limited energy nature of the UAV on-board batteries, co-channel interference and spectrum sharing, the interference management, etc. Motivated by the importance of the topic of UAV placement optimization as well as the need for a detailed review of its recent literature, we survey 100 of the recent research papers and provide in-depth discussion to fill the gaps found in the previous survey papers. The considered research papers are summarized and categorized to highlight the differences in the deployment scenario and system model, the optimization objectives and parameters, the proposed solution techniques, and the decision-making strategies and many other points. We also point to some of the existing challenges and potential research directions that have been considered in the surveyed literature and that requires to be considered     

Game theory-based radio resource allocation in NOMA vehicular communication networks supported by UAV

Vehicular communication networks are emerging as a promising technology to provide high-quality internet service such as entertainment for road users via infrastructure-to-vehicle (I2V) communication, and to guarantee road users’ safety via vehicle-to-vehicle (V2V) communication. Some technical issues that impact the performance of these networks are the lack of or poor communication paths between vehicles, and the limitation of radio resources. Unmanned aerial vehicles (UAVs) as promising solutions for supporting vehicular networks could provide communication coverage in hazardous environments and areas with no capacities for installation or maintenance of ground base stations (BSs). Also, non-orthogonal multiple access (NOMA) methods can improve spectral and energy efficiency and thereby allow more users to be connected to the desired network. In this paper, exploring the NOMA, we develop a scheme for optimum resource allocation in presence of a UAV that supports vehicular communications. Resource allocation for this scenario is formulated as a mixed-integer non-linear programming (MINLP) problem. Due to the high complexity of such problems, we propose two low-complexity near-optimal methods. First, we apply difference-of-concave-functions (DC) approximations to solve the problem in an iterative process. Next, we use Stackelberg game-based method for efficient solving, and then, closed-form expressions of optimal power allocations using KKT-conditions are derived. Simulations illustrate the effectiveness of the proposed scheme along with the Stackelberg game-based method.     

A survey on 5G: The next generation of mobile communication

The rapidly increasing number of mobile devices, voluminous data, and higher data rate are pushing to rethink the current generation of the cellular mobile communication. The next or fifth generation (5G) cellular networks are expected to meet high-end requirements. The 5G networks are broadly characterized by three unique features: ubiquitous connectivity, extremely low latency, and very high-speed data transfer. The 5G networks would provide novel architectures and technologies beyond state-of-the-art architectures and technologies. In this paper, our intent is to find an answer to the question: “what will be done by 5G and how?” We investigate and discuss serious limitations of the fourth generation (4G) cellular networks and corresponding new features of 5G networks. We identify challenges in 5G networks, new technologies for 5G networks, and present a comparative study of the proposed architectures that can be categorized on the basis of energy-efficiency, network hierarchy, and network types. Interestingly, the implementation issues, e.g., interference, QoS, handoff, security–privacy, channel access, and load balancing, hugely effect the realization of 5G networks. Furthermore, our illustrations highlight the feasibility of these models through an evaluation of existing real-experiments and testbeds.     

Joint UAVs’ Load Balancing and UEs’ Data Rate Fairness Optimization by Diffusion UAV Deployment Algorithm in Multi-UAV Networks

Unmanned aerial vehicles (UAVs) can be deployed as base stations (BSs) for emergency communications of user equipments (UEs) in 5G/6G networks. In multi-UAV communication networks, UAVs’ load balancing and UEs’ data rate fairness are two challenging problems and can be optimized by UAV deployment strategies. In this work, we found that these two problems are related by the same performance metric, which makes it possible to optimize the two problems simultaneously. To solve this joint optimization problem, we propose a UAV diffusion deployment algorithm based on the virtual force field method. Firstly, according to the unique performance metric, we define two new virtual forces, which are the UAV-UAV force and UE-UAV force defined by FU and FV, respectively. FV is the main contributor to load balancing and UEs’ data rate fairness, and FU contributes to fine tuning the UEs’ data rate fairness performance. Secondly, we propose a diffusion control stratedy to the update UAV-UAV force, which optimizes FV in a distributed manner. In this diffusion strategy, each UAV optimizes the local parameter by exchanging information with neighbor UAVs, which achieve global load balancing in a distributed manner. Thirdly, we adopt the successive convex optimization method to update FU, which is a non-convex problem. The resultant force of FV and FU is used to control the UAVs’ motion. Simulation results show that the proposed algorithm outperforms the baseline algorithm on UAVs’ load balancing and UEs’ data rate fairness.     

