22,051 research outputs found
Context-Aware Resource Allocation in Cellular Networks
We define and propose a resource allocation architecture for cellular
networks. The architecture combines content-aware, time-aware and
location-aware resource allocation for next generation broadband wireless
systems. The architecture ensures content-aware resource allocation by
prioritizing real-time applications users over delay-tolerant applications
users when allocating resources. It enables time-aware resource allocation via
traffic-dependent pricing that varies during different hours of day (e.g. peak
and off-peak traffic hours). Additionally, location-aware resource allocation
is integrable in this architecture by including carrier aggregation of various
frequency bands. The context-aware resource allocation is an optimal and
flexible architecture that can be easily implemented in practical cellular
networks. We highlight the advantages of the proposed network architecture with
a discussion on the future research directions for context-aware resource
allocation architecture. We also provide experimental results to illustrate a
general proof of concept for this new architecture.Comment: (c) 2015 IEEE. Personal use of this material is permitted. Permission
from IEEE must be obtained for all other uses, in any current or future
media, including reprinting/republishing this material for advertising or
promotional purposes, creating new collective works, for resale or
redistribution to servers or lists, or reuse of any copyrighted component of
this work in other work
Wireless Communications in the Era of Big Data
The rapidly growing wave of wireless data service is pushing against the
boundary of our communication network's processing power. The pervasive and
exponentially increasing data traffic present imminent challenges to all the
aspects of the wireless system design, such as spectrum efficiency, computing
capabilities and fronthaul/backhaul link capacity. In this article, we discuss
the challenges and opportunities in the design of scalable wireless systems to
embrace such a "bigdata" era. On one hand, we review the state-of-the-art
networking architectures and signal processing techniques adaptable for
managing the bigdata traffic in wireless networks. On the other hand, instead
of viewing mobile bigdata as a unwanted burden, we introduce methods to
capitalize from the vast data traffic, for building a bigdata-aware wireless
network with better wireless service quality and new mobile applications. We
highlight several promising future research directions for wireless
communications in the mobile bigdata era.Comment: This article is accepted and to appear in IEEE Communications
Magazin
Matching Theory for Future Wireless Networks: Fundamentals and Applications
The emergence of novel wireless networking paradigms such as small cell and
cognitive radio networks has forever transformed the way in which wireless
systems are operated. In particular, the need for self-organizing solutions to
manage the scarce spectral resources has become a prevalent theme in many
emerging wireless systems. In this paper, the first comprehensive tutorial on
the use of matching theory, a Nobelprize winning framework, for resource
management in wireless networks is developed. To cater for the unique features
of emerging wireless networks, a novel, wireless-oriented classification of
matching theory is proposed. Then, the key solution concepts and algorithmic
implementations of this framework are exposed. Then, the developed concepts are
applied in three important wireless networking areas in order to demonstrate
the usefulness of this analytical tool. Results show how matching theory can
effectively improve the performance of resource allocation in all three
applications discussed
Resource Allocation for D2D Communications Based on Matching Theory
PhDDevice-to-device (D2D) communications underlaying a cellular infrastructure takes advantage
of the physical proximity of communicating devices and increasing resource utilisation.
However, adopting D2D communications in complex scenarios poses substantial
challenges for the resource allocation design. Meanwhile, matching theory has emerged
as a promising framework for wireless resource allocation which can overcome some limitations
of game theory and optimisation. This thesis focuses on the resource allocation
optimisation for D2D communications based on matching theory.
First, resource allocation policy is designed for D2D communications underlaying cellular
networks. A novel spectrum allocation algorithm based on many-to-many matching
is proposed to improve system sum rate. Additionally, considering the quality-of-service
(QoS) requirements and priorities of di erent applications, a context-aware resource allocation
algorithm based on many-to-one matching is proposed, which is capable of providing
remarkable performance enhancement in terms of improved data rate, decreased
packet error rate (PER) and reduced delay.
Second, to improve resource utilisation, joint subchannel and power allocation problem
for D2D communications with non-orthogonal multiple access (NOMA) is studied. For
the subchannel allocation, a novel algorithm based on the many-to-one matching is
proposed for obtaining a suboptimal solution. Since the power allocation problem is
non-convex, sequential convex programming is adopted to transform the original power
allocation problem to a convex one. The proposed algorithm is shown to enhance the
network sum rate and number of accessed users.
Third, driven by the trend of heterogeneity of cells, the resource allocation problem for
NOMA-enhanced D2D communications in heterogeneous networks (HetNets) is investigated. In such a scenario, the proposed resource allocation algorithm is able to closely
approach the optimal solution within a limited number of iterations and achieves higher
sum rate compared to traditional HetNets schemes.
Thorough theoretical analysis is conducted in the development of all proposed algorithms,
and performance of proposed algorithm is evaluated via comprehensive simulations.
This thesis concludes that matching theory based resource allocation for D2D communications
achieves near-optimal performance with acceptable complexity. In addition,
the application of D2D communications in NOMA and HetNets can improve system
performance in terms of sum rate and users connectivity
Energy-Efficient Heterogeneous Cellular Networks with Spectrum Underlay and Overlay Access
In this paper, we provide joint subcarrier assignment and power allocation
schemes for quality-of-service (QoS)-constrained energy-efficiency (EE)
optimization in the downlink of an orthogonal frequency division multiple
access (OFDMA)-based two-tier heterogeneous cellular network (HCN). Considering
underlay transmission, where spectrum-efficiency (SE) is fully exploited, the
EE solution involves tackling a complex mixed-combinatorial and non-convex
optimization problem. With appropriate decomposition of the original problem
and leveraging on the quasi-concavity of the EE function, we propose a
dual-layer resource allocation approach and provide a complete solution using
difference-of-two-concave-functions approximation, successive convex
approximation, and gradient-search methods. On the other hand, the inherent
inter-tier interference from spectrum underlay access may degrade EE
particularly under dense small-cell deployment and large bandwidth utilization.
We therefore develop a novel resource allocation approach based on the concepts
of spectrum overlay access and resource efficiency (RE) (normalized EE-SE
trade-off). Specifically, the optimization procedure is separated in this case
such that the macro-cell optimal RE and corresponding bandwidth is first
determined, then the EE of small-cells utilizing the remaining spectrum is
maximized. Simulation results confirm the theoretical findings and demonstrate
that the proposed resource allocation schemes can approach the optimal EE with
each strategy being superior under certain system settings
- …