1,728 research outputs found
Multi-antenna Enabled Cluster-based Cooperation in Wireless Powered Communication Networks
In this paper, we consider a wireless powered communication network (WPCN)
consisting of a multi-antenna hybrid access point (HAP) that transfers wireless
energy to and receives sensing data from a cluster of low-power wireless
devices (WDs). To enhance the throughput performance of some far-away WDs, we
allow one of the WDs to act as the cluster head (CH) that helps forward the
messages of the other cluster members (CMs). However, the performance of the
proposed cluster-based cooperation is fundamentally limited by the high energy
consumption of the CH, who needs to transmit all the WDs' messages including
its own. To tackle this issue, we exploit the capability of multi-antenna
energy beamforming (EB) at the HAP, which can focus more transferred power to
the CH to balance its energy consumption in assisting the other WDs.
Specifically, we first derive the throughput performance of each individual WD
under the proposed scheme. Then, we jointly optimize the EB design, the
transmit time allocation among the HAP and the WDs, and the transmit power
allocation of the CH to maximize the minimum data rate achievable among all the
WDs (the max-min throughput) for improved throughput fairness among the WDs. An
efficient optimal algorithm is proposed to solve the joint optimization
problem. Moreover, we simulate under practical network setups and show that the
proposed multi-antenna enabled cluster-based cooperation can effectively
improve the throughput fairness of WPCN.Comment: This paper has been accepted for publication by IEEE ACCESS journal
in July 201
Reusing Wireless Power Transfer for Backscatter-assisted Cooperation in WPCN
This paper studies a novel user cooperation method in a wireless powered
communication network (WPCN), where a pair of closely located devices first
harvest wireless energy from an energy node (EN) and then use the harvested
energy to transmit information to an access point (AP). In particular, we
consider the two energy-harvesting users exchanging their messages and then
transmitting cooperatively to the AP using space-time block codes.
Interestingly, we exploit the short distance between the two users and allow
the information exchange to be achieved by energy-conserving backscatter
technique. Meanwhile the considered backscatter-assisted method can effectively
reuse wireless power transfer for simultaneous information exchange during the
energy harvesting phase. Specifically, we maximize the common throughput
through optimizing the time allocation on energy and information transmission.
Simulation results show that the proposed user cooperation scheme can
effectively improve the throughput fairness compared to some representative
benchmark methods.Comment: The paper has been accepted for publication in MLICOM 201
Optimizing Throughput Fairness of Cluster-based Cooperation in Underlay Cognitive WPCNs
In this paper, we consider a secondary wireless powered communication network
(WPCN) underlaid to a primary point-to-point communication link. The WPCN
consists of a multi-antenna hybrid access point (HAP) that transfers wireless
energy to a cluster of low-power wireless devices (WDs) and receives sensing
data from them. To tackle the inherent severe user unfairness problem in WPCN,
we consider a cluster-based cooperation where a WD acts as the cluster head
that relays the information of the other WDs. Besides, we apply energy
beamforming technique to balance the dissimilar energy consumptions of the WDs
to further improve the fairness. However, the use of energy beamforming and
cluster-based cooperation may introduce more severe interference to the primary
system than the WDs transmit independently. To guarantee the performance of
primary system, we consider an interference-temperature constraint to the
primary system and derive the throughput performance of each WD under the peak
interference-temperature constraint. To achieve maximum throughput fairness, we
jointly optimize the energy beamforming design, the transmit time allocation
among the HAP and the WDs, and the transmit power allocation of each WD to
maximize the minimum data rate achievable among the WDs (the max-min
throughput). We show that the non-convex joint optimization problem can be
transformed to a convex one and then be efficiently solved using off-the-shelf
convex algorithms. Moreover, we simulate under practical network setups and
show that the proposed method can effectively improve the throughput fairness
of the secondary WPCN, meanwhile guaranteeing the communication quality of the
primary network.Comment: The paper has been submitted for potential journal publication. arXiv
admin note: text overlap with arXiv:1707.0320
Multiuser Scheduling for Simultaneous Wireless Information and Power Transfer Systems
In this thesis, we study the downlink multiuser scheduling and power
allocation problem for systems with simultaneous wireless information and power
transfer (SWIPT). In the first part of the thesis, we focus on multiuser
scheduling. We design optimal scheduling algorithms that maximize the long-term
average system throughput under different fairness requirements, such as
proportional fairness and equal throughput fairness. In particular, the
algorithm designs are formulated as non-convex optimization problems which take
into account the minimum required average sum harvested energy in the system.