Mobility-aware coded caching in D2D communication networks

In this paper, we consider a cache-enable device-to-device (D2D) communication network with user mobility and design a mobility-aware coded caching scheme to exploit multicasting opportunities for reducing network traffic. In addition to the static cache memory that can be used to reap coded caching gains, we assign a dynamic cache memory to mobile users such that users who never meet can still exchange contents via relaying. We consider content exchange as an information flow among dynamic cache memories of mobile users and leverage network coding to reduce network traffic. Specifically, we transfer our storage and broadcast problem into a network coding problem. By solving the formulated network coding problem, we obtain a dynamic content replacement and broadcast strategy. Numerical results verify that our algorithm significantly outperforms the random and greedy algorithms in terms of the amount of broadcasting data, and the standard Ford–Fulkerson algorithm in terms of the successful decoding ratio.     

Analysis of fluctuations of antenna pattern in U-V2X communications

The third-generation partnership project (3GPP) defined several scenarios of vehicle-to-everything (V2X) networks such as vehicle-to-vehicle, vehicle-to-pedestrian, and vehicle-to-infrastructure. Unmanned aerial vehicles (UAVs) exploiting such scenarios for vehicular applications like vehicular-platooning, autonomous driving, and traffic management have shown improved networks’ performance in UAV-V2X (U-V2X) communications. This promising performance is typically obtained by considering high directional UAV antennas. However, the UAV vibration makes UAV antennas’ beam-width sensitive to UAV fluctuations which results in degrading the networks’ performance. Thus, in this paper, the performance of a U-V2X network in the presence of UAV fluctuations is investigated. The UAVs are modeled using an independent homogeneous Poisson Point Process and the vehicular-nodes are modeled using an independent Poisson Line Process. To this end, the association probability and success probability of various links such as vehicular-node connected to a UAV link, vehicular-node connected to a near-by vehicular-node link, and the overall U-V2X link are derived. In addition, the effect of different network settings such as the number of vehicular-nodes, UAVs, roads, and antennas is quantified. Moreover, the spectral efficiency of a U-V2X network is evaluated. Extensive simulations revealed that V2X networks facilitate UAVs and that for less dense areas with fewer roads, buildings, and crowds; UAVs provide more reliable links for connectivity than vehicular-nodes. Furthermore, it is also revealed that UAVs provide less reliable connection for V2X networks with larger UAV antenna fluctuations.     

Cryptography in Hierarchical Coded Caching: System Model and Cost Analysis

The idea behind network caching is to reduce network traffic during peak hours via transmitting frequently-requested content items to end users during off-peak hours. However, due to limited cache sizes and unpredictable access patterns, this might not totally eliminate the need for data transmission during peak hours. Coded caching was introduced to further reduce the peak hour traffic. The idea of coded caching is based on sending coded content which can be decoded in different ways by different users. This allows the server to service multiple requests by transmitting a single content item. Research works regarding coded caching traditionally adopt a simple network topology consisting of a single server, a single hub, a shared link connecting the server to the hub, and private links which connect the users to the hub. Building on the results of Sengupta et al. (IEEE Trans. Inf. Forensics Secur., 2015), we propose and evaluate a yet more complex system model that takes into consideration both throughput and security via combining the mentioned ideas. It is demonstrated that the achievable rates in the proposed model are within a constant multiplicative and additive gap with the minimum secure rates.     

A vision towards integrated 6G communication networks: Promising technologies,architecture, and use-cases

