680 research outputs found
Sum Throughput Maximization in Multi-BD Symbiotic Radio NOMA Network Assisted by Active-STAR-RIS
In this paper, we employ active simultaneously transmitting and reflecting
reconfigurable intelligent surface (ASRIS) to aid in establishing and enhancing
communication within a commensal symbiotic radio (CSR) network. Unlike
traditional RIS, ASRIS not only ensures coverage in an omni directional manner
but also amplifies received signals, consequently elevating overall network
performance. in the first phase, base station (BS) with active massive MIMO
antennas, send ambient signal to SBDs. In the first phase, the BS transmits
ambient signals to the symbiotic backscatter devices (SBDs), and after
harvesting the energy and modulating their information onto the signal carrier,
the SBDs send Backscatter signals back to the BS. In this scheme, we employ the
Backscatter Relay system to facilitate the transmission of information from the
SBDs to the symbiotic User Equipments (SUEs) with the assistance of the BS. In
the second phase, the BS transmits information signals to the SUEs after
eliminating interference using the Successive Interference Cancellation (SIC)
method. ASRIS is employed to establish communication among SUEs lacking a line
of sight (LoS) and to amplify power signals for SUEs with a LoS connection to
the BS. It is worth noting that we use NOMA for multiple access in all network.
The main goal of this paper is to maximize the sum throughput between all
users. To achieve this, we formulate an optimization problem with variables
including active beamforming coefficients at the BS and ASRIS, as well as the
phase adjustments of ASRIS and scheduling parameters between the first and
second phases. To model this optimization problem, we employ three deep
reinforcement learning (DRL) methods, namely PPO, TD3, and A3C. Finally, the
mentioned methods are simulated and compared with each other.Comment: This article will be submitted to the Transactions journa
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
Enhanced Physical Layer Security for Full-duplex Symbiotic Radio with AN Generation and Forward Noise Suppression
Due to the constraints on power supply and limited encryption capability,
data security based on physical layer security (PLS) techniques in backscatter
communications has attracted a lot of attention. In this work, we propose to
enhance PLS in a full-duplex symbiotic radio (FDSR) system with a proactive
eavesdropper, which may overhear the information and interfere legitimate
communications simultaneously by emitting attack signals. To deal with the
eavesdroppers, we propose a security strategy based on pseudo-decoding and
artificial noise (AN) injection to ensure the performance of legitimate
communications through forward noise suppression. A novel AN signal generation
scheme is proposed using a pseudo-decoding method, where AN signal is
superimposed on data signal to safeguard the legitimate channel. The phase
control in the forward noise suppression scheme and the power allocation
between AN and data signals are optimized to maximize security throughput. The
formulated problem can be solved via problem decomposition and alternate
optimization algorithms. Simulation results demonstrate the superiority of the
proposed scheme in terms of security throughput and attack mitigation
performance
Energy-efficient non-orthogonal multiple access for wireless communication system
Non-orthogonal multiple access (NOMA) has been recognized as a potential solution for enhancing the throughput of next-generation wireless communications. NOMA is a potential option for 5G networks due to its superiority in providing better spectrum efficiency (SE) compared to orthogonal multiple access (OMA). From the perspective of green communication, energy efficiency (EE) has become a new performance indicator. A systematic literature review is conducted to investigate the available energy efficient approach researchers have employed in NOMA. We identified 19 subcategories related to EE in NOMA out of 108 publications where 92 publications are from the IEEE website. To help the reader comprehend, a summary for each category is explained and elaborated in detail. From the literature review, it had been observed that NOMA can enhance the EE of wireless communication systems. At the end of this survey, future research particularly in machine learning algorithms such as reinforcement learning (RL) and deep reinforcement learning (DRL) for NOMA are also discussed
RF Energy Harvesting Wireless Communication: RF Environment, Device Hardware and Practical Issues
Radio frequency (RF) based wireless power transfer provides an attractive solution to extend the lifetime of power-constrained wireless sensor networks. Through harvesting RF energy from surrounding environments or dedicated energy sources, low-power wireless devices can be self-sustaining and environment-friendly. These features make the RF energy harvesting wireless communication (RF-EHWC) technique attractive to a wide range of applications. The objective of this article is to investigate the latest research activities on the practical RF-EHWC design. The distribution of RF energy in the real environment, the hardware design of RF-EHWC devices and the practical issues in the implementation of RF-EHWC networks are discussed. At the end of this article, we introduce several interesting applications that exploit the RF-EHWC technology to provide smart healthcare services for animals, wirelessly charge the wearable devices, and implement 5G-assisted RF-EHWC
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Transiently Powered Computers
Demand for compact, easily deployable, energy-efficient computers has driven the development of general-purpose transiently powered computers (TPCs) that lack both batteries and wired power, operating exclusively on energy harvested from their surroundings.
TPCs\u27 dependence solely on transient, harvested power offers several important design-time benefits. For example, omitting batteries saves board space and weight while obviating the need to make devices physically accessible for maintenance. However, transient power may provide an unpredictable supply of energy that makes operation difficult. A predictable energy supply is a key abstraction underlying most electronic designs. TPCs discard this abstraction in favor of opportunistic computation that takes advantage of available resources. A crucial question is how should a software-controlled computing device operate if it depends completely on external entities for power and other resources? The question poses challenges for computation, communication, storage, and other aspects of TPC design.
The main idea of this work is that software techniques can make energy harvesting a practicable form of power supply for electronic devices. Its overarching goal is to facilitate the design and operation of usable TPCs.
This thesis poses a set of challenges that are fundamental to TPCs, then pairs these challenges with approaches that use software techniques to address them. To address the challenge of computing steadily on harvested power, it describes Mementos, an energy-aware state-checkpointing system for TPCs. To address the dependence of opportunistic RF-harvesting TPCs on potentially untrustworthy RFID readers, it describes CCCP, a protocol and system for safely outsourcing data storage to RFID readers that may attempt to tamper with data. Additionally, it describes a simulator that facilitates experimentation with the TPC model, and a prototype computational RFID that implements the TPC model.
To show that TPCs can improve existing electronic devices, this thesis describes applications of TPCs to implantable medical devices (IMDs), a challenging design space in which some battery-constrained devices completely lack protection against radio-based attacks. TPCs can provide security and privacy benefits to IMDs by, for instance, cryptographically authenticating other devices that want to communicate with the IMD before allowing the IMD to use any of its battery power. This thesis describes a simplified IMD that lacks its own radio, saving precious battery energy and therefore size. The simplified IMD instead depends on an RFID-scale TPC for all of its communication functions.
TPCs are a natural area of exploration for future electronic design, given the parallel trends of energy harvesting and miniaturization. This work aims to establish and evaluate basic principles by which TPCs can operate
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