Energy Efficiency Optimization for SWIPT-Based D2D-Underlaid Cellular Networks Using Multiagent Deep Reinforcement Learning

Muy, Sengly; Ron, Dara; Lee, Jung-Ryun

doi:10.1109/jsyst.2021.3098860

Cited by 10 publications

(5 citation statements)

References 23 publications

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“…In [25], the authors determine the subchannel allocation, power splitting ratio (PR), and transmit power for the SWIPT-based device-to-device (D2D) networks through the deep-reinforcement-learning (DRL)-based algorithm developed therein. For similar D2D SWIPT-based networks, an EE optimization problem was formulated in [26], and the authors adopted exhaustive search (ES) and gradient search (GS), respectively, to obtain the global optimum and local optimum for the formulated nonconvex optimization problem.…”

Section: Related Workmentioning

confidence: 99%

“…In the above, we assume that N t antennas of each BS are arranged as a uniform linear array (ULA). In addition, similar to [9,11,25,26], we consider that each UE i with PS on the received signal y i (t) can simultaneously perform ID and EH as shown in Figure 1. Specifically, with θ i (t) ∈ (0, 1) to denote the PR adopted by UE i at time t, the instantaneous signal to interference and noise ratio (SINR) for ID can be formulated as [32]:…”

Section: Network and Channel Modelsmentioning

confidence: 99%

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Joint Data Transmission and Energy Harvesting for MISO Downlink Transmission Coordination in Wireless IoT Networks

Liu

Lin

et al. 2023

Sensors

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The advent of simultaneous wireless information and power (SWIPT) has been regarded as a promising technique to provide power supplies for an energy sustainable Internet of Things (IoT), which is of paramount importance due to the proliferation of high data communication demands of low-power network devices. In such networks, a multi-antenna base station (BS) in each cell can be utilized to concurrently transmit messages and energies to its intended IoT user equipment (IoT-UE) with a single antenna under a common broadcast frequency band, resulting in a multi-cell multi-input single-output (MISO) interference channel (IC). In this work, we aim to find the trade-off between the spectrum efficiency (SE) and energy harvesting (EH) in SWIPT-enabled networks with MISO ICs. For this, we derive a multi-objective optimization (MOO) formulation to obtain the optimal beamforming pattern (BP) and power splitting ratio (PR), and we propose a fractional programming (FP) model to find the solution. To tackle the nonconvexity of FP, an evolutionary algorithm (EA)-aided quadratic transform technique is proposed, which recasts the nonconvex problem as a sequence of convex problems to be solved iteratively. To further reduce the communication overhead and computational complexity, a distributed multi-agent learning-based approach is proposed that requires only partial observations of the channel state information (CSI). In this approach, each BS is equipped with a double deep Q network (DDQN) to determine the BP and PR for its UE with lower computational complexity based on the observations through a limited information exchange process. Finally, with the simulation experiments, we verify the trade-off between SE and EH, and we demonstrate that, apart from the FP algorithm introduced to provide superior solutions, the proposed DDQN algorithm also shows its performance gain in terms of utility to be up to 1.23-, 1.87-, and 3.45-times larger than the Advantage Actor Critic (A2C), greedy, and random algorithms, respectively, in comparison in the simulated environment.

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Section: Related Workmentioning

confidence: 99%

Section: Network and Channel Modelsmentioning

confidence: 99%

Joint Data Transmission and Energy Harvesting for MISO Downlink Transmission Coordination in Wireless IoT Networks

Liu

Lin

et al. 2023

Sensors

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“…Recently, there was a novel method to handle the problem, which meant the energy-limited cooperative communication system relay collected the interference signal energy and used it to transmit signal to compensate for the bad effects of interference [18]. So, many scholars had done some research on the matter of interference processing (IP) [19][20], efficient resource allocation strategy [21][22][23][24], and energy efficiency (EE) [25][26][27][28][29].…”

Section: Related Workmentioning

confidence: 99%

“…In [25], the authors studied the optimal energy efficiency in wireless device-to-device (D2D) cellular networks in which D2D couples used SWIPT technology. The EE optimization was studied with imperfect CSI in a SWIPT two-tier heterogeneous network in [26].…”

Section: Related Workmentioning

confidence: 99%

Research on The SWIPT System Throughput Based on Interference Signal Energy Collecting

2023

KSII TIIS

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The general interference is the imperative trouble for simultaneous wireless information and power transfer (SWIPT) system. Although interference has bad influences on the performance of the system, it carries energy simultaneously. In this paper, the energy-constrained relay of the SWIPT system needs to spend much time on energy collecting (EC) in the information transmission (IT) period. Therefore, we propose the scheme of interference signal energy collecting (ISEC) when the interference is strong, and the SWIPT system does not carry out IT. The relay of the system continues to collect energy and stores it until the interference has minimal impact on IT. Then the system performs IT. We divide the collected interference energy equally into several parts, and each IT block receives one part. The proposed scheme is appealing because it can reduce the time of EC in IT period to make the relay spends more time forwarding the received signal in order to improve the performance of the system throughput. Furthermore, we propose a time-switching (TS) protocol based on EC at the relay. And it allows the relay forwarding signal at an appropriate power. Under the protocol, the time of EC can be flexible according to the forwarding power that we give so that the collected energy can be used more efficiently. We give the expressions of the system throughput according to the proposed scheme and protocol. Moreover, the influence of the interference power on the system throughput is also studied.

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“…Many options are being explored to address the problem of frequency spectrum scarcity. Some of these options include utilization of visible light communication (VLC) [10], tremendously high frequencies, such as, terahertz [11], device to device (D2D) communication [12], [13], and cognitive radio (CR) [14], [15]. Particularly, spectrum scarcity can be overcome by using the unique solution provided by CR.…”

Section: Introductionmentioning

confidence: 99%

Interference Avoidance in Cognitive Radio Networks Using Cooperative Localization

Farooq-i-Azam

Dong

et al. 2022

IEEE Systems Journal

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In the recent years, there has been a tremendous increase in the use of wireless medium and radio frequency spectrum due to the development of new types of wireless networks, applications and enabling technologies. Consequently, the radio frequency spectrum is getting over crowded due to this increasing demand. Traditionally, frequency bands are allocated to licensed users for their specific use. Cognitive radio allows secondary users to communicate using these frequency bands. However, this may result in interference to the primary users. Information of the relative positions of the primary and secondary users and the distance between them can be exploited to avoid this interference. In our work, we use cooperative localization strategy to determine the distance between the secondary and primary users. This distance information is then utilized to adjust the transmission power of the secondary nodes so that the interference threshold of the primary users is not exceeded. The proposed methodology is evaluated using simulation experiments. Different aspects of the proposed algorithm including location and distance estimation, channel availability and channel capacity against transmission power and path loss are evaluated. The results show that the proposed scheme is able to achieve considerable gains as a consequence of interference avoidance.

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Energy Efficiency Optimization for SWIPT-Based D2D-Underlaid Cellular Networks Using Multiagent Deep Reinforcement Learning

Cited by 10 publications

References 23 publications

Joint Data Transmission and Energy Harvesting for MISO Downlink Transmission Coordination in Wireless IoT Networks

Joint Data Transmission and Energy Harvesting for MISO Downlink Transmission Coordination in Wireless IoT Networks

Research on The SWIPT System Throughput Based on Interference Signal Energy Collecting

Interference Avoidance in Cognitive Radio Networks Using Cooperative Localization

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