2,765 research outputs found
Feedback Enhances Simultaneous Wireless Information and Energy Transmission in Multiple Access Channels
International audienceIn this paper, the fundamental limits of simultaneous information and energy transmission in the two-user Gaussian multiple access channel (G-MAC) with and without feedback are fully characterized. More specifically, all the achievable information and energy transmission rates (in bits per channel use and energy-units per channel use, respectively) are identified. Furthermore, the fundamental limits on the individual and sum-rates given a minimum energy rate ensured at an energy harvester are also characterized. In the case without feedback, an achievability scheme based on power-splitting and successive interference cancellation is shown to be optimal. Alternatively, in the case with feedback (G-MAC-F), a simple yet optimal achievability scheme based on power-splitting and Ozarow's capacity achieving scheme is presented. Finally, the energy transmission enhancement induced by the use of feedback is quantified. Feedback can at most double the energy transmission rate at high SNRs when the information transmission sum-rate is kept fixed at the sum-capacity of the G-MAC, but it has no effect at very low SNRs. Index Terms—Feedback, Gaussian multiple access channel, simultaneous information and energy transmission, RF harvesting, information-energy capacity region
Feedback Enhances Simultaneous Wireless Information and Energy Transmission in Multiple Access Channels
In this report, the fundamental limits of simultaneous information and energy
transmission in the two-user Gaussian multiple access channel (G-MAC) with and
without feedback are fully characterized. More specifically, all the achievable
information and energy transmission rates (in bits per channel use and
energy-units per channel use, respectively) are identified. Furthermore, the
fundamental limits on the individual and sum- rates given a minimum energy rate
ensured at an energy harvester are also characterized. In the case without
feedback, an achievability scheme based on power-splitting and successive
interference cancellation is shown to be optimal. Alternatively, in the case
with feedback (G-MAC-F), a simple yet optimal achievability scheme based on
power-splitting and Ozarow's capacity achieving scheme is presented. Finally,
the energy transmission enhancement induced by the use of feedback is
quantified. Feedback can at most double the energy transmission rate at high
SNRs when the information transmission sum-rate is kept fixed at the
sum-capacity of the G-MAC, but it has no effect at very low SNRs.Comment: INRIA REPORT N{\deg}8804, accepted for publication in IEEE
transactions on Information Theory, March, 201
Energy Harvesting Wireless Communications: A Review of Recent Advances
This article summarizes recent contributions in the broad area of energy
harvesting wireless communications. In particular, we provide the current state
of the art for wireless networks composed of energy harvesting nodes, starting
from the information-theoretic performance limits to transmission scheduling
policies and resource allocation, medium access and networking issues. The
emerging related area of energy transfer for self-sustaining energy harvesting
wireless networks is considered in detail covering both energy cooperation
aspects and simultaneous energy and information transfer. Various potential
models with energy harvesting nodes at different network scales are reviewed as
well as models for energy consumption at the nodes.Comment: To appear in the IEEE Journal of Selected Areas in Communications
(Special Issue: Wireless Communications Powered by Energy Harvesting and
Wireless Energy Transfer
Optimal Energy Allocation For Delay-Constrained Traffic Over Fading Multiple Access Channels
In this paper, we consider a multiple-access fading channel where users
transmit to a single base station (BS) within a limited number of time slots.
We assume that each user has a fixed amount of energy available to be consumed
over the transmission window. We derive the optimal energy allocation policy
for each user that maximizes the total system throughput under two different
assumptions on the channel state information. First, we consider the offline
allocation problem where the channel states are known a priori before
transmission. We solve a convex optimization problem to maximize the
sum-throughput under energy and delay constraints. Next, we consider the online
allocation problem, where the channels are causally known to the BS and obtain
the optimal energy allocation via dynamic programming when the number of users
is small. We also develop a suboptimal resource allocation algorithm whose
performance is close to the optimal one. Numerical results are presented
showing the superiority of the proposed algorithms over baseline algorithms in
various scenarios.Comment: IEEE Global Communications Conference: Wireless Communications
(Globecom2016 WC
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