835 research outputs found
Energy efficient D2D communications in dynamic TDD systems
Network-assisted device-to-device communication is a promising technology for
improving the performance of proximity-based services. This paper demonstrates
how the integration of device-to-device communications and dynamic
time-division duplex can improve the energy efficiency of future cellular
networks, leading to a greener system operation and a prolonged battery
lifetime of mobile devices. We jointly optimize the mode selection,
transmission period and power allocation to minimize the energy consumption
(from both a system and a device perspective) while satisfying a certain rate
requirement. The radio resource management problems are formulated as
mixed-integer nonlinear programming problems. Although they are known to be
NP-hard in general, we exploit the problem structure to design efficient
algorithms that optimally solve several problem cases. For the remaining cases,
a heuristic algorithm that computes near-optimal solutions while respecting
practical constraints on execution times and signaling overhead is also
proposed. Simulation results confirm that the combination of device-to-device
and flexible time-division-duplex technologies can significantly enhance
spectrum and energy-efficiency of next generation cellular systems.Comment: Submitted to IEEE Journal of Selected Areas in Communication
Resource Allocation for Device-to-Device Communications in Multi-Cell Multi-Band Heterogeneous Cellular Networks
Heterogeneous cellular networks (HCNs) with millimeter wave (mm-wave)
communications are considered as a promising technology for the fifth
generation mobile networks. Mm-wave has the potential to provide multiple
gigabit data rate due to the broad spectrum. Unfortunately, additional free
space path loss is also caused by the high carrier frequency. On the other
hand, mm-wave signals are sensitive to obstacles and more vulnerable to
blocking effects. To address this issue, highly directional narrow beams are
utilized in mm-wave networks. Additionally, device-to-device (D2D) users make
full use of their proximity and share uplink spectrum resources in HCNs to
increase the spectrum efficiency and network capacity. Towards the caused
complex interferences, the combination of D2D-enabled HCNs with small cells
densely deployed and mm-wave communications poses a big challenge to the
resource allocation problems. In this paper, we formulate the optimization
problem of D2D communication spectrum resource allocation among multiple
micro-wave bands and multiple mm-wave bands in HCNs. Then, considering the
totally different propagation conditions on the two bands, a heuristic
algorithm is proposed to maximize the system transmission rate and approximate
the solutions with sufficient accuracies. Compared with other practical
schemes, we carry out extensive simulations with different system parameters,
and demonstrate the superior performance of the proposed scheme. In addition,
the optimality and complexity are simulated to further verify effectiveness and
efficiency.Comment: 13 pages, 11 figures, IEEE Transactions on Vehicular Technolog
Energy-Efficient Resource Allocation for Device-to-Device Underlay Communication
Device-to-device (D2D) communication underlaying cellular networks is
expected to bring significant benefits for utilizing resources, improving user
throughput and extending battery life of user equipments. However, the
allocation of radio and power resources to D2D communication needs elaborate
coordination, as D2D communication can cause interference to cellular
communication. In this paper, we study joint channel and power allocation to
improve the energy efficiency of user equipments. To solve the problem
efficiently, we introduce an iterative combinatorial auction algorithm, where
the D2D users are considered as bidders that compete for channel resources, and
the cellular network is treated as the auctioneer. We also analyze important
properties of D2D underlay communication, and present numerical simulations to
verify the proposed algorithm.Comment: IEEE Transactions on Wireless Communication
Intelligent Wireless Communications Enabled by Cognitive Radio and Machine Learning
The ability to intelligently utilize resources to meet the need of growing
diversity in services and user behavior marks the future of wireless
communication systems. Intelligent wireless communications aims at enabling the
system to perceive and assess the available resources, to autonomously learn to
adapt to the perceived wireless environment, and to reconfigure its operating
mode to maximize the utility of the available resources. The perception
capability and reconfigurability are the essential features of cognitive radio
while modern machine learning techniques project great potential in system
adaptation. In this paper, we discuss the development of the cognitive radio
technology and machine learning techniques and emphasize their roles in
improving spectrum and energy utility of wireless communication systems. We
describe the state-of-the-art of relevant techniques, covering spectrum sensing
and access approaches and powerful machine learning algorithms that enable
spectrum- and energy-efficient communications in dynamic wireless environments.