The evolution of the previous mobile communication generations has led to innovative goals of the Internet of Everything (IoE) in the 5G. However, addressing all IoE-associated problems in 5G is difficult and a long-term process. As the key performance indicators (KPIs) of the 5G services are highly diverse, it is an intimidating task to develop a single platform enabling all KPIs. The vision of next-generation 6G wireless communications lies not only in enhancing these targets but also in providing new services. Numerous extensively envisaged future services, including life-critical services and wireless brain–computer interactions, will be critically dependent on an instant, virtually unlimited wireless connectivity. In this direction, the 6G is envisioned to have primely five service objectives; further-enhanced mobile broadband (FeMBB), ultra-massive machine type communication (umMTC), extremely reliable low latency communication (ERLLC), long-distance and high-mobility communications (LDHMC), and extremely low-power communications (ELPC). The 3D global integration of the wireless communication networks is lacking in the 5G, which is targeted by the future 6G. In this paper, we present an exhaustive review of the 6G wireless communication network. We explore the various existing mobile communication generations concerning data rate, frequency band, bandwidth allotted, latency, and applications. We also highlight various current trends and issues in the 5G communication network, which drives research for the 6G communication network. Our focus is to provide a comprehensive survey on the future 6G. So, we explored the objectives and design principles for 6G. This paper highlights the key 6G technology drivers. This paper also proposes an architectural design for 6G. Moreover, we carry out a case-study of 6G architecture operational design and compare the result with previous generation architecture designs. Further, 6G envisioned open research challenges, research directions, and recent advancements are also highlighted in this paper. Furthermore, we discuss possible use-cases in terms of real-time interactions of the biological, physical, and digital world, and also how these use-cases are going to serve in 6G.     

Caching popularity-unknown contents for massive communication channels via deep Q-learning

In order to reduce the backhaul link pressure of wireless networks, edge caching technology has been regarded as a promising solution. However, with massive and dynamical communication connections, it is challenging to provide analytical caching solution to achieve the best performance, particularly when the requested contents are changing and their popularities are unknown. In this paper, we propose a deep Q-learning (DQN) method to address the issue of caching placement. Considering a content caching network containing multiple cooperating SBSs with unknown content popularity, we need to determine which content to cache and where to cache. Therefore, the learning network has to be designed for dual aims, one of which is to estimate the content popularities while the other is to assign contents to the proper channels. An elaborate DQN is proposed to make decisions to cache contents with limited storage space of base-station by considering channel conditions. Specifically, the content requests of users are first collected as one of the training samples of the learning network. Second, the channel state information for the massive links are estimated as the other training samples. Then, we train the network based on the proposed method thereby improving spectral efficiency of the entire system and reducing bit-error rate. Our major contribution is to contrive a caching strategy for enhanced performance in massive connection communications without knowing the content popularity. Numerical studies are performed to show that the proposed method acquires apparent performance gain over random caching in terms of average spectral efficiency and bit-error rate of the network.     

Mobile user forecast and power-law acceleration invariance of scale-free networks

This paper studies and predicts the number growth of China's mobile users by using the power-law regression. We find that the number growth of the mobile users follows a power law. Motivated by the data on the evolution of the mobile users, we consider scenarios of self-organization of accelerating growth networks into scale-free structures and propose a directed network model, in which the nodes grow following a power-law acceleration. The expressions for the transient and the stationary average degree distributions are obtained by using the Poisson process. This result shows that the model generates appropriate power-law connectivity distributions. Therefore, we find a power-law acceleration invariance of the scale-free networks. The numerical simulations of the models agree with the analytical results well.     

Time allocation improvement method for UAV-based wireless energy transfer cooperative mobile edge

Wireless power transfer (WPT) and mobile edge computing (MEC) are two advanced technologies that could improve the computing power and range of mobile devices. However, by integrating the unmanned aerial vehicle (UAV) into wireless powered MEC systems, wireless energy transfer will be susceptible to the “double near–far” effect. Therefore, in order to further overcome the influence of the “double near–far” effect, this paper considers the optimization of time slot allocation for UAV-assisted wireless powered cooperative MEC system, which includes an access point (UAV) and two mobile devices. The purpose of the study is to minimize the total transmission energy of the UAV while satisfying the delay and size of the computational tasks, so this paper proposed a 2:1:1 time-slot optimization allocation method. The method exploits the synergy of users so that the mobile device which is closer to the UAV acts as an offloading relay, by combining power and time slot optimization to minimize the total energy consumption of the UAV. Compared with the equal time slot scheme before the improvement, this method can not only utilize the wireless transmission energy to charge the mobile device for more time in the first period, but also can save the time of data transmission of the closer device in the third period, and it can enhance the rate of data transmission of the mobile devices at the same time. The results show that the task capacity of the system computed will be increased compared to the original scheme; the total transmission rate of the whole system is also improved by the same order of magnitude. The simulation results verify the effectiveness and reliability of the algorithm of the paper, and the comprehensive performance of the system can be maximized by the flexible offloading algorithm.     

