Throughput Maximization in Wireless Powered Communication Networks
02 Dec 2013-Vol. 13, Iss: 1, pp 418-428
TL;DR: The solution reveals an interesting "doubly near-far" phenomenon due to both the DL and UL distance-dependent signal attenuation, where a far user from the H-AP, which receives less wireless energy than a nearer user in the DL, has to transmit with more power in the UL for reliable information transmission.
Abstract: This paper studies the newly emerging wireless powered communication network in which one hybrid access point (H-AP) with constant power supply coordinates the wireless energy/information transmissions to/from a set of distributed users that do not have other energy sources. A "harvest-then-transmit" protocol is proposed where all users first harvest the wireless energy broadcast by the H-AP in the downlink (DL) and then send their independent information to the H-AP in the uplink (UL) by time-division-multiple-access (TDMA). First, we study the sum-throughput maximization of all users by jointly optimizing the time allocation for the DL wireless power transfer versus the users' UL information transmissions given a total time constraint based on the users' DL and UL channels as well as their average harvested energy values. By applying convex optimization techniques, we obtain the closed-form expressions for the optimal time allocations to maximize the sum-throughput. Our solution reveals an interesting "doubly near-far" phenomenon due to both the DL and UL distance-dependent signal attenuation, where a far user from the H-AP, which receives less wireless energy than a nearer user in the DL, has to transmit with more power in the UL for reliable information transmission. As a result, the maximum sum-throughput is shown to be achieved by allocating substantially more time to the near users than the far users, thus resulting in unfair rate allocation among different users. To overcome this problem, we furthermore propose a new performance metric so-called common-throughput with the additional constraint that all users should be allocated with an equal rate regardless of their distances to the H-AP. We present an efficient algorithm to solve the common-throughput maximization problem. Simulation results demonstrate the effectiveness of the common-throughput approach for solving the new doubly near-far problem in wireless powered communication networks.
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TL;DR: A comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management is provided in this paper, where a set of issues, challenges, and future research directions for MEC are discussed.
Abstract: Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized mobile cloud computing toward mobile edge computing (MEC). The main feature of MEC is to push mobile computing, network control and storage to the network edges (e.g., base stations and access points) so as to enable computation-intensive and latency-critical applications at the resource-limited mobile devices. MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. The promised gains of MEC have motivated extensive efforts in both academia and industry on developing the technology. A main thrust of MEC research is to seamlessly merge the two disciplines of wireless communications and mobile computing, resulting in a wide-range of new designs ranging from techniques for computation offloading to network architectures. This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. We also discuss a set of issues, challenges, and future research directions for MEC research, including MEC system deployment, cache-enabled MEC, mobility management for MEC, green MEC, as well as privacy-aware MEC. Advancements in these directions will facilitate the transformation of MEC from theory to practice. Finally, we introduce recent standardization efforts on MEC as well as some typical MEC application scenarios.
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TL;DR: This paper presents an overview of the RF-EHNs including system architecture, RF energy harvesting techniques, and existing applications, and explores various key design issues according to the network types, i.e., single-hop networks, multiantenna networks, relay networks, and cognitive radio networks.
Abstract: Radio frequency (RF) energy transfer and harvesting techniques have recently become alternative methods to power the next-generation wireless networks As this emerging technology enables proactive energy replenishment of wireless devices, it is advantageous in supporting applications with quality-of-service requirements In this paper, we present a comprehensive literature review on the research progresses in wireless networks with RF energy harvesting capability, which is referred to as RF energy harvesting networks (RF-EHNs) First, we present an overview of the RF-EHNs including system architecture, RF energy harvesting techniques, and existing applications Then, we present the background in circuit design as well as the state-of-the-art circuitry implementations and review the communication protocols specially designed for RF-EHNs We also explore various key design issues in the development of RF-EHNs according to the network types, ie, single-hop networks, multiantenna networks, relay networks, and cognitive radio networks Finally, we envision some open research directions
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Cites background or methods or result from "Throughput Maximization in Wireless..."
...The study in [17] extends [143] by considering the case with a multi-antenna access point....
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...The simulations show that the proposed protocol is superior to the harvest-thentransmit protocol [143] reviewed above in all considered cases....
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...Simulation results show that the fixed point iteration algorithm achieves similar individual throughput compared to the iterative algorithm in [143] but with much lower computation complexity....
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...This doubly near-far phenomenon has been considered in different network models [17], [143], [144]....
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...In [143], a joint downlink RF energy transfer and uplink information transmission problem is investigated in a multiple access system....
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Posted Content•
TL;DR: A comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management and recent standardization efforts on MEC are introduced.
