10,376 research outputs found
Cooperative Energy Trading in CoMP Systems Powered by Smart Grids
This paper studies the energy management in the coordinated multi-point
(CoMP) systems powered by smart grids, where each base station (BS) with local
renewable energy generation is allowed to implement the two-way energy trading
with the grid. Due to the uneven renewable energy supply and communication
energy demand over distributed BSs as well as the difference in the prices for
their buying/selling energy from/to the gird, it is beneficial for the
cooperative BSs to jointly manage their energy trading with the grid and energy
consumption in CoMP based communication for reducing the total energy cost.
Specifically, we consider the downlink transmission in one CoMP cluster by
jointly optimizing the BSs' purchased/sold energy units from/to the grid and
their cooperative transmit precoding, so as to minimize the total energy cost
subject to the given quality of service (QoS) constraints for the users. First,
we obtain the optimal solution to this problem by developing an algorithm based
on techniques from convex optimization and the uplink-downlink duality. Next,
we propose a sub-optimal solution of lower complexity than the optimal
solution, where zero-forcing (ZF) based precoding is implemented at the BSs.
Finally, through extensive simulations, we show the performance gain achieved
by our proposed joint energy trading and communication cooperation schemes in
terms of energy cost reduction, as compared to conventional schemes that
separately design communication cooperation and energy trading
Energy Beamforming with One-Bit Feedback
Wireless energy transfer (WET) has attracted significant attention recently
for providing energy supplies wirelessly to electrical devices without the need
of wires or cables. Among different types of WET techniques, the radio
frequency (RF) signal enabled far-field WET is most practically appealing to
power energy constrained wireless networks in a broadcast manner. To overcome
the significant path loss over wireless channels, multi-antenna or
multiple-input multiple-output (MIMO) techniques have been proposed to enhance
the transmission efficiency and distance for RF-based WET. However, in order to
reap the large energy beamforming gain in MIMO WET, acquiring the channel state
information (CSI) at the energy transmitter (ET) is an essential task. This
task is particularly challenging for WET systems, since existing channel
training and feedback methods used for communication receivers may not be
implementable at the energy receiver (ER) due to its hardware limitation. To
tackle this problem, in this paper we consider a multiuser MIMO system for WET,
where a multiple-antenna ET broadcasts wireless energy to a group of
multiple-antenna ERs concurrently via transmit energy beamforming. By taking
into account the practical energy harvesting circuits at the ER, we propose a
new channel learning method that requires only one feedback bit from each ER to
the ET per feedback interval. The feedback bit indicates the increase or
decrease of the harvested energy by each ER between the present and previous
intervals, which can be measured without changing the existing hardware at the
ER. Based on such feedback information, the ET adjusts transmit beamforming in
different training intervals and at the same time obtains improved estimates of
the MIMO channels to ERs by applying a new approach termed analytic center
cutting plane method (ACCPM).Comment: This is the longer version of a paper to appear in IEEE Transactions
on Signal Processin
Cost-Aware Green Cellular Networks with Energy and Communication Cooperation
Energy cost of cellular networks is ever-increasing to match the surge of
wireless data traffic, and the saving of this cost is important to reduce the
operational expenditure (OPEX) of wireless operators in future. The recent
advancements of renewable energy integration and two-way energy flow in smart
grid provide potential new solutions to save the cost. However, they also
impose challenges, especially on how to use the stochastically and spatially
distributed renewable energy harvested at cellular base stations (BSs) to
reliably supply time- and space-varying wireless traffic over cellular
networks. To overcome these challenges, in this article we present three
approaches, namely, {\emph{energy cooperation, communication cooperation, and
joint energy and communication cooperation}}, in which different BSs
bidirectionally trade or share energy via the aggregator in smart grid, and/or
share wireless resources and shift loads with each other to reduce the total
energy cost.Comment: Submitted for possible publicatio
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