3,575 research outputs found
Modeling, Analysis and Design for Carrier Aggregation in Heterogeneous Cellular Networks
Carrier aggregation (CA) and small cells are two distinct features of
next-generation cellular networks. Cellular networks with small cells take on a
very heterogeneous characteristic, and are often referred to as HetNets. In
this paper, we introduce a load-aware model for CA-enabled \textit{multi}-band
HetNets. Under this model, the impact of biasing can be more appropriately
characterized; for example, it is observed that with large enough biasing, the
spectral efficiency of small cells may increase while its counterpart in a
fully-loaded model always decreases. Further, our analysis reveals that the
peak data rate does not depend on the base station density and transmit powers;
this strongly motivates other approaches e.g. CA to increase the peak data
rate. Last but not least, different band deployment configurations are studied
and compared. We find that with large enough small cell density, spatial reuse
with small cells outperforms adding more spectrum for increasing user rate.
More generally, universal cochannel deployment typically yields the largest
rate; and thus a capacity loss exists in orthogonal deployment. This
performance gap can be reduced by appropriately tuning the HetNet coverage
distribution (e.g. by optimizing biasing factors).Comment: submitted to IEEE Transactions on Communications, Nov. 201
Cell Selection in Wireless Two-Tier Networks: A Context-Aware Matching Game
The deployment of small cell networks is seen as a major feature of the next
generation of wireless networks. In this paper, a novel approach for cell
association in small cell networks is proposed. The proposed approach exploits
new types of information extracted from the users' devices and environment to
improve the way in which users are assigned to their serving base stations.
Examples of such context information include the devices' screen size and the
users' trajectory. The problem is formulated as a matching game with
externalities and a new, distributed algorithm is proposed to solve this game.
The proposed algorithm is shown to reach a stable matching whose properties are
studied. Simulation results show that the proposed context-aware matching
approach yields significant performance gains, in terms of the average utility
per user, when compared with a classical max-SINR approach.Comment: 11 pages, 11 figures, Journal article in ICST Wireless Spectrum, 201
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
Unified and Distributed QoS-Driven Cell Association Algorithms in Heterogeneous Networks
This paper addresses the cell association problem in the downlink of a
multi-tier heterogeneous network (HetNet), where base stations (BSs) have
finite number of resource blocks (RBs) available to distribute among their
associated users. Two problems are defined and treated in this paper: sum
utility of long term rate maximization with long term rate quality of service
(QoS) constraints, and global outage probability minimization with outage QoS
constraints. The first problem is well-suited for low mobility environments,
while the second problem provides a framework to deal with environments with
fast fading. The defined optimization problems in this paper are solved in two
phases: cell association phase followed by the optional RB distribution phase.
We show that the cell association phase of both problems have the same
structure. Based on this similarity, we propose a unified distributed algorithm
with low levels of message passing to for the cell association phase. This
distributed algorithm is derived by relaxing the association constraints and
using Lagrange dual decomposition method. In the RB distribution phase, the
remaining RBs after the cell association phase are distributed among the users.
Simulation results show the superiority of our distributed cell association
scheme compared to schemes that are based on maximum signal to interference
plus noise ratio (SINR)
User Association in Cell-less 5G Networks Exploiting Particle Swarm Optimisation
In heterogeneous networks (HetNets), users can by default associate with the macro base stations (BSs) while the small cell BSs are underloaded. Biasing user association is a simple and realistic approach to balance the load in HetNets, as well as creating a cell-less architecture where a user does not connect to the closest base station. Most of the existing research focuses on the static biasing scheme which is not the optimal strategy to improve the system performance. In this paper, the biasing factors are generated dynamically by the algorithm of particle swarm optimisation (PSO) with the objective of balancing the load and maximising the cell spectral efficiency (CSE). This work studies two different interference cases: the first case is when each tier uses different radio resources (typical when multiple radio access technologies are used) and a user receives interference only from same-tier base stations, whereas the second interference case is when all tiers use the same radio resources and a user receives interference from the same-tier and other tier BSs. The simulation results show that the dynamic biasing using PSO outperforms the static biasing in terms of balancing the load and maximising the CSE
An Efficient Requirement-Aware Attachment Policy for Future Millimeter Wave Vehicular Networks
The automotive industry is rapidly evolving towards connected and autonomous
vehicles, whose ever more stringent data traffic requirements might exceed the
capacity of traditional technologies for vehicular networks. In this scenario,
densely deploying millimeter wave (mmWave) base stations is a promising
approach to provide very high transmission speeds to the vehicles. However,
mmWave signals suffer from high path and penetration losses which might render
the communication unreliable and discontinuous. Coexistence between mmWave and
Long Term Evolution (LTE) communication systems has therefore been considered
to guarantee increased capacity and robustness through heterogeneous
networking. Following this rationale, we face the challenge of designing fair
and efficient attachment policies in heterogeneous vehicular networks.
Traditional methods based on received signal quality criteria lack
consideration of the vehicle's individual requirements and traffic demands, and
lead to suboptimal resource allocation across the network. In this paper we
propose a Quality-of-Service (QoS) aware attachment scheme which biases the
cell selection as a function of the vehicular service requirements, preventing
the overload of transmission links. Our simulations demonstrate that the
proposed strategy significantly improves the percentage of vehicles satisfying
application requirements and delivers efficient and fair association compared
to state-of-the-art schemes.Comment: 8 pages, 8 figures, 2 tables, accepted to the 30th IEEE Intelligent
Vehicles Symposiu
Delay-Optimal Biased User Association in Heterogeneous Networks
© 2017 IEEE. In heterogeneous networks (HetNets), load balancing among different tiers can be effectively achieved by a biased user association scheme with which each user chooses to associate with one base station (BS) based on the biased received power. In contrast to previous studies, where a BS always has packets to transmit, we assume in this paper that incoming packets intended for all the associated users form a queue in the BS. In order to find the delay limit of the network to support real-time service, we focus on the delay optimization problem by properly tuning the biasing factor of each tier. By adopting a thinned Poisson point process model to characterize the locations of BSs in the busy state, an explicit expression of the average traffic intensity of each tier is obtained. On that basis, an optimization problem is formulated to minimize a lower bound of the network mean queuing delay. By showing that the optimization problem is convex, the optimal biasing factor of each tier can be obtained numerically. When the mean packet arrival rate of each user is small, a closed-form solution is derived. The simulation results demonstrate that the network queuing performance can be significantly improved by properly tuning the biasing factor. It is further shown that the network mean queuing delay might be improved at the cost of a deterioration of the network signal-to-interference ratio coverage, which indicates a performance tradeoff between real-time and non-real-time traffic in HetNets
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