Abstract: Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized Mobile Cloud Computing towards Mobile Edge Computing (MEC). The main feature of MEC is to push mobile computing, network control and storage to the network edges (e.g., base stations and access points) so as to enable computation-intensive and latency-critical applications at the resource-limited mobile devices. MEC promises dramatic reduction in latency and mobile energy consumption, tackling the key challenges for materializing 5G vision. The promised gains of MEC have motivated extensive efforts in both academia and industry on developing the technology. A main thrust of MEC research is to seamlessly merge the two disciplines of wireless communications and mobile computing, resulting in a wide-range of new designs ranging from techniques for computation offloading to network architectures. This paper provides a comprehensive survey of the state-of-the-art MEC research with a focus on joint radio-and-computational resource management. We also present a research outlook consisting of a set of promising directions for MEC research, including MEC system deployment, cache-enabled MEC, mobility management for MEC, green MEC, as well as privacy-aware MEC. Advancements in these directions will facilitate the transformation of MEC from theory to practice. Finally, we introduce recent standardization efforts on MEC as well as some typical MEC application scenarios.
2,289 citations
Cites background from "Throughput Maximization in Wireless..."
...• Moreover, wireless power transfer (WPT), which charges mobile devices using RF wave [209], [210], is a newlyemerged solution that enables wireless charging and extends the battery life....
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TL;DR: An overview of state-of- the-art RF-enabled WET technologies and their applications to wireless communications, highlighting the key design challenges, solutions, and opportunities ahead.
Abstract: The performance of wireless communication is fundamentally constrained by the limited battery life of wireless devices, the operations of which are frequently disrupted due to the need of manual battery replacement/recharging. The recent advance in RF-enabled wireless energy transfer (WET) technology provides an attractive solution named wireless powered communication (WPC), where the wireless devices are powered by dedicated wireless power transmitters to provide continuous and stable microwave energy over the air. As a key enabling technology for truly perpetual communications, WPC opens up the potential to build a network with larger throughput, higher robustness, and increased flexibility compared to its battery-powered counterpart. However, the combination of wireless energy and information transmissions also raises many new research problems and implementation issues that need to be addressed. In this article, we provide an overview of stateof- the-art RF-enabled WET technologies and their applications to wireless communications, highlighting the key design challenges, solutions, and opportunities ahead.
1,032 citations
Cites background or methods from "Throughput Maximization in Wireless..."
...ontrollable energy source, a wireless powered communication network (WPCN) could be efficiently built to power multiple communic ation devices of different physical conditions and service requirements [3]. Besides, with RF-enabled WET, information could also be jointly transmitted with energy using the same waveform. Such a design paradigm is referred to as simultaneous wireless information and power ...
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...ess energy within the short duration of DL WET. Otherwise, a larger τ0 is required for the far users to harvest sufficient energy before commencing reliab le data transmission. In fact, it is shown in [3] that the optimal value of τ0 that maximizes the sum-rate decreases as the sum of channel power gains of all users increases. B. Doubly-near-far problem Besides setting the optimal duration for WET in...
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...the HAP (U2) harvests much lower wireless energy in the DL but consumes more to transmit data in the UL than a user near the HAP (U1). This coupled effect is referred to as the doubly-near-far problem[3], which could result in very low throughput for far users, e.g., 100times less data rate than a nearby user, if the multiple access scheme is not properly designed. When TDMA is used in the second pha...
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...em. Here, we consider another scenario that the wireless devices use the harvested energy to transmit information. This design paradigm is referred to as wireless powered communication network (WPCN) [3]. In this section, we introduce the basic operations of a WPCN, the key design challenges and solutions, and interesting extensions to many practical network models. A. Harvest-then-transmit protocol ...
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...onally, the receivers perform EH in the DL transmission of WPCN mode while sending data in the UL with harvested energy, with applications such as sensor battery charging and data collection in a WSN [3]. For the SWIPT mode, the receivers perform both EH and information decoding (ID) in the DL with the same received signals, each using harvested energy to power its information decoder, e.g., in an en...
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TL;DR: In this paper, the authors present a comprehensive overview of wireless charging techniques, the developments in technical standards, and their recent advances in network applications, with regard to network applications and discuss open issues and challenges in implementing wireless charging technologies.
Abstract: Wireless charging is a technology of transmitting power through an air gap to electrical devices for the purpose of energy replenishment. The recent progress in wireless charging techniques and development of commercial products have provided a promising alternative way to address the energy bottleneck of conventionally portable battery-powered devices. However, the incorporation of wireless charging into the existing wireless communication systems also brings along a series of challenging issues with regard to implementation, scheduling, and power management. In this paper, we present a comprehensive overview of wireless charging techniques, the developments in technical standards, and their recent advances in network applications. In particular, with regard to network applications, we review the static charger scheduling strategies, mobile charger dispatch strategies and wireless charger deployment strategies. Additionally, we discuss open issues and challenges in implementing wireless charging technologies. Finally, we envision some practical future network applications of wireless charging.