The problems are solved by using convex optimization techniques and the
proposed optimization framework reveals the tradeoff between the long-term
average system throughput and the sum harvested energy in multiuser systems
with fairness constraints. Simulation results demonstrate that substantial
performance gains can be achieved by the proposed optimization framework
compared to existing suboptimal scheduling algorithms from the literature. In
the second part of the thesis, we investigate the joint user scheduling and
power allocation algorithm design for SWIPT systems. The algorithm design is
formulated as a non-convex optimization problem which maximizes the achievable
rate subject to a minimum required average power transfer. Subsequently, the
non-convex optimization problem is reformulated by big-M method which can be
solved optimally. Furthermore, we show that joint power allocation and user
scheduling is an efficient way to enlarge the feasible trade-off region for
improving the system performance in terms of achievable data rate and harvested
energy.Comment: Master Thesis, Institute for Digital Communications,
Friedrich-Alexander-Universit\"at Erlangen-N\"urnberg, Germany
http://www.idc.lnt.de/en
Towards Optimal Resource Allocation in Wireless Powered Communication Networks with Non-Orthogonal Multiple Access
The optimal allocation of time and energy resources is characterized in a
Wireless Powered Communication Network (WPCN) with non-Orthogonal Multiple
Access (NOMA). We consider two different formulations; in the first one
(max-sum), the sum-throughput of all users is maximized. In the second one
(max-min), and targeting fairness among users, we consider maximizing the
min-throughput of all users. Under the above two formulations, two NOMA
decoding schemes are studied, namely, low complexity decoding (LCD) and
successive interference cancellation decoding (SICD). Due to the non-convexity
of three of the studied optimization problems, we consider an approximation
approach, in which the non-convex optimization problem is approximated by a
convex optimization problem, which satisfies all the constraints of the
original problem. The approximated convex optimization problem can then be
solved iteratively. The results show a trade-off between maximizing the sum
throughout and achieving fairness through maximizing the minimum throughput
Resource Allocation and Fairness in Wireless Powered Cooperative Cognitive Radio Networks
We integrate a wireless powered communication network with a cooperative
cognitive radio network, where multiple secondary users (SUs) powered
wirelessly by a hybrid access point (HAP) help a primary user relay the data.
As a reward for the cooperation, the secondary network gains the spectrum
access where SUs transmit to HAP using time division multiple access. To
maximize the sum-throughput of SUs, we present a secondary sum-throughput
optimal resource allocation (STORA) scheme. Under the constraint of meeting
target primary rate, the STORA scheme chooses the optimal set of relaying SUs
and jointly performs the time and energy allocation for SUs. Specifically, by
exploiting the structure of the optimal solution, we find the order in which
SUs are prioritized to relay primary data. Since the STORA scheme focuses on
the sum-throughput, it becomes inconsiderate towards individual SU throughput,
resulting in low fairness. To enhance fairness, we investigate three resource
allocation schemes, which are (i) equal time allocation, (ii) minimum
throughput maximization, and (iii) proportional time allocation. Simulation
results reveal the trade-off between sum-throughput and fairness. The minimum
throughput maximization scheme is the fairest one as each SU gets the same
throughput, but yields the least SU sum-throughput.Comment: Accepted in IEEE Transactions on Communication
Optimization of Energy-Constrained Wireless Powered Communication Networks with Heterogeneous Nodes
In this paper, we study wireless networks where nodes have two energy
sources, namely a battery and radio frequency (RF) energy harvesting circuitry.