Secured data transmissions in corporeal unmanned device to device using machine learning algorithm

Cyber–physical systems (CPS) for device-to-device (D2D) communications are gaining prominence in today’s sophisticated data transmission infrastructures. This research intends to develop a new model for UAV transmissions across distinct network nodes, which is necessary since an automatic monitoring system is required to enhance the current D2D application infrastructure. The real time significance of proposed UAV for D2D communications can be observed during data transmission state where individual data will have huge impact on maximizing the D2D security. Additionally, through the use of simulation, an exploratory persistence tool is offered for CPS networks with fully characterized energy issues. This UAV CPS paradigm is based on mobility nodes, which host concurrent systems and control algorithms. In sixth-generation networks, when there are no barriers and the collision rate is low and the connectivity is fast, the method is also feasible. Unmanned aerial vehicles (UAVs) can now cover great distances, even while encountering hazardous obstacles. When compared to the preexisting models, the simulated values for autonomous, collision, and parametric reliability are much better by an average of 87%. The proposed model, however, is shown to be highly independent and exhibits stable perceptual behaviour. The proposed UAV approach is optimal for real-time applications due to its potential for more secure operation via a variety of different communication modules.     

CEAR: A cooperation based energy aware reward scheme for next generation green cognitive radio networks

Cognitive Radio (CR) networks are envisioned as a key empowering technology of the fifth-generation (5G) wireless communication networks, which solves the major issues of 5G, like high-speed data transmission, seamless connectivity, and increased demand for mobile data. Another significant characteristic of the 5G network is green communications, as energy consumption from the communication field is predicted to rise remarkably by the year 2030. In this work, we are concerned about energy-related issues and propose a cooperation-based energy-aware reward scheme (CEAR) for next-generation green CR networks. The proposed CEAR scheme is based on the antenna and temporal diversity of the primary users (PUs). For providing the service to the PUs, the users of another network called cognitive users (CUs) work as a cooperative relay node, and, in return, they get more spectrum access opportunities as a reward from the primary network. The CUs with delay-tolerant data packets take a cooperative decision by recognizing the availability and traffic load of PUs, channel state information, and data transmission requirements. We utilize the optimal stopping protocol for solving the decision-making problem and use the backward induction method to obtain the optimal cooperative solution. The simulation results reveal notable enhancements in energy efficiency (EE) of CUs compared with other cooperative schemes. The proposed CEAR scheme is more energy-efficient for ultra-dense network deployment because results show that the CU’s EE, spectral efficiency (SE), and throughput improved with the increase of PUs.     

Enabling next generation small cells through femtorelays

Today’s society is driven by ever-growing information needs, which cause increased demand for ubiquitous and very high speed wireless communications. In search for the urgent need of improved coverage and capacity, cellular networks are currently undergoing a major transformation from an architecture comprised of thoroughly planned macrocell base stations (MBSs) to a much more heterogeneous architecture where the macrocell network is underlaid by one or several tiers of unevenly deployed small cells. However, this new set of technologies is not exempt of several challenges. Backhaul is still an unresolved issue, i.e. which is the best technology for the small cell to reach the core network. In the case of uncoordinated co-channel deployments where the macrocell and small cell tier share the spectrum (e.g. femtocells or metrocells), the interference is also a major problem. In this paper, a new concept and architecture called femtorelays is introduced as a novel solution for next generation small cell problems. A femtorelay is a small cell access point that enables improved cellular coverage within indoor environments while increasing the overall system capacity through spatial frequency reuse. Working as an open-access small cell, it provides dual-backhaul connectivity to the core network for registered and unregistered users. One of the backhaul connections is the internet-based, and the second one is the relay-based operating on the spectrum owned by the wireless carrier. The radio interference between the macrocell and the small cell is overcome by servicing the macrocell interfering users at the femtorelay. Unlike the traffic from subscribers, this traffic will be forwarded to the network through the relay-based backhaul. The internal architecture, the approach employed to make the technology fit in existing networks, and future evolution of the basic femtorelays for larger scenarios are also presented. Finally, performance results show the potential of this technology to outperform other existing solutions.     

