Energy Harvesting in Sub-6 GHz and Millimeter Wave Hybrid Networks

Muhammad, Nor Aishah; Seman, Norhudah; Apandi, Nur Ilyana Anwar; Li, Yonghui

doi:10.1109/tvt.2021.3068956

Cited by 10 publications

(9 citation statements)

References 37 publications

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“…Proof. The proof of Lemma 3 follows the same lines as given in [33,Appendix B]. Now, let X k denotes the conditional distance that the typical UE associates with a BS in the k-th tier.…”

Section: A Distance Distributionmentioning

confidence: 99%

“…A perfect beam alignment is assumed between the typical UE and its serving BS [27], [33], where the effective gain on the desired link is G 1 G u . For the interfering BSs, we assume that each interferer is transmitting with the main-lobe beam pointed at a random direction.…”

Section: B Antenna Modelingmentioning

confidence: 99%

“…In contrast, the MMW signals are vulnerable to severe penetration losses, which lead to completely different path loss laws for LoS and non-LoS propagation. Following the work in [21], [22], [33], we consider a distance-dependent blockage model where an MMW link with distance r can be either in LoS or non-LoS state. Denote by p L (r) = e −βr and p N (r) = 1 − e −βr the probability of LoS and non-LoS states, respectively, where β is a parameter determined by the average size and the density of the blockages [21].…”

Section: Propagation Modelingmentioning

confidence: 99%

“…Content may change prior to final publication. Next, following the derivation steps in (33), and evaluating the expectation of the combined expression with respect to S s , we obtain the IPD coverage probability of the typical UE in MMW tier as in Theorem 2.…”

Section: Appendix C Proof Of Theoremmentioning

confidence: 99%

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Stochastic Geometry Analysis of Electromagnetic Field Exposure in Coexisting Sub-6 GHz and Millimeter Wave Networks

et al. 2021

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Deploying sub-6 GHz macro-cell networks overlaid by millimeter wave (MMW) small-cells is a promising method to accommodate the unprecedented growth of data traffic demands and user devices. Although such a hybrid network could provide seamless connectivity and achieve high-quality services, there is a need to ensure that the growing number of base stations (BSs) does not affect biological safety, especially when the BSs are operated at high frequencies. This paper focuses on an analytical framework to investigate the electromagnetic field (EMF) exposure in a cellular network with coexisting sub-6 GHz and MMW BSs using a stochastic geometry approach. Locations of sub-6 GHz and MMW BSs are modeled as Poisson point processes (PPP). By incorporating different channel propagation, antenna, and fading models for sub-6 GHz and MMW tiers, the incident power density (IPD) coverage probability and the average IPD are derived and validated by Monte Carlo simulations. The impact of various system parameters such as BS density, number of antenna elements, and blockage density are investigated to gain insights on the network scenario. The results demonstrate that the variation of the EMF exposure level closely depends on the BS density and the number of antennas deployed at the BS. The results also show that the receiver sensitivity has a significant impact on the average IPD. For the same receiver sensitivity, it is revealed that an MMW user is exposed to a higher average IPD level than the sub-6 GHz counterpart. The results are also compared with the existing international regulations.INDEX TERMS Electromagnetic field (EMF), millimeter wave, sub-6 GHz, stochastic geometry, Poisson point process, incident power density.

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“…Proof. The proof of Lemma 3 follows the same lines as given in [33,Appendix B]. Now, let X k denotes the conditional distance that the typical UE associates with a BS in the k-th tier.…”

Section: A Distance Distributionmentioning

confidence: 99%

Section: B Antenna Modelingmentioning

confidence: 99%

Section: Propagation Modelingmentioning

confidence: 99%

Section: Appendix C Proof Of Theoremmentioning

confidence: 99%

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Stochastic Geometry Analysis of Electromagnetic Field Exposure in Coexisting Sub-6 GHz and Millimeter Wave Networks

et al. 2021

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“…Under the mmWave network architecture, energy harvesting is capable of providing reliable and sustainable energy coverage and shows better performance than conventional low-frequency scenarios [ 12 , 13 , 14 ]. The authors of [ 15 , 16 ] investigated the performance of energy harvesting in UAV-assisted mmWave technology. The authors of [ 15 ] derived the energy and SINR coverage probability under the UAV mmWave network enabled by energy harvesting.…”

