Exploiting Backscatter-Aided Relay Communications with Hybrid Access Model in Device-to-Device Networks

© 2015 IEEE. The backscatter and active RF radios can complement each other and bring potential performance gain. In this paper, we envision a dual-mode radio structure that allows each device to make smart decisions on mode switch between backscatter communications (i.e., the passive mode) or RF communications (i.e., the active mode), according to the channel and energy conditions. The flexibility in mode switching also makes it more complicated for transmission control and network optimization. To exploit the radio diversity gain, we consider a wireless powered device-to-device network of hybrid radios and propose a sum throughput maximization by jointly optimizing energy beamforming and transmission scheduling in two radio modes. We further exploit the user cooperation gain by allowing the passive radios to relay for the active radios. As such, the sum throughput maximization is reformulated into a non-convex. We first present a sub-optimal algorithm based on successive convex approximation, which optimizes the relays' reflection coefficients by iteratively solving semi-definite programs. We also devise a set of heuristic algorithms with reduced computational complexity, which are shown to significantly improve the sum throughput and amenable for practical implementation

Towards 6G-Enabled Internet of Things with IRS-Empowered Backscatter-Assisted WPCNs

Wireless powered communication networks (WPCNs) are expected to play a key role in the forthcoming 6G systems. However, they have not yet found their way to large-scale practical implementations due to their inherent shortcomings such as the low efficiency of energy transfer and information transmission. In this thesis, we aim to study the integration of WPCNs with other novel technologies of backscatter communication and intelligent reflecting surface (IRS) to enhance the performance and improve the efficiency of these networks so as to prepare them for being seamlessly fitted into the 6G ecosystem. We first study the incorporation of backscatter communication into conventional WPCNs and investigate the performance of backscatter-assisted WPCNs (BS-WPCNs). We then study the inclusion of IRS into the WPCN environment, where an IRS is used for improving the performance of energy transfer and information transmission in WPCNs. After that, the simultaneous integration of backscatter communication and IRS technologies into WPCNs is investigated, where the analyses show the significant performance gains that can be achieved by this integration

A Comprehensive Overview on 5G-and-Beyond Networks with UAVs: From Communications to Sensing and Intelligence

Due to the advancements in cellular technologies and the dense deployment of cellular infrastructure, integrating unmanned aerial vehicles (UAVs) into the fifth-generation (5G) and beyond cellular networks is a promising solution to achieve safe UAV operation as well as enabling diversified applications with mission-specific payload data delivery. In particular, 5G networks need to support three typical usage scenarios, namely, enhanced mobile broadband (eMBB), ultra-reliable low-latency communications (URLLC), and massive machine-type communications (mMTC). On the one hand, UAVs can be leveraged as cost-effective aerial platforms to provide ground users with enhanced communication services by exploiting their high cruising altitude and controllable maneuverability in three-dimensional (3D) space. On the other hand, providing such communication services simultaneously for both UAV and ground users poses new challenges due to the need for ubiquitous 3D signal coverage as well as the strong air-ground network interference. Besides the requirement of high-performance wireless communications, the ability to support effective and efficient sensing as well as network intelligence is also essential for 5G-and-beyond 3D heterogeneous wireless networks with coexisting aerial and ground users. In this paper, we provide a comprehensive overview of the latest research efforts on integrating UAVs into cellular networks, with an emphasis on how to exploit advanced techniques (e.g., intelligent reflecting surface, short packet transmission, energy harvesting, joint communication and radar sensing, and edge intelligence) to meet the diversified service requirements of next-generation wireless systems. Moreover, we highlight important directions for further investigation in future work.Comment: Accepted by IEEE JSA

Intelligent-Reflecting-Surface-Assisted UAV Communications for 6G Networks

In 6th-Generation (6G) mobile networks, Intelligent Reflective Surfaces (IRSs) and Unmanned Aerial Vehicles (UAVs) have emerged as promising technologies to address the coverage difficulties and resource constraints faced by terrestrial networks. UAVs, with their mobility and low costs, offer diverse connectivity options for mobile users and a novel deployment paradigm for 6G networks. However, the limited battery capacity of UAVs, dynamic and unpredictable channel environments, and communication resource constraints result in poor performance of traditional UAV-based networks. IRSs can not only reconstruct the wireless environment in a unique way, but also achieve wireless network relay in a cost-effective manner. Hence, it receives significant attention as a promising solution to solve the above challenges. In this article, we conduct a comprehensive survey on IRS-assisted UAV communications for 6G networks. First, primary issues, key technologies, and application scenarios of IRS-assisted UAV communications for 6G networks are introduced. Then, we put forward specific solutions to the issues of IRS-assisted UAV communications. Finally, we discuss some open issues and future research directions to guide researchers in related fields

A Prospective Look: Key Enabling Technologies, Applications and Open Research Topics in 6G Networks

The fifth generation (5G) mobile networks are envisaged to enable a plethora of breakthrough advancements in wireless technologies, providing support of a diverse set of services over a single platform. While the deployment of 5G systems is scaling up globally, it is time to look ahead for beyond 5G systems. This is driven by the emerging societal trends, calling for fully automated systems and intelligent services supported by extended reality and haptics communications. To accommodate the stringent requirements of their prospective applications, which are data-driven and defined by extremely low-latency, ultra-reliable, fast and seamless wireless connectivity, research initiatives are currently focusing on a progressive roadmap towards the sixth generation (6G) networks. In this article, we shed light on some of the major enabling technologies for 6G, which are expected to revolutionize the fundamental architectures of cellular networks and provide multiple homogeneous artificial intelligence-empowered services, including distributed communications, control, computing, sensing, and energy, from its core to its end nodes. Particularly, this paper aims to answer several 6G framework related questions: What are the driving forces for the development of 6G? How will the enabling technologies of 6G differ from those in 5G? What kind of applications and interactions will they support which would not be supported by 5G? We address these questions by presenting a profound study of the 6G vision and outlining five of its disruptive technologies, i.e., terahertz communications, programmable metasurfaces, drone-based communications, backscatter communications and tactile internet, as well as their potential applications. Then, by leveraging the state-of-the-art literature surveyed for each technology, we discuss their requirements, key challenges, and open research problems

