396 research outputs found
Energy-Efficient Antenna Selection and Power Allocation for Large-Scale Multiple Antenna Systems with Hybrid Energy Supply
The combination of energy harvesting and large-scale multiple antenna
technologies provides a promising solution for improving the energy efficiency
(EE) by exploiting renewable energy sources and reducing the transmission power
per user and per antenna. However, the introduction of energy harvesting
capabilities into large-scale multiple antenna systems poses many new
challenges for energy-efficient system design due to the intermittent
characteristics of renewable energy sources and limited battery capacity.
Furthermore, the total manufacture cost and the sum power of a large number of
radio frequency (RF) chains can not be ignored, and it would be impractical to
use all the antennas for transmission. In this paper, we propose an
energy-efficient antenna selection and power allocation algorithm to maximize
the EE subject to the constraint of user's quality of service (QoS). An
iterative offline optimization algorithm is proposed to solve the non-convex EE
optimization problem by exploiting the properties of nonlinear fractional
programming. The relationships among maximum EE, selected antenna number,
battery capacity, and EE-SE tradeoff are analyzed and verified through computer
simulations.Comment: IEEE Globecom 2014 Selected Areas in Communications Symposium-Green
Communications and Computing Trac
Wireless Information and Power Transfer Design for Energy Cooperation Distributed Antenna Systems
Distributed antenna systems (DASs) have been widely implemented in the state-of-the-art cellular communication systems to cover dead spots. Recent studies have also indicated that DAS has advantages in wireless energy transfer (WET). In this paper, we study simultaneous wireless information and power transfer for a multiple-input single-output DAS in the downlink, which consists of arbitrarily distributed remote antenna units (RAUs). In order to save the energy cost, we adopt the energy cooperation of energy harvesting (EH) and two-way energy flows to let the RAUs trade their harvested energy through the smart grid network. Under individual EH constraints, per-RAU power constraints, and various smart grid considerations, we investigate a power management strategy that determines how to utilize the stochastically spatially distributed harvested energy at the RAUs and how to trade the energy with the smart grid simultaneously to supply maximum wireless information transfer (WIT) with a minimum WET constraint for a receiver adopting power splitting. Our analysis shows that the optimal design can be achieved in two steps. The first step is to maximize a new objective that can simultaneously maximize both WET and WIT, considering both the smart grid profitable and smart grid neutral cases. For the grid-profitable case, we derive the optimal full power strategy and provide a closed-form result to see under what condition this strategy is used. On the other hand, for the grid-neutral case, we illustrate that the optimal power policy has a double-threshold structure and present an optimal allocation strategy. The second step is then to solve the whole problem by obtaining the splitting power ratio based on the minimum WET constraint. Simulation results are provided to evaluate the performance under various settings and characterize the double-threshold structure
GreenDelivery: Proactive Content Caching and Push with Energy-Harvesting-based Small Cells
The explosive growth of mobile multimedia traffic calls for scalable wireless
access with high quality of service and low energy cost. Motivated by the
emerging energy harvesting communications, and the trend of caching multimedia
contents at the access edge and user terminals, we propose a paradigm-shift
framework, namely GreenDelivery, enabling efficient content delivery with
energy harvesting based small cells. To resolve the two-dimensional randomness
of energy harvesting and content request arrivals, proactive caching and push
are jointly optimized, with respect to the content popularity distribution and
battery states. We thus develop a novel way of understanding the interplay
between content and energy over time and space. Case studies are provided to
show the substantial reduction of macro BS activities, and thus the related
energy consumption from the power grid is reduced. Research issues of the
proposed GreenDelivery framework are also discussed.Comment: 15 pages, 5 figures, accepted by IEEE Communications Magazin
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