195 research outputs found
Recent advances in radio resource management for heterogeneous LTE/LTE-A networks
As heterogeneous networks (HetNets) emerge as one of the most promising developments toward realizing the target specifications of Long Term Evolution (LTE) and LTE-Advanced (LTE-A) networks, radio resource management (RRM) research for such networks has, in recent times, been intensively pursued. Clearly, recent research mainly concentrates on the aspect of interference mitigation. Other RRM aspects, such as radio resource utilization, fairness, complexity, and QoS, have not been given much attention. In this paper, we aim to provide an overview of the key challenges arising from HetNets and highlight their importance. Subsequently, we present a comprehensive survey of the RRM schemes that have been studied in recent years for LTE/LTE-A HetNets, with a particular focus on those for femtocells and relay nodes. Furthermore, we classify these RRM schemes according to their underlying approaches. In addition, these RRM schemes are qualitatively analyzed and compared to each other. We also identify a number of potential research directions for future RRM development. Finally, we discuss the lack of current RRM research and the importance of multi-objective RRM studies
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Radio network management in cognitive LTE-Femtocell Systems
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.There is a strong uptake of femtocell deployment as small cell application
platforms in the upcoming LTE networks. In such two-tier networks of LTEfemtocell
base stations, a large portion of the assigned spectrum is used
sporadically leading to underutilisation of valuable frequency resources.
Novel spectrum access techniques are necessary to solve these current spectrum
inefficiency problems. Therefore, spectrum management solutions should have
the features to improve spectrum access in both temporal and spatial manner.
Cognitive Radio (CR) with the Dynamic Spectrum Access (DSA) is considered
to be the key technology in this research in order to increase the spectrum
efficiency. This is an effective solution to allow a group of Secondary Users
(SUs) to share the radio spectrum initially allocated to the Primary User (PUs) at
no interference.
The core aim of this thesis is to develop new cognitive LTE-femtocell systems
that offer a 4G vision, to facilitate the radio network management in order to
increase the network capacity and further improve spectrum access probabilities.
In this thesis, a new spectrum management model for cognitive radio networks is
considered to enable a seamless integration of multi-access technology with
existing networks. This involves the design of efficient resource allocation
algorithms that are able to respond to the rapid changes in the dynamic wireless
environment and primary users activities. Throughout this thesis a variety of
network upgraded functions are developed using application simulation
scenarios. Therefore, the proposed algorithms, mechanisms, methods, and system
models are not restricted in the considered networks, but rather have a wider
applicability to be used in other technologies.
This thesis mainly investigates three aspects of research issues relating to the
efficient management of cognitive networks: First, novel spectrum resource
management modules are proposed to maximise the spectrum access by rapidly
detecting the available transmission opportunities. Secondly, a developed pilot
power controlling algorithm is introduced to minimise the power consumption by
considering mobile position and application requirements. Also, there is
investigation on the impact of deploying different numbers of femtocell base
stations in LTE domain to identify the optimum cell size for future networks.
Finally, a novel call admission control mechanism for mobility management is
proposed to support seamless handover between LTE and femtocell domains.
This is performed by assigning high speed mobile users to the LTE system to
avoid unnecessary handovers.
The proposed solutions were examined by simulation and numerical analysis to
show the strength of cognitive femtocell deployment for the required
applications. The results show that the new system design based on cognitive
radio configuration enable an efficient resource management in terms of
spectrum allocation, adaptive pilot power control, and mobile handover. The
proposed framework and algorithms offer a novel spectrum management for self organised LTE-femtocell architecture.
Eventually, this research shows that certain architectures fulfilling spectrum
management requirements are implementable in practice and display good
performance in dynamic wireless environments which recommends the
consideration of CR systems in LTE and femtocell networks
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Interference Aware Cognitive Femtocell Networks
Femtocells Access Points (FAP) are low power, plug and play home base stations which are designed to extend the cellular radio range in indoor environments where macrocell coverage is generally poor. They offer significant increases in data rates over a short range, enabling high speed wireless and mobile broadband services, with the femtocell network overlaid onto the macrocell in a dual-tier arrangement. In contrast to conventional cellular systems which are well planned, FAP are arbitrarily installed by the end users and this can create harmful interference to both collocated femtocell and macrocell users. The interference becomes particularly serious in high FAP density scenarios and compromises the ensuing data rate. Consequently, effective management of both cross and co-tier interference is a major design challenge in dual-tier networks.
Since traditional radio resource management techniques and architectures for single-tier systems are either not applicable or operate inefficiently, innovative dual-tier approaches to intelligently manage interference are required. This thesis presents a number of original contributions to fulfill this objective including, a new hybrid cross-tier spectrum sharing model which builds upon an existing fractional frequency reuse technique to ensure minimal impact on the macro-tier resource allocation. A new flexible and adaptive virtual clustering framework is then formulated to alleviate co-tier interference in high FAP densities situations and finally, an intelligent coverage extension algorithm is developed to mitigate excessive femto-macrocell handovers, while upholding the required quality of service provision.