Secure efficiency maximization for UAV-assisted mobile edge computing networks

This paper considers an unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) system, in which the intelligent reflecting surface (IRS) is applied to enhance the performance of the wireless transmission. The role of the UAV is twofold: (1) It is equipped with a MEC server and receives computing tasks from ground users and IRS at the same time; (2) It sends interference signals to counter the potential eavesdropper. Here, the UAV is working as a full duplex equipment, i.e., sending and receiving meanwhile. We comprehensively considered the flight speed constraint of the UAV, the total mission data constraint and the minimum security rate constraint of multiple users on the ground. The phase matrix constraints of IRS are also considered. Our system is dedicated to maximizing the efficiency of secure computing. The formulated problem is highly non-convex, we consider to propose an alternative optimization algorithm. The simulation results show that the proposed scheme not only achieves higher safe computing efficiency, but also has better performance in terms of energy consumption and security rate.     

High-performance networks for broadband multimedia services

Research and development in Advanced Communications technologies for Europe (RACE) played a key role in developing the crucial technology of Asynchronous Transfer Mode (ATM), which can provide a high-performance networking platform for broadband multimedia communications while allowing access to the existing worlds of voice, data, and broadcasting. The functionalities of high-performance networks in the user plane, control plane, and management planes to provide integral performance for the satisfaction of the users have been tested in accompanying measures such as the TEN-IBC projects of the European Commission. The European Union (EU) is now starting Advanced Communications Technologies and Services (ACTS)—the follow-up to RACE—as one of the major specific programs in the fourth research framework, involving 630 million ECUs of European Union contribution over four years. High-performance networking is a key development area within ACTS. It has a clear objective of enabling the deployment of a coherent and comprehensive trans-European information highway consisting of a terrestrial (optical), mobile, and satellite network infrastructure supporting broadband multimedia communications with maximum flexibility and a cost-effective evolution approach. Operational trials of high-performance networks involving different types of users, applications, network operators (national hosts), and the European ATM pilot network are planned as a part of the new ACTS projects. This article summarizes the projects involved and their activities toward the objectives of provisioning the high-performance network information highway for broadband multimedia applications.     

DRL-Assisted Resource Allocation for NOMA-MEC Offloading with Hybrid SIC

Multi-access edge computing (MEC) and non-orthogonal multiple access (NOMA) are regarded as promising technologies to improve the computation capability and offloading efficiency of mobile devices in the sixth-generation (6G) mobile system. This paper mainly focused on the hybrid NOMA-MEC system, where multiple users were first grouped into pairs, and users in each pair offloaded their tasks simultaneously by NOMA, then a dedicated time duration was scheduled to the more delay-tolerant user for uploading the remaining data by orthogonal multiple access (OMA). For the conventional NOMA uplink transmission, successive interference cancellation (SIC) was applied to decode the superposed signals successively according to the channel state information (CSI) or the quality of service (QoS) requirement. In this work, we integrated the hybrid SIC scheme, which dynamically adapts the SIC decoding order among all NOMA groups. To solve the user grouping problem, a deep reinforcement learning (DRL)-based algorithm was proposed to obtain a close-to-optimal user grouping policy. Moreover, we optimally minimized the offloading energy consumption by obtaining the closed-form solution to the resource allocation problem. Simulation results showed that the proposed algorithm converged fast, and the NOMA-MEC scheme outperformed the existing orthogonal multiple access (OMA) scheme.     

Two-stage deep learning-based hybrid precoder design for very large scale massive MIMO systems

Wireless networking is approaching a new era, which necessitates new frequency ranges and novel strategies. With recent circuit growth, communications over the Terahertz (THz) band is proving to be a viable option because of the tremendous bandwidth and low cost. On the other hand, THz signals suffer from significant direction loss, necessitating the use of precoding. In this paper, Deep Learning (DL) based precoding techniques for upcoming 6G networks were examined, along with their complexities. Based on the signal-to-noise ratio (SNR) and spectral efficiency (SE), the proposed DL-based precoding scheme is compared to traditional model-based precoding schemes. The proposed DL-based precoding technique is ideal for 6G networks, according to simulation results. Furthermore, the proposed DL-based precoding technique has lower computational complexity, making it suitable for parallel processing and high-speed data transmission.