Millimeter Wave Energy Harvesting

Khan, Talha Ahmed; Alkhateeb, Ahmed; Heath, Robert W.

doi:10.1109/twc.2016.2577582

Cited by 143 publications

(106 citation statements)

References 31 publications

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“…The outage is said to occur if the signal-to-noise ratio (SNR) is low or the energy harvested at the transmitter or receiver is not high enough. Contrary to all these works, which are more applicable to ad hoc or decentralized networks, the joint analysis of harvested energy and downlink SINR in a cellular setup was recently performed in [29], [30]. In [29], since the exact analysis does not provide insightful results, authors use Frechet's inequality to derive an upper bound on the joint downlink energy and SINR coverage probability.…”

Section: Introductionmentioning

confidence: 99%

Joint Uplink and Downlink Coverage Analysis of Cellular-based RF-powered IoT Network

Kishk

Dhillon

2018

IEEE Trans. on Green Commun. Netw.

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Ambient radio frequency (RF) energy harvesting has emerged as a promising solution for powering small devices and sensors in massive Internet of Things (IoT) ecosystem due to its ubiquity and cost efficiency. In this paper, we study joint uplink and downlink coverage of cellular-based ambient RF energy harvesting IoT where the cellular network is assumed to be the only source of RF energy. We consider a time division-based approach for power and information transmission where each time-slot is partitioned into three sub-slots: (i) charging sub-slot during which the cellular base stations (BSs) act as RF chargers for the IoT devices, which then use the energy harvested in this sub-slot for information transmission and/or reception during the remaining two sub-slots, (ii) downlink sub-slot during which the IoT device receives information from the associated BS, and (iii) uplink sub-slot during which the IoT device transmits information to the associated BS. For this setup, we characterize the joint coverage probability, which is the joint probability of the events that the typical device harvests sufficient energy in the given time slot and is under both uplink and downlink signal-to-interference-plus-noise ratio (SINR) coverage with respect to its associated BS. This metric significantly generalizes the prior art on energy harvesting communications, which usually focused on downlink or uplink coverage separately.The key technical challenge is in handling the correlation between the amount of energy harvested in the charging sub-slot and the information signal quality (SINR) in the downlink and uplink subslots. Dominant BS-based approach is developed to derive tight approximation for this joint coverage probability. Several system design insights including comparison with regularly powered IoT network and throughput-optimal slot partitioning are also provided.Internet of Things (IoT) is a massive ecosystem of interconnected things (referred to as IoT devices) with sensing, processing, and communication capabilities [2]. Due to its ubiquity, cellular network has emerged as an attractive option to provide reliable communication infrastructure for supporting and managing these networks [3]-[6]. This new communication paradigm will enable a new era of applications including medical applications, transportation, surveillance, and smart homes to name a few. Unlike human-operated cellular devices, such as smart phones and tablets, that can be charged at will, these IoT devices may be deployed at hard-to-reach places, such as underground or in the tunnels, which makes it difficult to charge or replace their batteries. This has led to an increasing interest in energy-efficient communication of IoT devices, both from the system design [4]- [6], and hardware perspectives [7]. While these efforts will increase the lifetime of these devices, they do not necessarily make them self-sustained in terms of their energy requirements. One possible way to develop an almost self-perpetuatingIoT network is to complement or even circumven...

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Section: Introductionmentioning

confidence: 99%

Joint Uplink and Downlink Coverage Analysis of Cellular-based RF-powered IoT Network

Kishk

Dhillon

2018

IEEE Trans. on Green Commun. Netw.

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“…The work of [22] studied the wireless powered mmWave cellular network, in which uniform linear array with analog beamforming was implemented for WPT and uplink information transmission. Subsequently in [23], downlink SWIPT was investigated in mmWave systems, and the average harvested energy at the UEs and the downlink coverage probability were evaluated. However, the limitation of [22] is that it assumed that mmWave UEs have infinite battery capacity such that constant uplink transmit power can be guaranteed, while [23] only considered WPT in the downlink and investigated the effects of WPT on downlink information transmission.…”

Section: A Prior Work and Motivationmentioning

confidence: 99%

Wireless Powered Dense Cellular Networks: How Many Small Cells Do We Need?