Section: Related Workmentioning

confidence: 99%

Energy-Efficient Optimization for Energy-Harvesting-Enabled mmWave-UAV Heterogeneous Networks

Zhang

Chuai

Gao

2022

Entropy

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Energy Harvesting (EH) is a promising paradigm for 5G heterogeneous communication. EH-enabled Device-to-Device (D2D) communication can assist devices in overcoming the disadvantage of limited battery capacity and improving the Energy Efficiency (EE) by performing EH from ambient wireless signals. Although numerous research works have been conducted on EH-based D2D communication scenarios, the feature of EH-based D2D communication underlying Air-to-Ground (A2G) millimeter-Wave (mmWave) networks has not been fully studied. In this paper, we considered a scenario where multiple Unmanned Aerial Vehicles (UAVs) are deployed to provide energy for D2D Users (DUs) and data transmission for Cellular Users (CUs). We aimed to improve the network EE of EH-enabled D2D communications while reducing the time complexity of beam alignment for mmWave-enabled D2D Users (DUs). We considered a scenario where multiple EH-enabled DUs and CUs coexist, sharing the full mmWave frequency band and adopting high-directive beams for transmitting. To improve the network EE, we propose a joint beamwidth selection, power control, and EH time ratio optimization algorithm for DUs based on alternating optimization. We iteratively optimized one of the three variables, fixing the other two. During each iteration, we first used a game-theoretic approach to adjust the beamwidths of DUs to achieve the sub-optimal EE. Then, the problem with regard to power optimization was solved by the Dinkelbach method and Successive Convex Approximation (SCA). Finally, we performed the optimization of the EH time ratio using linear fractional programming to further increase the EE. By performing extensive simulation experiments, we validated the convergence and effectiveness of our algorithm. The results showed that our proposed algorithm outperformed the fixed beamwidth and fixed power strategy and could closely approach the performance of exhaustive search, particle swarm optimization, and the genetic algorithm, but with a much reduced time complexity.

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Wireless Powered mmWave Cooperative Communication Network

Parida

Das

2023

Wireless Pers Commun

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This research article verifies the scope of utilization of a very favourable combination of Wireless power transfer (WPT) and millimeter wave (mmWave) communications technology using selective beamforming in a Multiple input single output (MISO) system consisting of a Hybrid access point (HAP) having an array antenna in downlink and a user having single antenna in the uplink. A specific mmWave extended NYUSIM Channel model used for good spatial consistency. The mmWave based wireless powered cooperative communication network (WPCCN) considered here serves the user equipment in the network by harvesting energy from the received signal to use it further to power their uplink transmissions. The scope of wireless power transfer in an mmWave channel has been verified and discussed based on the analysis made on the output performance parameters derived using an mmWave based novel NYUSIM channel simulator, i.e., NYUSIM Version 2.01. The output results derived from the simulation results with sufficient analysis on user requirements support the fact that the proposed work discovers a good scope of development in the mmWave based WPCCN. Ultimately it explores the design and validation of a robust self-sustainable communication network model for the future green communication network. Some important technical challenges and future research scopes are also discussed effectively.

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Energy Harvesting in Sub-6 GHz and Millimeter Wave Hybrid Networks

Cited by 10 publications

References 37 publications

Stochastic Geometry Analysis of Electromagnetic Field Exposure in Coexisting Sub-6 GHz and Millimeter Wave Networks

Stochastic Geometry Analysis of Electromagnetic Field Exposure in Coexisting Sub-6 GHz and Millimeter Wave Networks

Energy-Efficient Optimization for Energy-Harvesting-Enabled mmWave-UAV Heterogeneous Networks

Wireless Powered mmWave Cooperative Communication Network

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