Energy-Efficient Stable Matching for Resource Allocation in Energy Harvesting-Based Device-to-Device Communications

Zhou, Zhenyu; Gao, Caixia; Xu, Chen; Chen, Tao; Zhang, Di; Mumtaz, Shahid

doi:10.1109/access.2017.2678508

Cited by 88 publications

(47 citation statements)

References 61 publications

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“…Based on the linear energy harvesting model [31], the power of the received signal for the energy harvesting at the SU-Rx…”

Section: System Model and Formulationmentioning

confidence: 99%

“…Remark 2: In the considered SWIPT-enabled cognitive ad hoc networks, there is no central BS for scheduling the overall messages. Based on the broadcast channel gain g m (which is obtained by listening to the feeback signals from the PU-Rx [28]) and the estimated interference power at each SU-Rx, the algorithm can be achieved by a distributed way from (22), (29), (31) and (36). Specifically, algorithm 1 is a distributed RA algorithm which can reduce the computational burden of mobile devices and save energy.…”

Section: B Feasible Region Analysismentioning

confidence: 99%

“…Moreover, it can reduce the overhead of message passing among all SUs. Specifically, firstly, according to (22), (29), (31), and (36), the utility function of each SU (∀m) only depends on that user's primal variables. Secondly, the Lagrange multipliers can be divided into the local variables for each SU (e.g., β m , α m ).…”

Section: B Feasible Region Analysismentioning

confidence: 99%

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Optimal and Robust Distributed Resource Allocation for SWIPT-Enabled Cognitive Networks

Xu¹,

Sun²,

Yang³

et al. 2020

Preprint

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Simultaneous wireless information and power transfer (SWIPT)-enabled cognitive networks (CRNs) is recognized as one of the most promising techniques to improve spectrum efficiency and prolong operation lifetime in 5G and beyond. However, existing methods focus on the centralized algorithm and the power allocation under perfect channel state information (CSI). The analytical solution and the impact of power splitting (PS) on the optimal power allocation strategy are not addressed. In addition, the influence of the PS factor on the feasible region of transit power is rarely analyzed. In this paper, we propose a joint power allocation and PS algorithm under perfect CSI and imperfect CSI, respectively, for multiuser SWIPT-enabled CRNs scenarios. The power minimization of resource allocation problem is formulated as a multivariate nonconvex optimization which is hard to obtain the closed-form solution. Hence, we propose a suboptimal algorithm to alternatively optimize the power allocation and PS coefficient under the cases of the low-harvested energy region and the high-harvested energy region, respectively. Moreover, a closed-form distributed power allocation and PS expressions are derived by the Lagrangian approach. Simulation results confirm the proposed method with good robustness and high energy efficiency.

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“…Based on the linear energy harvesting model [31], the power of the received signal for the energy harvesting at the SU-Rx…”

Section: System Model and Formulationmentioning

confidence: 99%

Section: B Feasible Region Analysismentioning

confidence: 99%

Section: B Feasible Region Analysismentioning

confidence: 99%

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Optimal and Robust Distributed Resource Allocation for SWIPT-Enabled Cognitive Networks

Xu¹,

Sun²,

Yang³

et al. 2020

Preprint

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“…Kaur et al [4] proposed a network model for the performance analysis of D2D communications in a peer-to-peer SWIPT strategy with RF transmitters. Also, a joint power control and resource allocation problem in SWIPT-based energy-harvesting D2D underlay networks was investigated in [5]. Furthermore, Ali el at.[6] employed the SWIPT energy harvesting technique at the relay nodes to prolong the lifetime of energy-constrained networks and integrated D2D clustering techniques into cellular networks so that communication services can be effectively maintained when the cellular infrastructure becomes partially dysfunctional.…”

mentioning

confidence: 99%

mentioning

confidence: 99%

Harnessing D2D Communications in Collaborative Mobile Clouds for Content Sharing: An Energy Efficient Communication Scheme

Huang

Xing

2019

Proceedings of the 12th EAI International Conference on Mobile Multimedia Communications, Mobimedia 2019, 29th - 30th Jun 2019,

