Source-linked AI summary
Wireless Powered Communication Networks: An Overview
Suzhi Bi, Yong Zeng, Rui Zhang
TL;DR
WPCNs address battery replacement needs but face challenges from long-distance WPT inefficiency and joint information-power transfer. This article surveys WPCN models and performance-enhancing techniques, reporting throughput improvements over conventional and environmental-energy-harvesting communications.
Problem
WPCNs must overcome low long-distance WPT efficiency and the complex joint transfer of wireless information and power.
Method
The article provides an overview of WPCN components, network models, and state-of-the-art performance-enhancing techniques.
Results
WPCN significantly improves throughput compared with battery-powered and environmental-energy-harvesting communications.
Takeaways & Limitations
The overview organizes basic WPCN models and corresponding techniques for building efficient WPCNs.
Abstract
from arXiv · showhide
Wireless powered communication network (WPCN) is a new networking paradigm where the battery of wireless communication devices can be remotely replenished by means of microwave wireless power transfer (WPT) technology. WPCN eliminates the need of frequent manual battery replacement/recharging, and thus significantly improves the performance over conventional battery-powered communication networks in many aspects, such as higher throughput, longer device lifetime, and lower network operating cost. However, the design and future application of WPCN is essentially challenged by the low WPT efficiency over long distance and the complex nature of joint wireless information and power transfer within the same network. In this article, we provide an overview of the key networking structures and performance enhancing techniques to build an efficient WPCN. Besides, we point out new and challenging future research directions for WPCN.
I. INTRODUCTION
WPCN uses microwave WPT to replenish wireless-device batteries remotely, offering stable power and potential gains in lifetime, throughput, and operating cost. Its practical design must address low long-distance transfer efficiency and the joint optimization of wireless energy and information transmissions.
- I. INTRODUCTION: WPCN remotely replenishes wireless devices over the air using microwave wireless power transfer.Current WPT can transfer tens of microwatts of RF power over distances exceeding 10 meters.
- I. INTRODUCTION: WPCN can eliminate manual battery replacement or recharging, reduce operational cost, and support uninterrupted operation in wireless sensor networks.WPT-enabled WSNs can power massive numbers of sensors through fixed transmitters or vehicles following routes for charging and data collection.
- I. INTRODUCTION: WPT provides controllable transmit power, waveforms, and occupied time or frequency, enabling stable energy supply under varying physical conditions and service requirements.This contrasts with environmental energy harvesting, whose availability and strength are mostly random and time varying.
- I. INTRODUCTION: WPT-enabled RFID devices can achieve longer operating lifetimes and transmit at higher data rates and longer distances than conventional backscatter-based devices.The passage attributes these capabilities to the more ample power supply from WPT.
- I. INTRODUCTION: Efficient WPCN design is challenging because microwave attenuation lowers received energy for distant devices, creating near-far unfairness, while energy and information transmissions interact and may interfere.Wireless devices must harvest enough energy before transmitting data, and shared spectrum can cause co-channel interference.
- I. INTRODUCTION: The article surveys WPCN components, network models, performance-enhancing techniques, extensions, and future research directions.It aims to identify physical-layer techniques and networking protocols for efficient WPCNs.
II. BASIC MODELS OF WPCN
WPCN designs combine wireless energy delivery with information transmission through separated or co-located network elements and out-band, in-band, or full-duplex operation. These choices trade user fairness, spectrum efficiency, throughput, and interference management.
- WPCNs use energy nodes to power wireless devices in the downlink, after which devices transmit data to information access points in the uplink.
- Separating energy nodes and access points can alleviate the energy near-far effect because distant users may harvest less energy but also expend less uplink transmission power.
- Practical WPT-enabled devices and hybrid access points generally use separate antenna systems for energy and information transmission because their receiver requirements and circuit structures differ.An information receiver may operate at −60 dBm, whereas an energy receiver may require up to −10 dBm.
- Out-band transmission avoids interference by using different frequency bands, whereas in-band transmission improves spectrum efficiency but can create co-channel or self-interference.Time separation mitigates interference but reduces the time available for information transmission and therefore system throughput.
- Full-duplex wireless devices can simultaneously harvest energy and transmit information, including self-energy recycling from their own transmitted signal when loop-link conditions permit.Full-duplex hybrid access points require interference mitigation because energy transmission can strongly interfere with information decoding.
- Full-duplex HAPs with 80 dB self-interference cancellation strictly outperform half-duplex HAPs, while 50 dB cancellation can yield close-to-zero data rates under moderate separation.For separated energy and information nodes, 80 dB interference cancellation also gives higher data rate than half-duplex operation, whereas 50 dB gives lower data rate.
III. KEY TECHNIQUES FOR WPCN
WPCN performance is limited by inefficient, short-range wireless power transfer and constrained energy and information resources. The overview organizes enhancement approaches around beamforming, scheduling, cooperation, and multi-node coordination.
