3,661 research outputs found
Energy-Efficient NOMA Enabled Heterogeneous Cloud Radio Access Networks
Heterogeneous cloud radio access networks (H-CRANs) are envisioned to be
promising in the fifth generation (5G) wireless networks. H-CRANs enable users
to enjoy diverse services with high energy efficiency, high spectral
efficiency, and low-cost operation, which are achieved by using cloud computing
and virtualization techniques. However, H-CRANs face many technical challenges
due to massive user connectivity, increasingly severe spectrum scarcity and
energy-constrained devices. These challenges may significantly decrease the
quality of service of users if not properly tackled. Non-orthogonal multiple
access (NOMA) schemes exploit non-orthogonal resources to provide services for
multiple users and are receiving increasing attention for their potential of
improving spectral and energy efficiency in 5G networks. In this article a
framework for energy-efficient NOMA H-CRANs is presented. The enabling
technologies for NOMA H-CRANs are surveyed. Challenges to implement these
technologies and open issues are discussed. This article also presents the
performance evaluation on energy efficiency of H-CRANs with NOMA.Comment: This work has been accepted by IEEE Network. Pages 18, Figure
Employing Antenna Selection to Improve Energy-Efficiency in Massive MIMO Systems
Massive MIMO systems promise high data rates by employing large number of
antennas, which also increases the power usage of the system as a consequence.
This creates an optimization problem which specifies how many antennas the
system should employ in order to operate with maximal energy efficiency. Our
main goal is to consider a base station with a fixed number of antennas, such
that the system can operate with a smaller subset of antennas according to the
number of active user terminals, which may vary over time. Thus, in this paper
we propose an antenna selection algorithm which selects the best antennas
according to the better channel conditions with respect to the users, aiming at
improving the overall energy efficiency. Then, due to the complexity of the
mathematical formulation, a tight approximation for the consumed power is
presented, using the Wishart theorem, and it is used to find a deterministic
formulation for the energy efficiency. Simulation results show that the
approximation is quite tight and that there is significant improvement in terms
of energy efficiency when antenna selection is employed.Comment: To appear in Transactions on Emerging Telecommunications
Technologies, 12 pages, 8 figures, 2 table
Multi-Objective Optimization for Power Efficient Full-Duplex Wireless Communication Systems
In this paper, we investigate power efficient resource allocation algorithm
design for multiuser wireless communication systems employing a full-duplex
(FD) radio base station for serving multiple half-duplex (HD) downlink and
uplink users simultaneously. We propose a multi-objective optimization
framework for achieving two conflicting yet desirable system design objectives,
i.e., total downlink transmit power minimization and total uplink transmit
power minimization, while guaranteeing the quality-of-service of all users. To
this end, the weighted Tchebycheff method is adopted to formulate a
multi-objective optimization problem (MOOP). Although the considered MOOP is
non-convex, we solve it optimally by semidefinite programming relaxation.
Simulation results not only unveil the trade-off between the total downlink and
the total uplink transmit power, but also confirm that the proposed FD system
provides substantial power savings over traditional HD systems.Comment: Accepted for presentation at the IEEE Globecom 2015, San Diego, CA,
USA, Dec. 201
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