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This paper presents an energy efficiency (EE) communication scheme for content sharing with Collaborative Mobile Clouds (CMC) and D2D cluster. A waterfilling-based data segmentation approach for content distribution is proposed. Within the CMC, the cost-effective resource allocation and the power control mechanisms for D2D communications are designed. Through performance comparisons, it is disclosed that the proposed scheme dominates different variations of it in terms of system EE.On the other hand, simultaneous wireless information and power transfer (SWIPT) has emerged as a powerful mechanism against the energy depletion in wireless communications. SWIPT admits two architectures-time switching and power splitting. In the former, the receiver periodically switches between information decoding and energy harvesting (EH) modules. In the latter, the receiver separates the received signals into two streams, one for the energy harvester and the other for the information decoder. Recent studies show the ndication that SWIPT can be expected to be fully used in D2D communications.While the SWIPT realizes the energy harvesting from information signal streams, SWIPTenabled D2D communication scenarios have extensively explored. Huang et al. [3] surveyed the state-of-the-art of SWIPT architectures and enabling technologies, identified technical challenges to implement SWIPT, and showcased a novel SWIPT-supported D2D power allocation mechanism to illustrate the importance of the application of the SWIPT technology. Kaur et al. [4] proposed a network model for the performance analysis of D2D communications in a peer-to-peer SWIPT strategy with RF transmitters. Also, a joint power control and resource allocation problem in SWIPT-based energy-harvesting D2D underlay networks was investigated in [5]. Furthermore, Ali el at.[6] employed the SWIPT energy harvesting technique at the relay nodes to prolong the lifetime of energy-constrained networks and integrated D2D clustering techniques into cellular networks so that communication services can be effectively maintained when the cellular infrastructure becomes partially dysfunctional. By analyzing the above research work, the D2D cluster and SWIPT technology are not effectively combined to improve communication energy efficiency. It is worth noting that the resource allocation problem in CMC-assisted and SWIPT-enabled D2D content sharing scenarios was investigated in [7], and the EE of the entire system could be improved to a certain extent in that study. Unfortunately, the following critical issues were not addressed appropriately in [7].1) How to segment the data contents? 2) In addition to spectrum utilization improvement, can a better EE be gained if the reuse mode of D2D communications is adopted? 3) How to guarantee the fairness of energy transfer and data transmission within the CMC? 4) What if SWIPT is supported by D2D user devices in terms of the system EE? Dealing with these issues can contribute significantly toward enhancing the system EE, which is part of the motiva...

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D2Dwith Energy Harvesting Capabilities

Chang

2020

Wiley 5G Ref

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Device‐to‐device (D2D) communication is envisioned as a key enabling technology for fifth‐generation (5G) wireless systems and the Internet of Things (IoT). D2D promises increased resource utilization, throughput, and coverage, and decreased delays and power consumption, by offloading traffic from the centralized infrastructure to autonomous direct device‐to‐device transmissions. With the rise of D2D and IoT, which comprise typically small, battery‐powered devices, it is essential to consider the energy efficiency and sustainability of future D2D networks. Energy harvesting (EH) has emerged as a promising green and sustainable energy solution for D2D and IoT. EH technologies represent harnessing energy from ambient renewable energy sources and converting the harvested environmental energy into usable electrical energy via wireless power transfer (WPT) technologies. Among various renewable sources, radio frequency (RF) signals are more reliable and allow for simultaneous wireless information and power transfer (SWIPT), and therefore are of particular interest. EH‐aided D2D communication raises new resource allocation and interference management considerations nonexistent in conventional D2D communication, since cochannel interference, a main performance‐limiting factor in underlaid D2D networks, could be converted into useful energy. Issues such as power allocation/control, beamforming design, time allocation, and spectrum allocation, with the consideration of EH‐empowered D2D devices, have been investigated for EH‐aided D2D networks.

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Energy-Efficient Stable Matching for Resource Allocation in Energy Harvesting-Based Device-to-Device Communications

Cited by 88 publications

References 61 publications

Optimal and Robust Distributed Resource Allocation for SWIPT-Enabled Cognitive Networks

Optimal and Robust Distributed Resource Allocation for SWIPT-Enabled Cognitive Networks

Harnessing D2D Communications in Collaborative Mobile Clouds for Content Sharing: An Energy Efficient Communication Scheme

D2Dwith Energy Harvesting Capabilities

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