- WPCNs are fundamentally constrained by the low efficiency and short range of wireless power transfer and by limited resources for energy and information transmission.
- The paper introduces energy beamforming, joint communication and energy scheduling, wireless powered cooperative communication, and multi-node cooperation as performance-enhancing techniques.
- The introduced techniques and their combinations can extend WPCN operating range and increase capacity, supporting more extensive applications.
A. Energy Beamforming
Energy beamforming directs weighted energy signals toward receivers, but its effectiveness depends on channel knowledge that is costly for energy-limited or hardware-constrained receivers. Reverse-link and limited-feedback methods reduce this overhead.
- Energy Beamforming: Energy beamforming weights signals across transmit antennas to create constructive superposition at intended energy receivers and generally requires accurate channel state information.
- Energy Beamforming: Channel training for wireless power transfer is constrained by receiver energy, because estimation and CSI feedback consume energy that may offset beamforming gains.
- Energy Beamforming: With large transmit arrays, reverse-link training estimates CSI directly at the energy transmitter and makes training overhead independent of the transmitter’s antenna count.
- Energy Beamforming: Low-cost energy receivers may lack adequate baseband processing for conventional CSI estimation or feedback, motivating limited-feedback methods.
- Energy Beamforming: A one-bit increase-or-decrease power signal can guide iterative channel-matrix updates with a cutting-plane algorithm, which is proved to converge to the exact matrix after finitely many steps.
B. Joint Communication and Energy Scheduling
WPCN communication and energy transmissions must be jointly scheduled because harvested energy constrains later uplink communication and both compete for shared resources. Scheduling can adapt across time, frequency, and space to account for channels, battery states, demands, and fairness.
- Joint scheduling: Uplink information transmission is causally constrained by the energy available after downlink wireless power transfer.Joint scheduling avoids co-channel interference while coordinating energy delivery with subsequent information transmission.
- Joint scheduling: Time-frequency resource blocks can be dynamically assigned either to downlink energy transfer or uplink information transmission.Allocation considers wireless channel conditions, battery states, communication demands, and fairness among wireless devices.
- Dynamic allocation: Far-user fairness can be improved by allocating more resource blocks to far user WD2 and fewer to near user WD1.Poor fading conditions can also leave some resource blocks unused, motivating dynamic allocation methods.
- Dynamic allocation: Real-time information and energy scheduling is challenging because wireless channels vary over time and current wireless power transfer affects future information transmissions.The causal relationship between present charging and later communication complicates online decisions.
- Spatial scheduling: Energy beamforming steers stronger energy beams toward selected users, while SDMA allows multiple users to transmit on the same time-frequency resource block.Uplink transmit-power control can balance throughput, and combining beamforming and SDMA with dynamic allocation can further enhance performance.
C. Wireless Powered Cooperative Communication
Wireless powered cooperative communication lets users share energy, time, or communication resources to improve WPCN performance. Cooperation can shorten the far user's communication range, provide more data-transmission time, and support energy sharing.
- Cooperation mechanisms: Wireless powered cooperative communication is presented as a promising approach for improving WPCN performance.Users may cooperate through communication or peer-to-peer energy transfer after harvesting energy.
- Communication cooperation: A near user with ample energy can relay a far user's data through a three-slot protocol involving WPT, inter-user transmission, and forwarding to the HAP.WD2 first sends data to WD1, which combines WD2's message with its own before transmitting to the HAP.
- Communication cooperation: WD2 benefits from cooperation because the relay path provides a shorter communication range than direct transmission to the HAP.The near user spends energy and transmission time helping WD2, while the resulting data-rate loss can be offset by longer overall data-transmission time.
- Cooperation gains: User cooperation can let the HAP allocate more time to data transmission instead of WPT, improving overall WPCN efficiency.The stated gain from cooperation can compensate for the helper's energy and time expenditure.
- Energy cooperation: Peer-to-peer energy cooperation allows one user to transmit excessive energy directly to another user.Communication links between cooperating users must be sufficiently reliable for spectrally efficient methods such as distributed space-time coding.
D. Multi-node Cooperation
Multi-node cooperation coordinates energy transmitters and information access points to improve WPCN performance, but centralized processing can be costly at large scale. Joint node placement and hybrid processing address performance and implementation trade-offs.
- Multi-node cooperation: Multiple ENs and information APs can cooperate to improve energy and information-transfer efficiency.They exchange user data and control signals over wired or wireless backhaul links to serve wireless devices collaboratively.
- Multi-node cooperation: Collaborating ENs form a virtual MIMO system for distributed energy beamforming, while collaborating APs form a coordinated multi-point system for joint message decoding.These mechanisms target received energy at wireless devices and combine signals across multiple access points.