We formulate two optimization problems with different objective functions,
namely maximizing the sum throughput and maximizing the minimum throughput, for
enhanced fairness. Furthermore, we show the generality of the proposed system
model through characterizing the conditions under which the two formulated
optimization problems can be reduced to the corresponding problems of different
known wireless networks, namely, conventional wireless networks
(battery-powered) and wireless powered communications networks (WPCNs) with
only RF energy harvesting nodes. In addition, we introduce WPCNs with two types
of nodes, with and without RF energy harvesting capability, in which the nodes
without RF energy harvesting are utilized to enhance the sum throughput, even
beyond WPCNs with all energy harvesting nodes. We establish the convexity of
all formulated problems which opens room for efficient solution using standard
techniques. Our numerical results show that the two types of wireless networks,
namely WPCNs with only RF energy harvesting nodes and conventional wireless
networks, are considered, respectively, as lower and upper bounds on the
performance of the generalized problem setting in terms of the maximum sum
throughput and the maxmin throughput. Moreover, the results reveal new insights
and throughput-fairness trade-offs unique to our new problem setting.Comment: Accepted for publication in Wireless Networks, 201
Resource Allocation in SWIPT Networks under a Non-Linear Energy Harvesting Model: Power Efficiency, User Fairness, and Channel Non-Reciprocity
This paper considers a multi-user simultaneous wireless information and power
transfer (SWIPT) system with a non-linear energy harvesting model, in which a
multi-antenna base station (BS) estimates the downlink channel state
information (CSI) via uplink pilots. Each single-antenna user is equipped with
a power splitter. Three crucial issues on resource management for this system
include: (i) power-efficient improvement, (ii) user-fairness guarantee, and
(iii) non-ideal channel reciprocity effect mitigation. Potentially, a resource
allocation scheme to address jointly such issues can be devised by using the
framework of multi-objective optimization. However, the resulting problem might
be complex to solve since the three issues hold different characteristics.
Therefore, we propose a novel method to design the resource allocation scheme.
In particular, the principle of our method relies on structuralizing
mathematically the issues into a cross-layer multi-level optimization problem.
On this basis, we then devise solving algorithms and closed-form solutions.
Moreover, to instantly adapt the CSI changes in practice while reducing
computational burdens, we propose a closed-form suboptimal solution to tackle
the problem. Finally, we provide numerical results to show the achievable
performance gains using the optimal and suboptimal solutions, and then validate
the proposed resource allocation scheme.Comment: This paper has been accepted for publication in IEEE Transactions on
Vehicular Technolog
On Optimal Policies in Full-Duplex Wireless Powered Communication Networks
The optimal resource allocation scheme in a full-duplex Wireless Powered
Communication Network (WPCN) composed of one Access Point (AP) and two wireless
devices is analyzed and derived. AP operates in a full-duplex mode and is able
to broadcast wireless energy signals in downlink and receive information data
in uplink simultaneously. On the other hand, each wireless device is assumed to
be equipped with Radio-Frequency (RF) energy harvesting circuitry which gathers
the energy sent by AP and stores it in a finite capacity battery. The harvested
energy is then used for performing uplink data transmission tasks. In the
literature, the main focus so far has been on slot-oriented optimization. In
this context, all the harvested RF energy in a given slot is also consumed in
the same slot. However, this approach leads to sub-optimal solutions because it
does not take into account the Channel State Information (CSI) variations over
future slots. Differently from most of the prior works, in this paper we focus
on the long-term weighted throughput maximization problem. This approach
significantly increases the complexity of the optimization problem since it
requires to consider both CSI variations over future slots and the evolution of
the batteries when deciding the optimal resource allocation. We formulate the
problem using the Markov Decision Process (MDP) theory and show how to solve
it. Our numerical results emphasize the superiority of our proposed full-duplex
WPCN compared to the half-duplex WPCN and reveal interesting insights about the
effects of perfect as well as imperfect self-interference cancellation
techniques on the network performance.Comment: Proc. IEEE Symp. Modeling and Optimization in Mobile, Ad Hoc and
Wireless Networks (WiOpt), May 201
Energy Efficient Resource Allocation for Time-Varying OFDMA Relay Systems with Hybrid Energy Supplies
This paper investigates the energy efficient resource allocation for
orthogonal frequency division multiple access (OFDMA) relay systems, where the
system is supplied by the conventional utility grid and a renewable energy
generator equipped with a storage device. The optimal usage of radio resource
depends on the characteristics of the renewable energy generation and the
mobile traffic, which exhibit both temporal and spatial diversities. Lyapunov
optimization method is used to decompose the problem into the joint flow
control, radio resource allocation and energy management without knowing a
priori knowledge of system statistics. It is proven that the proposed algorithm
can result in close-to-optimal performance with capacity limited data buffer
and storage device. Simulation results show that the flexible tradeoff between
the system utility and the conventional energy consumption can be achieved.
Compared with other schemes, the proposed algorithm demonstrates better
performance.Comment: 12 pages, 9 figures, IEEE System Journa
- …