718 citations
References
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TL;DR: This paper studies a multiple-input multiple-output (MIMO) wireless broadcast system consisting of three nodes, where one receiver harvests energy and another receiver decodes information separately from the signals sent by a common transmitter, and all the transmitter and receivers may be equipped with multiple antennas.
Abstract: Wireless power transfer (WPT) is a promising new solution to provide convenient and perpetual energy supplies to wireless networks. In practice, WPT is implementable by various technologies such as inductive coupling, magnetic resonate coupling, and electromagnetic (EM) radiation, for short-/mid-/long-range applications, respectively. In this paper, we consider the EM or radio signal enabled WPT in particular. Since radio signals can carry energy as well as information at the same time, a unified study on simultaneous wireless information and power transfer (SWIPT) is pursued. Specifically, this paper studies a multiple-input multiple-output (MIMO) wireless broadcast system consisting of three nodes, where one receiver harvests energy and another receiver decodes information separately from the signals sent by a common transmitter, and all the transmitter and receivers may be equipped with multiple antennas. Two scenarios are examined, in which the information receiver and energy receiver are separated and see different MIMO channels from the transmitter, or co-located and see the identical MIMO channel from the transmitter. For the case of separated receivers, we derive the optimal transmission strategy to achieve different tradeoffs for maximal information rate versus energy transfer, which are characterized by the boundary of a so-called rate-energy (R-E) region. For the case of co-located receivers, we show an outer bound for the achievable R-E region due to the potential limitation that practical energy harvesting receivers are not yet able to decode information directly. Under this constraint, we investigate two practical designs for the co-located receiver case, namely time switching and power splitting, and characterize their achievable R-E regions in comparison to the outer bound.
2,595 citations
06 Jul 2008
TL;DR: The fundamental tradeoff between the rates at which energy and reliable information can be transmitted over a single noisy line is studied.
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1,792 citations
TL;DR: A general receiver operation, namely, dynamic power splitting (DPS), which splits the received signal with adjustable power ratio for energy harvesting and information decoding, separately is proposed and the optimal transmission strategy is derived to achieve different rate-energy tradeoffs.
Abstract: Simultaneous information and power transfer over the wireless channels potentially offers great convenience to mobile users. Yet practical receiver designs impose technical constraints on its hardware realization, as practical circuits for harvesting energy from radio signals are not yet able to decode the carried information directly. To make theoretical progress, we propose a general receiver operation, namely, dynamic power splitting (DPS), which splits the received signal with adjustable power ratio for energy harvesting and information decoding, separately. Three special cases of DPS, namely, time switching (TS), static power splitting (SPS) and on-off power splitting (OPS) are investigated. The TS and SPS schemes can be treated as special cases of OPS. Moreover, we propose two types of practical receiver architectures, namely, separated versus integrated information and energy receivers. The integrated receiver integrates the front-end components of the separated receiver, thus achieving a smaller form factor. The rate-energy tradeoff for the two architectures are characterized by a so-called rate-energy (R-E) region. The optimal transmission strategy is derived to achieve different rate-energy tradeoffs. With receiver circuit power consumption taken into account, it is shown that the OPS scheme is optimal for both receivers. For the ideal case when the receiver circuit does not consume power, the SPS scheme is optimal for both receivers. In addition, we study the performance for the two types of receivers under a realistic system setup that employs practical modulation. Our results provide useful insights to the optimal practical receiver design for simultaneous wireless information and power transfer (SWIPT).
1,610 citations
TL;DR: This work focuses on the multiaccess fading channel with Gaussian noise, and defines two notions of capacity depending on whether the traffic is delay-sensitive or not, and characterize the throughput capacity region which contains the long-term achievable rates through the time-varying channel.
Abstract: In multiaccess wireless systems, dynamic allocation of resources such as transmit power, bandwidths, and rates is an important means to deal with the time-varying nature of the environment. We consider the problem of optimal resource allocation from an information-theoretic point of view. We focus on the multiaccess fading channel with Gaussian noise, and define two notions of capacity depending on whether the traffic is delay-sensitive or not. We characterize the throughput capacity region which contains the long-term achievable rates through the time-varying channel. We show that each point on the boundary of the region can be achieved by successive decoding. Moreover, the optimal rate and power allocations in each fading state can be explicitly obtained in a greedy manner. The solution can be viewed as the generalization of the water-filling construction for single-user channels to multiaccess channels with arbitrary number of users, and exploits the underlying polymatroid structure of the capacity region.
1,216 citations