- Centralized processing: Concurrent downlink energy transfer and uplink information transmission can share the same frequency band without interference when APs cancel predetermined energy signals.The centralized scheme provides downlink beamforming gain and uplink spatial diversity or multiplexing gain.
- Processing trade-offs: Centralized processing can be very costly in large WPCNs because of computational complexity, control-signaling overhead, backhaul traffic, and synchronization requirements.A hybrid scheme integrating centralized and distributed processing may balance performance against implementation cost.
- Node placement: Node placement determines the number and locations of ENs and APs needed to satisfy energy-harvesting and communication-performance requirements.ENs can be placed near distant wireless devices to replenish high energy consumption, while EN and AP placements should be jointly optimized for throughput, lifetime, and deployment cost.
IV. EXTENSIONS AND FUTURE DIRECTIONS
WPCN contains additional research problems with important applications that remain insufficiently studied. The paper highlights several future topics as especially worth investigating.
- Future directions: WPCN entails rich research problems with important applications that remain to be studied.The paper identifies several topics it considers particularly worth investigating.
A. Extensions
The overview extends WPCN designs through energy beamforming, full-duplex operation, cooperative relaying, and clustered structures, while identifying practical challenges involving channel knowledge, nonlinear conversion, and battery imbalance.
- Energy beamforming: Energy beamforming is a key WPCN technique, but efficient design requires accurate channel state information at the energy transmitter.Limited energy or simplified hardware at energy receivers can make this information unavailable, motivating reverse-link training, limited feedback, and imperfect- or statistical-CSIT designs.
- Energy beamforming: Practical energy beamforming must also account for nonlinear energy conversion efficiency, which varies with received RF power.Efficiency generally increases with received power and degrades above a certain received-power level.
- Full-duplex operation: Full-duplex HAPs can transfer energy while receiving data on the same frequency band, avoiding orthogonal time or frequency allocation used in half-duplex systems.Full-duplex cooperative communication similarly allows a WD to transmit data while receiving concurrent energy and collaborative data, provided interference can be effectively canceled.
- Cooperative and clustered WPCNs: Cluster-based WPCNs use near users as relays and coordinators for groups of users with poor direct WD-to-HAP links.Cluster heads may quickly deplete their batteries, so proposed remedies include targeted energy beamforming and opportunistic direct communication by non-cluster-head nodes.
- Full-duplex operation: Full-duplex operation is defined here as self-interference cancellation together with simultaneous energy harvesting and information transmission.This capability underlies the full-duplex extensions described for HAPs and WDs.
B. Green WPCN
Green WPCNs combine renewable energy harvesting with WPT to reduce reliance on fixed power sources, but their operation must adapt to variable renewable supply, battery states, and channel conditions.
- Hybrid energy sources: Energy harvesting can be combined with WPT to build a green and self-sustainable WPCN.Harvesting may occur at both energy nodes and wireless devices, including solar power and ambient RF radiation stored in rechargeable batteries.
- Hybrid energy sources: When renewable energy is strong, energy nodes can turn off WPT, while conventional WPT can power devices when harvesting is infeasible.A hybrid mode can combine both sources, with transmit-power control or energy beamforming used to concentrate energy.
- Design challenges: The key hybrid-source challenge is timely switching among operating modes and efficient energy transmission while meeting communication requirements.The objective includes minimizing energy drawn from fixed power sources.
- Design challenges: Optimal green-WPCN design must jointly consider renewable-energy intensity, battery-state information, and wireless-channel conditions.The supplied discussion identifies this joint design as open to future investigation.
C. Cognitive WPCN
Cognitive WPCNs address coexistence with existing communication networks by sharing spectrum while managing interference, using cooperative or noncooperative transmission strategies.
- Coexistence models: WPCNs may coexist with existing communication networks and can operate cooperatively or noncooperatively with them.Cooperative designs protect existing communications, whereas noncooperative designs prioritize their own performance while secondarily minimizing impact on incumbent networks.
- Spectrum sharing: Simultaneous operation on a shared frequency band can create harmful co-channel interference in both networks.The WPCN can interfere with information decoding in the existing network, while the existing network can interfere with HAP decoding.
- Spectrum sharing: Existing-network transmissions can simultaneously provide additional harvestable energy to WPCN users despite interfering with HAP information decoding.This dual effect motivates cognitive spectrum sharing under limited operating spectrum.
- Conclusions: The overview presents basic WPCN models and performance-enhancing techniques for building efficient networks.It concludes that WPCNs improve throughput and reliability relative to battery-powered and environment-energy-harvesting communications.
- Conclusions: The additional energy-transfer dimension requires more sophisticated system design while creating opportunities to address energy scarcity in wireless communications.The article foresees WPCN as an important building block for energy-self-sustainable future wireless systems.