Wang

Wong

Heath

et al. 2017

IEEE J. Select. Areas Commun.

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This paper focuses on wireless powered 5G dense cellular networks, where base station (BS) delivers energy to user equipment (UE) via the microwave radiation in sub-6 GHz or millimeter wave (mmWave) frequency, and UE uses the harvested energy for uplink information transmission. By addressing the impacts of employing different number of antennas and bandwidths at lower and higher frequencies, we evaluate the amount of harvested energy and throughput in such networks. Based on the derived results, we obtain the required small cell density to achieve an expected level of harvested energy or throughput. Also, we obtain that when the ratio of the number of sub-6 GHz BSs to that of the mmWave BSs is lower than a given threshold, UE harvests more energy from a mmWave BS than a sub-6 GHz BS. We find how many mmWave small cells are needed to perform better than the sub-6 GHz small cells from the perspectives of harvested energy and throughput. Our results reveal that the amount of harvested energy from the mmWave tier can be comparable to the sub-6 GHz counterpart in the dense scenarios. For the same tier scale, mmWave tier can achieve higher throughput. Furthermore, the throughput gap between different mmWave frequencies increases with the mmWave BS density.Index Terms-Millimeter wave (mmWave), dense small cells, wireless power transfer, throughput.• The very sharp signal beams in large-scale antenna systems such as massive MIMO and mmWave bring large antenna array gains, enabling WPT over long distances.

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“…Due to wireless medium, some nodes are not connected to their neighbors which are treated as isolated nodes. These performance metrics have been studied in recent literature [6], [14], [38]. Due to the impact of 3 For details on finding the active node density, please refer to [14].…”

Section: Performance Analysismentioning

confidence: 99%

“…These design features of mmWave makes encourages radio frequency (RF) energy harvesting (EH), where a node may harvest the ambient mmWave energy incident on it. A receiver architecture for mmWave systems was proposed in [6] for simultaneous wireless information and power transfer. EH solutions to power devices have been studied in literature for quite a while, with moderate level of practical success [7].…”

Section: Introductionmentioning

confidence: 99%

On the Performance of mmWave Networks Aided by Wirelessly Powered Relays

Biswas

Vuppala

Ratnarajah

2016

IEEE J. Sel. Top. Signal Process.

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Abstract-We investigate the energy harvesting (EH) potential of an outdoor millimeter-wave (mmWave) network aided by wirelessly powered relays (WRs). Due to the effect of propagation characteristics, such as blockages, WRs can assist the coverage in mmWave networks. In this paper, we consider the WRs to be equipped with battery units that can store ambient RF energy from the mmWave sources. The sources and the WRs are modeled as independent homogeneous Poisson point processes (PPPs). Leveraging tools from stochastic geometry, we study the EH potential of the WRs and their coverage probability based on the amount of energy that can be harvested. To successfully receive and transmit, the batteries in the WRs have to store sufficient energy, while the received signal to interference plus noise (SINR) ratio at the destination is above a certain threshold level. We also analyze the node isolation and network connectivity probabilities for the WRs considering a bounded region. Based on this bounded region of the WRs, we then select the best WR to forward the message from sources to the destination. Furthermore, the coverage probability is also analyzed for the WRs residing both within and outside the bounded region.

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Millimeter Wave Energy Harvesting

Cited by 143 publications

References 31 publications

Joint Uplink and Downlink Coverage Analysis of Cellular-based RF-powered IoT Network

Joint Uplink and Downlink Coverage Analysis of Cellular-based RF-powered IoT Network

Wireless Powered Dense Cellular Networks: How Many Small Cells Do We Need?

On the Performance of mmWave Networks Aided by Wirelessly Powered Relays

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