10,834 research outputs found
Energy Efficiency in MIMO Underlay and Overlay Device-to-Device Communications and Cognitive Radio Systems
This paper addresses the problem of resource allocation for systems in which
a primary and a secondary link share the available spectrum by an underlay or
overlay approach. After observing that such a scenario models both cognitive
radio and D2D communications, we formulate the problem as the maximization of
the secondary energy efficiency subject to a minimum rate requirement for the
primary user. This leads to challenging non-convex, fractional problems. In the
underlay scenario, we obtain the global solution by means of a suitable
reformulation. In the overlay scenario, two algorithms are proposed. The first
one yields a resource allocation fulfilling the first-order optimality
conditions of the resource allocation problem, by solving a sequence of easier
fractional problems. The second one enjoys a weaker optimality claim, but an
even lower computational complexity. Numerical results demonstrate the merits
of the proposed algorithms both in terms of energy-efficient performance and
complexity, also showing that the two proposed algorithms for the overlay
scenario perform very similarly, despite the different complexity.Comment: to appear in IEEE Transactions on Signal Processin
Interference Management Based on RT/nRT Traffic Classification for FFR-Aided Small Cell/Macrocell Heterogeneous Networks
Cellular networks are constantly lagging in terms of the bandwidth needed to
support the growing high data rate demands. The system needs to efficiently
allocate its frequency spectrum such that the spectrum utilization can be
maximized while ensuring the quality of service (QoS) level. Owing to the
coexistence of different types of traffic (e.g., real-time (RT) and
non-real-time (nRT)) and different types of networks (e.g., small cell and
macrocell), ensuring the QoS level for different types of users becomes a
challenging issue in wireless networks. Fractional frequency reuse (FFR) is an
effective approach for increasing spectrum utilization and reducing
interference effects in orthogonal frequency division multiple access networks.
In this paper, we propose a new FFR scheme in which bandwidth allocation is
based on RT/nRT traffic classification. We consider the coexistence of small
cells and macrocells. After applying FFR technique in macrocells, the remaining
frequency bands are efficiently allocated among the small cells overlaid by a
macrocell. In our proposed scheme, total frequency-band allocations for
different macrocells are decided on the basis of the traffic intensity. The
transmitted power levels for different frequency bands are controlled based on
the level of interference from a nearby frequency band. Frequency bands with a
lower level of interference are assigned to the RT traffic to ensure a higher
QoS level for the RT traffic. RT traffic calls in macrocell networks are also
given a higher priority compared with nRT traffic calls to ensure the low
call-blocking rate. Performance analyses show significant improvement under the
proposed scheme compared with conventional FFR schemes
Energy-Efficient Resource Allocation in Multiuser OFDM Systems with Wireless Information and Power Transfer
In this paper, we study the resource allocation algorithm design for
multiuser orthogonal frequency division multiplexing (OFDM) downlink systems
with simultaneous wireless information and power transfer. The algorithm design
is formulated as a non-convex optimization problem for maximizing the energy
efficiency of data transmission (bit/Joule delivered to the users). In
particular, the problem formulation takes into account the minimum required
system data rate, heterogeneous minimum required power transfers to the users,
and the circuit power consumption. Subsequently, by exploiting the method of
time-sharing and the properties of nonlinear fractional programming, the
considered non-convex optimization problem is solved using an efficient
iterative resource allocation algorithm. For each iteration, the optimal power
allocation and user selection solution are derived based on Lagrange dual
decomposition. Simulation results illustrate that the proposed iterative
resource allocation algorithm achieves the maximum energy efficiency of the
system and reveal how energy efficiency, system capacity, and wireless power
transfer benefit from the presence of multiple users in the system.Comment: 6 pages. The paper has been accepted for publication at the IEEE
Wireless Communications and Networking Conference (WCNC) 2013, Shanghai,
China, Apr. 201
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