44 research outputs found
Flexible resource allocation for joint optimization of energy and spectral efficiency in OFDMA multi-cell networks
The radio resource allocation problem is studied, aiming to jointly optimize the energy efficiency (EE) and spectral efficiency (SE) of downlink OFDMA multi-cell networks. Different from existing works on either EE or SE optimization, a novel EE-SE tradeoff (EST) metric, which can capture both the EST relation and the individual cells’ preferences for EE or SE performance, is introduced as the utility function for each base station (BS). Then the joint EE-SE optimization problem is formulated, and an iterative subchannel allocation and power allocation algorithm is proposed. Numerical results show that the proposed algorithm can exploit the EST relation flexibly and optimize the EE and SE simultaneously to meet diverse EE and SE preferences of individual cells.<br/
Distributed power control over interference channels using ACK/NACK feedback
In this work, we consider a network composed of several single-antenna
transmitter-receiver pairs in which each pair aims at selfishly minimizing the
power required to achieve a given signal-to-interference-plus-noise ratio. This
is obtained modeling the transmitter-receiver pairs as rational agents that
engage in a non-cooperative game. Capitalizing on the well-known results on the
existence and structure of the generalized Nash equilibrium (GNE) point of the
underlying game, a low complexity, iterative and distributed algorithm is
derived to let each terminal reach the GNE using only a limited feedback in the
form of link-layer acknowledgement (ACK) or negative acknowledgement (NACK).
Numerical results are used to prove that the proposed solution is able to
achieve convergence in a scalable and adaptive manner under different operating
conditions.Comment: 5 pages, 6 figures, IEEE Global Communications Conference (GLOBECOM),
Austin, Texas, Dec. 201
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
Distributed Interference-Aware Energy-Efficient Resource Allocation for Device-to-Device Communications Underlaying Cellular Networks
The introduction of device-to-device (D2D) into cellular networks poses many
new challenges in the resource allocation design due to the co-channel
interference caused by spectrum reuse and limited battery life of user
equipments (UEs). In this paper, we propose a distributed interference-aware
energy-efficient resource allocation algorithm to maximize each UE's energy
efficiency (EE) subject to its specific quality of service (QoS) and maximum
transmission power constraints. We model the resource allocation problem as a
noncooperative game, in which each player is self-interested and wants to
maximize its own EE. The formulated EE maximization problem is a non-convex
problem and is transformed into a convex optimization problem by exploiting the
properties of the nonlinear fractional programming. An iterative optimization
algorithm is proposed and verified through computer simulations.Comment: 6 pages, 3 figures, IEEE GLOBECOM 201
Energy Efficiency and Spectral Efficiency Tradeoff in Device-to-Device (D2D) Communications
In this letter, we investigate the tradeoff between energy efficiency (EE)
and spectral efficiency (SE) in device-to-device (D2D) communications
underlaying cellular networks with uplink channel reuse. The resource
allocation problem is modeled as a noncooperative game, in which each user
equipment (UE) is self-interested and wants to maximize its own EE. Given the
SE requirement and maximum transmission power constraints, a distributed
energy-efficient resource allocation algorithm is proposed by exploiting the
properties of the nonlinear fractional programming. The relationships between
the EE and SE tradeoff of the proposed algorithm and system parameters are
analyzed and verified through computer simulations.Comment: 8 pages, 6 figures, long version paper of IEEE Wireless
Communications Letters, accepted for publication. arXiv admin note: text
overlap with arXiv:1405.196
Energy-Efficient Power Control for Contention-Based Synchronization in OFDMA Systems with Discrete Powers and Limited Feedback
This work derives a distributed and iterative algorithm by which mobile
terminals can selfishly control their transmit powers during the
synchronization procedure specified by the IEEE 802.16m and the 3GPP-LTE
standards for orthogonal frequency-division multiple-access technologies. The
proposed solution aims at maximizing the energy efficiency of the network and
is derived on the basis of a finite noncooperative game in which the players
have discrete action sets of transmit powers. The set of Nash equilibria of the
game is investigated, and a distributed power control algorithm is proposed to
achieve synchronization in an energy-efficient manner under the assumption that
the feedback from the base station is limited. Numerical results show that the
proposed solution improves the energy efficiency as well as the timing
estimation accuracy of the network compared to existing alternatives, while
requiring a reasonable amount of information to be exchanged on the return
channel
Non-cooperative power control for energy-efficient and delay-aware wireless networks
This work aims at developing a distributed power control algorithm for energy efficiency maximization (measured in bit/Joule) in wireless networks. Unlike most previous works, a new formulation is proposed to jointly account for the energy efficiency and communication delay while ensuring quality-of-service constraints. A non-cooperative game-theoretic approach is taken, and feasibility conditions are derived for the best-response of the game. Under the assumption that these conditions are met, it is shown that the game admits a unique Nash equilibrium, which is guaranteed to be reached by implementing the game best-response dynamics. Based on these results, a convergent power control algorithm is derived, which can be implemented in a fully decentralized fashion