789 research outputs found
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
On the resource allocation for D2D underlaying uplink cellular networks
Device-to-Device (D2D) communications has attracted research interests as an emerging technology towards 5G and beyond cellular networks. In this paper, we investigate the power allocation in D2D underlaying cellular networks with uplink channel reuse. We first develop an optimization problem to minimize the total power consumption subject to per- user Quality-of-Service (QoS) constraints. A distributed power allocation algorithm is proposed to allocate the power for both D2D and cellular users by exploiting the property of strictly non-negative inverse of a Z-matrix. It is shown that the power allocated for users can be considerably saved for low QoS requirements, especially with a large number of D2D users. The proposed algorithm is validated through simulation to realize the impacts of noise power, distance between D2D users and the number of D2D pairs in the network
Distributed power allocation for D2D communications underlaying/overlaying OFDMA cellular networks
The implementation of device-to-device (D2D) underlaying or overlaying
pre-existing cellular networks has received much attention due to the potential
of enhancing the total cell throughput, reducing power consumption and
increasing the instantaneous data rate. In this paper we propose a distributed
power allocation scheme for D2D OFDMA communications and, in particular, we
consider the two operating modes amenable to a distributed implementation:
dedicated and reuse modes. The proposed schemes address the problem of
maximizing the users' sum rate subject to power constraints, which is known to
be nonconvex and, as such, extremely difficult to be solved exactly. We propose
here a fresh approach to this well-known problem, capitalizing on the fact that
the power allocation problem can be modeled as a potential game. Exploiting the
potential games property of converging under better response dynamics, we
propose two fully distributed iterative algorithms, one for each operation mode
considered, where each user updates sequentially and autonomously its power
allocation. Numerical results, computed for several different user scenarios,
show that the proposed methods, which converge to one of the local maxima of
the objective function, exhibit performance close to the maximum achievable
optimum and outperform other schemes presented in the literature
On the resource allocation for D2D underlaying uplink cellular networks
Device-to-Device (D2D) communications has attracted research interests as an emerging technology towards 5G and beyond cellular networks. In this paper, we investigate the power allocation in D2D underlaying cellular networks with uplink channel reuse. We first develop an optimization problem to minimize the total power consumption subject to per- user Quality-of-Service (QoS) constraints. A distributed power allocation algorithm is proposed to allocate the power for both D2D and cellular users by exploiting the property of strictly non-negative inverse of a Z-matrix. It is shown that the power allocated for users can be considerably saved for low QoS requirements, especially with a large number of D2D users. The proposed algorithm is validated through simulation to realize the impacts of noise power, distance between D2D users and the number of D2D pairs in the network
Game-theoretic Resource Allocation Methods for Device-to-Device (D2D) Communication
Device-to-device (D2D) communication underlaying cellular networks allows
mobile devices such as smartphones and tablets to use the licensed spectrum
allocated to cellular services for direct peer-to-peer transmission. D2D
communication can use either one-hop transmission (i.e., in D2D direct
communication) or multi-hop cluster-based transmission (i.e., in D2D local area
networks). The D2D devices can compete or cooperate with each other to reuse
the radio resources in D2D networks. Therefore, resource allocation and access
for D2D communication can be treated as games. The theories behind these games
provide a variety of mathematical tools to effectively model and analyze the
individual or group behaviors of D2D users. In addition, game models can
provide distributed solutions to the resource allocation problems for D2D
communication. The aim of this article is to demonstrate the applications of
game-theoretic models to study the radio resource allocation issues in D2D
communication. The article also outlines several key open research directions.Comment: Accepted. IEEE Wireless Comms Mag. 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
Efficiency Resource Allocation for Device-to-Device Underlay Communication Systems: A Reverse Iterative Combinatorial Auction Based Approach
Peer-to-peer communication has been recently considered as a popular issue
for local area services. An innovative resource allocation scheme is proposed
to improve the performance of mobile peer-to-peer, i.e., device-to-device
(D2D), communications as an underlay in the downlink (DL) cellular networks. To
optimize the system sum rate over the resource sharing of both D2D and cellular
modes, we introduce a reverse iterative combinatorial auction as the allocation
mechanism. In the auction, all the spectrum resources are considered as a set
of resource units, which as bidders compete to obtain business while the
packages of the D2D pairs are auctioned off as goods in each auction round. We
first formulate the valuation of each resource unit, as a basis of the proposed
auction. And then a detailed non-monotonic descending price auction algorithm
is explained depending on the utility function that accounts for the channel
gain from D2D and the costs for the system. Further, we prove that the proposed
auction-based scheme is cheat-proof, and converges in a finite number of
iteration rounds. We explain non-monotonicity in the price update process and
show lower complexity compared to a traditional combinatorial allocation. The
simulation results demonstrate that the algorithm efficiently leads to a good
performance on the system sum rate.Comment: 26 pages, 6 fgures; IEEE Journals on Selected Areas in
Communications, 201
- …