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Throughput Maximization in Wireless Powered Communication Networks

Hyungsik Ju, +1 more
- Vol. 13, Iss: 1, pp 418-428
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TLDR
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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Citations
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Energy efficiency optimization-based resource allocation for underlay RF-CRN with residual energy and QoS guarantee

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Energy-Efficient Resource Allocation for Energy Harvesting-Powered D2D Communications Underlaying Cellular Networks

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Wireless Information and Power Transfer: Nonlinearity, Waveform Design and Rate-Energy Tradeoff

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References
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Journal ArticleDOI

MIMO Broadcasting for Simultaneous Wireless Information and Power Transfer

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.
Proceedings ArticleDOI

Transporting information and energy simultaneously

TL;DR: The fundamental tradeoff between the rates at which energy and reliable information can be transmitted over a single noisy line is studied.
Journal ArticleDOI

Wireless Information and Power Transfer: Architecture Design and Rate-Energy Tradeoff

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.
Journal ArticleDOI

Multiaccess fading channels. I. Polymatroid structure, optimal resource allocation and throughput capacities

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.
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