Energy Efficient Resource Allocation for Wireless Powered Communication Networks

The exponential growth of smart wireless devices has put much pressure on the spectral efficiency and energy efficiency (EE) of the Internet of things (IoT) networks and wireless sensor networks. In order to support energy constrained wireless devices, wireless powered communication networks (WPCN) have been proposed based on different wireless powered transmission (WPT) technologies, e.g., simultaneous wireless information and power transfer (SWIPT), harvest then transmit (HTT) and backscatter communication (BackCom). We note that energy-efficient resource allocation schemes need to be tailored to the different WPT technologies used in WPCNs. In this thesis (including four papers), we classify WPCNs into three types according to the way of information transmission: active transmission, passive transmission and hybrid transmission, and present energy-efficient resource allocation schemes for them in different scenarios of WPCNs. In active transmission-based WPCNs, a radio frequency (RF) power source, e.g., a base station (BS) or a power beacon (PB), sends an RF signal to a transmitter, which harvests energy from the received RF signal through its energy harvesting (EH) circuit and generates its own RF signal to carry information to a receiver. In Paper I, we consider a SWIPT-enabled device-to-device (D2D) underlaid network, where a D2D receiver decodes information and harvests energy from its associated D2D transmitter simultaneously via its SWIPT circuit, and propose to maximize the sum EE of all D2D links by optimizing the spectrum resource and power allocation, and the power splitting ratio of each D2D device based on a non-linear EH model. We find that the number of SWIPT-enabled D2D links that maximize the sum EE is limited by the EH circuit sensitivity, especially when the D2D communication distance is long. In passive transmission-based WPCNs, an RF power source sends an RF signal to a backscatter device (BD), which backscatters parts of the incident RF signal to a receiver and harvests energy from the rest of the incident RF signal to support the backscatter circuit. In Paper II, we propose to ensure the max-min EE fairness among the backscatter links by jointly optimizing the PB transmission power and the backscatter reflection coefficients. Our results show that the proposed max-min EE resource allocation scheme is more effective when the throughput requirement of the BDs is lower and the channel power gain difference among different PB-to-BD links is smaller. In Paper III, we propose to maximize the system EE of a symbiotic radio (SR) network that contains a primary link and multiple BDs, each being able to harvest energy while backscattering, by optimizing the primary transmitter (PT) transmission power, the BDs' reflection coefficients and time division multiple access (TDMA) time slot durations for both the parasitic SR (PSR) and commensal SR (CSR) cases. The simulation results show that the system EE is maximized when all BDs only achieve the minimum throughput requirement in the PSR case, while in the CSR case, the system EE is maximized when a best BD that can contribute the most toward the system EE is allocated the maximum allowed time to backscatter its information to the primary receiver (PR), and this best BD is determined by the optimized PT transmission power in the corresponding time slot. In hybrid transmission-based WPCNs, the wireless devices are equipped with both the RF signal generation circuit and the backscatter circuit to support active transmission and passive transmission, respectively. In paper IV, we maximize the total EE of all the IoT nodes, which are powered by an unmanned aerial vehicle (UAV) and need to send information to a reader, by optimizing the UAV's transmit power and trajectory, the IoT nodes' backscatter reflection coefficients, transmit power for active transmission, and time allocation between backscattering and active transmission. Our results show that the UAV tends to fly toward the IoT nodes with better channel conditions to the reader, and the maximum total EE of the IoT nodes is achieved when the IoT node that is closest to the reader achieves the highest throughput, while other IoT nodes maintaining the minimum throughout requirement

Energy-Sustainable IoT Connectivity: Vision, Technological Enablers, Challenges, and Future Directions

Technology solutions must effectively balance economic growth, social equity, and environmental integrity to achieve a sustainable society. Notably, although the Internet of Things (IoT) paradigm constitutes a key sustainability enabler, critical issues such as the increasing maintenance operations, energy consumption, and manufacturing/disposal of IoT devices have long-term negative economic, societal, and environmental impacts and must be efficiently addressed. This calls for self-sustainable IoT ecosystems requiring minimal external resources and intervention, effectively utilizing renewable energy sources, and recycling materials whenever possible, thus encompassing energy sustainability. In this work, we focus on energy-sustainable IoT during the operation phase, although our discussions sometimes extend to other sustainability aspects and IoT lifecycle phases. Specifically, we provide a fresh look at energy-sustainable IoT and identify energy provision, transfer, and energy efficiency as the three main energy-related processes whose harmonious coexistence pushes toward realizing self-sustainable IoT systems. Their main related technologies, recent advances, challenges, and research directions are also discussed. Moreover, we overview relevant performance metrics to assess the energy-sustainability potential of a certain technique, technology, device, or network and list some target values for the next generation of wireless systems. Overall, this paper offers insights that are valuable for advancing sustainability goals for present and future generations.Comment: 25 figures, 12 tables, submitted to IEEE Open Journal of the Communications Societ