1,904 research outputs found
Energy Efficient Coordinated Beamforming for Multi-cell MISO Systems
In this paper, we investigate the optimal energy efficient coordinated
beamforming in multi-cell multiple-input single-output (MISO) systems with
multiple-antenna base stations (BS) and single-antenna mobile stations
(MS), where each BS sends information to its own intended MS with cooperatively
designed transmit beamforming. We assume single user detection at the MS by
treating the interference as noise. By taking into account a realistic power
model at the BS, we characterize the Pareto boundary of the achievable energy
efficiency (EE) region of the links, where the EE of each link is defined
as the achievable data rate at the MS divided by the total power consumption at
the BS. Since the EE of each link is non-cancave (which is a non-concave
function over an affine function), characterizing this boundary is difficult.
To meet this challenge, we relate this multi-cell MISO system to cognitive
radio (CR) MISO channels by applying the concept of interference temperature
(IT), and accordingly transform the EE boundary characterization problem into a
set of fractional concave programming problems. Then, we apply the fractional
concave programming technique to solve these fractional concave problems, and
correspondingly give a parametrization for the EE boundary in terms of IT
levels. Based on this characterization, we further present a decentralized
algorithm to implement the multi-cell coordinated beamforming, which is shown
by simulations to achieve the EE Pareto boundary.Comment: 6 pages, 2 figures, to be presented in IEEE GLOBECOM 201
An Energy Efficient Semi-static Power Control and Link Adaptation Scheme in UMTS HSDPA
High speed downlink packet access (HSDPA) has been successfully applied in
commercial systems and improves user experience significantly. However, it
incurs substantial energy consumption. In this paper, we address this issue by
proposing a novel energy efficient semi-static power control and link
adaptation scheme in HSDPA. Through estimating the EE under different
modulation and coding schemes (MCSs) and corresponding transmit power, the
proposed scheme can determine the most energy efficient MCS level and transmit
power at the Node B. And then the Node B configure the optimal MCS level and
transmit power. In order to decrease the signaling overhead caused by the
configuration, a dual trigger mechanism is employed. After that, we extend the
proposed scheme to the multiple input multiple output (MIMO) scenarios.
Simulation results confirm the significant EE improvement of our proposed
scheme. Finally, we give a discussion on the potential EE gain and challenge of
the energy efficient mode switching between single input multiple output (SIMO)
and MIMO configuration in HSDPA.Comment: 9 pages, 11 figures, accepted in EURASIP Journal on Wireless
Communications and Networking, special issue on Green Radi
Capacity of UAV-Enabled Multicast Channel: Joint Trajectory Design and Power Allocation
This paper studies an unmanned aerial vehicle (UAV)-enabled multicast
channel, in which a UAV serves as a mobile transmitter to deliver common
information to a set of ground users. We aim to characterize the capacity
of this channel over a finite UAV communication period, subject to its maximum
speed constraint and an average transmit power constraint. To achieve the
capacity, the UAV should use a sufficiently long code that spans over its whole
communication period. Accordingly, the multicast channel capacity is achieved
via maximizing the minimum achievable time-averaged rates of the users, by
jointly optimizing the UAV's trajectory and transmit power allocation over
time. However, this problem is non-convex and difficult to be solved optimally.
To tackle this problem, we first consider a relaxed problem by ignoring the
maximum UAV speed constraint, and obtain its globally optimal solution via the
Lagrange dual method. The optimal solution reveals that the UAV should hover
above a finite number of ground locations, with the optimal hovering duration
and transmit power at each location. Next, based on such a
multi-location-hovering solution, we present a successive hover-and-fly
trajectory design and obtain the corresponding optimal transmit power
allocation for the case with the maximum UAV speed constraint. Numerical
results show that our proposed joint UAV trajectory and transmit power
optimization significantly improves the achievable rate of the UAV-enabled
multicast channel, and also greatly outperforms the conventional multicast
channel with a fixed-location transmitter.Comment: To appear in the IEEE International Conference on Communications
(ICC), 201
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