We also present practical applications of these techniques and identify further
research challenges in cognitive radio and machine learning as applied to the
existing and future wireless communication systems
Radio Resource Allocation for Device-to-Device Underlay Communication Using Hypergraph Theory
Device-to-Device (D2D) communication has been recognized as a promising
technique to offload the traffic for the evolved Node B (eNB). However, the D2D
transmission as an underlay causes severe interference to both the cellular and
other D2D links, which imposes a great technical challenge to radio resource
allocation. Conventional graph based resource allocation methods typically
consider the interference between two user equipments (UEs), but they cannot
model the interference from multiple UEs to completely characterize the
interference. In this paper, we study channel allocation using hypergraph
theory to coordinate the interference between D2D pairs and cellular UEs, where
an arbitrary number of D2D pairs are allowed to share the uplink channels with
the cellular UEs. Hypergraph coloring is used to model the cumulative
interference from multiple D2D pairs, and thus, eliminate the mutual
interference. Simulation results show that the system capacity is significantly
improved using the proposed hypergraph method in comparison to the conventional
graph based one.Comment: 27 pages,10 figure
Spectrum Resource Management and Interference Mitigation for D2D Communications with Awareness of BER Constraint in mmWave 5G Underlay Network
The work presented in this paper deals with the issue of massive demands for
higher capacity. For that matter, we investigate the spectrum resource
management in outdoor mmWave cell for the uplink of cellular and D2D
communications. Indeed, we provide a first insight how to optimize the system
performance in terms of achievable throughput while realizing a compromise
between the large number of admitted devices and the generated interference
constraint. We propose a mathematical formulation of the optimization objective
which falls in the mixed integer-real optimization scheme. To overcome its
complexity, we apply a heuristic algorithm and test its efficiency through
simulation results with a particular regard to the BER impact in the QoS.Comment: Accepted in IEEE Symposium on Computers and Communications June, 201
Energy Efficient Power and Channel Allocation in Underlay Device to Multi Device Communications
In this paper, we optimize the energy efficiency (bits/s/Hz/J) of
device-to-multi-device (D2MD) wireless communications. While the
device-to-device scenario has been extensively studied to improve the spectral
efficiency in cellular networks, the use of multicast communications opens the
possibility of reusing the spectrum resources also inside the groups. The
optimization problem is formulated as a mixed integer non-linear joint
optimization for the power control and allocation of resource blocks (RBs) to
each group. Our model explicitly considers resource sharing by letting
co-channel transmission over a RB (up to a maximum of r transmitters) and/or
transmission through s different channels in each group. We use an iterative
decomposition approach, using first matching theory to find a stable even if
sub-optimal channel allocation, to then optimize the transmission power vectors
in each group via fractional programming. Additionally, within this framework,
both the network energy efficiency and the max-min individual energy efficiency
are investigated. We characterize numerically the energy-efficient capacity
region, and our results show that the normalized energy efficiency is nearly
optimal (above 90 percent of the network capacity) for a wide range of
minimum-rate constraints. This performance is better than that of other
matching-based techniques previously proposed
Relay Assisted Device-to-Device Communication: Approaches and Issues
Enabling technologies for 5G and future wireless communication have attracted
the interest of industry and research communities. One of such technologies is
Device-to-Device (D2D) communication which exploits user proximity to offer
spectral efficiency, energy efficiency and increased throughput. Data
offloading, public safety communication, context aware communication and
content sharing are some of the use cases for D2D communication. D2D
communication can be direct or through a relay depending on the nature of the
channel in between the D2D devices. Apart from the problem of interference, a
key challenge of relay aided D2D communication is appropriately assigning
relays to a D2D pair while maintaining the QoS requirement of the cellular
users. In this article, relay assisted D2D communication is reviewed and
research issues are highlighted. We also propose matching theory with
incomplete information for relay allocation considering uncertainties which the
mobility of the relay introduces to the set up
Optimal Virtualized Inter-Tenant Resource Sharing for Device-to-Device Communications in 5G Networks
Device-to-Device (D2D) communication is expected to enable a number of new
services and applications in future mobile networks and has attracted
significant research interest over the last few years. Remarkably, little
attention has been placed on the issue of D2D communication for users belonging
to different operators. In this paper, we focus on this aspect for D2D users
that belong to different tenants (virtual network operators), assuming
virtualized and programmable future 5G wireless networks. Under the assumption
of a cross-tenant orchestrator, we show that significant gains can be achieved
in terms of network performance by optimizing resource sharing from the
different tenants, i.e., slices of the substrate physical network topology. To
this end, a sum-rate optimization framework is proposed for optimal sharing of
the virtualized resources. Via a wide site of numerical investigations, we
prove the efficacy of the proposed solution and the achievable gains compared
to legacy approaches.Comment: 10 pages, 7 figure
Resource Optimization in Device-to-Device Cellular Systems Using Time-Frequency Hopping
We develop a flexible and accurate framework for device-to-device (D2D)
communication in the context of a conventional cellular network, which allows
for time-frequency resources to be either shared or orthogonally partitioned
between the two networks. Using stochastic geometry, we provide accurate
expressions for SINR distributions and average rates, under an assumption of
interference randomization via time and/or frequency hopping, for both
dedicated and shared spectrum approaches. We obtain analytical results in
closed or semi-closed form in high SNR regime, that allow us to easily explore
the impact of key parameters (e.g., the load and hopping probabilities) on the
network performance. In particular, unlike other models, the expressions we
obtain are tractable, i.e., they can be efficiently optimized without extensive
simulation. Using these, we optimize the hopping probabilities for the D2D
links, i.e., how often they should request a time or frequency slot. This can
be viewed as an optimized lower bound to other more sophisticated scheduling
schemes. We also investigate the optimal resource partitions between D2D and
cellular networks when they use orthogonal resources
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