This thesis contends that to exploit the undoubted potential of dual-tier, macro-femtocell architectures an interference awareness solution is necessary. Rigorous evidence confirms that noteworthy performance improvements can be achieved in the quality of the received signal and throughput by applying cognitive methods to manage interference
Improving Macrocell - Small Cell Coexistence through Adaptive Interference Draining
The deployment of underlay small base stations (SBSs) is expected to
significantly boost the spectrum efficiency and the coverage of next-generation
cellular networks. However, the coexistence of SBSs underlaid to an existing
macro-cellular network faces important challenges, notably in terms of spectrum
sharing and interference management. In this paper, we propose a novel
game-theoretic model that enables the SBSs to optimize their transmission rates
by making decisions on the resource occupation jointly in the frequency and
spatial domains. This procedure, known as interference draining, is performed
among cooperative SBSs and allows to drastically reduce the interference
experienced by both macro- and small cell users. At the macrocell side, we
consider a modified water-filling policy for the power allocation that allows
each macrocell user (MUE) to focus the transmissions on the degrees of freedom
over which the MUE experiences the best channel and interference conditions.
This approach not only represents an effective way to decrease the received
interference at the MUEs but also grants the SBSs tier additional transmission
opportunities and allows for a more agile interference management. Simulation
results show that the proposed approach yields significant gains at both
macrocell and small cell tiers, in terms of average achievable rate per user,
reaching up to 37%, relative to the non-cooperative case, for a network with
150 MUEs and 200 SBSs
Efficient radio resource management for future generation heterogeneous wireless networks
The heterogeneous deployment of small cells (e.g., femtocells) in the coverage area of the traditional macrocells is a cost-efficient solution to provide network capacity, indoor coverage and green communications towards sustainable environments in the future fifth generation (5G) wireless networks. However, the unplanned and ultra-dense deployment of femtocells with their uncoordinated operations will result in technical challenges such as severe interference, a significant increase in total energy consumption, unfairness in radio resource sharing and inadequate quality of service provisioning. Therefore, there is a need to develop efficient radio resource management algorithms that will address the above-mentioned technical challenges. The aim of this thesis is to develop and evaluate new efficient radio resource management algorithms that will be implemented in cognitive radio enabled femtocells to guarantee the economical sustainability of broadband wireless communications and users' quality of service in terms of throughput and fairness. Cognitive Radio (CR) technology with the Dynamic Spectrum Access (DSA) and stochastic process are the key technologies utilized in this research to increase the spectrum efficiency and energy efficiency at limited interference. This thesis essentially investigates three research issues relating to the efficient radio resource management: Firstly, a self-organizing radio resource management algorithm for radio resource allocation and interference management is proposed. The algorithm considers the effect of imperfect spectrum sensing in detecting the available transmission opportunities to maximize the throughput of femtocell users while keeping interference below pre-determined thresholds and ensuring fairness in radio resource sharing among users. Secondly, the effect of maximizing the energy efficiency and the spectrum efficiency individually on radio resource management is investigated. Then, an energy-efficient radio resource management algorithm and a spectrum-efficient radio resource management algorithm are proposed for green communication, to improve the probabilities of spectrum access and further increase the network capacity for sustainable environments. Also, a joint maximization of the energy efficiency and spectrum efficiency of the overall networks is considered since joint optimization of energy efficiency and spectrum efficiency is one of the goals of 5G wireless networks. Unfortunately, maximizing the energy efficiency results in low performance of the spectrum efficiency and vice versa. Therefore, there is an investigation on how to balance the trade-off that arises when maximizing both the energy efficiency and the spectrum efficiency simultaneously. Hence, a joint energy efficiency and spectrum efficiency trade-off algorithm is proposed for radio resource allocation in ultra-dense heterogeneous networks based on orthogonal frequency division multiple access. Lastly, a joint radio resource allocation with adaptive modulation and coding scheme is proposed to minimize the total transmit power across femtocells by considering the location and the service requirements of each user in the network. The performance of the proposed algorithms is evaluated by simulation and numerical analysis to demonstrate the impact of ultra-dense deployment of femtocells on the macrocell networks. The results show that the proposed algorithms offer improved performance in terms of throughput, fairness, power control, spectrum efficiency and energy efficiency. Also, the proposed algorithms display excellent performance in dynamic wireless environments
Technical advances in the design and deployment of future heterogeneous networks
The trend in wireless communications systems is the enhancement of the network infrastructure with the introduction of small cells, where a specific geographical area is served by low-range, low-power access points. The result is the creation of a heterogeneous topology where macrocells coexist with a variety of small-cell types. In this editorial article we briefly summarize the recent technical advances in the design and deployment of future heterogeneous networks addressed in the papers that compose this special issue. In particular the following aspects are considered: the design of interference and radio resource management algorithms, the analysis of the energy efficiency and power control issues in heterogeneous networks, the concept of coordination in small cell networks, key backhaul aspects of HetNets, deployment issues and overall management strategies.Peer ReviewedPostprint (published version
Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory
Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization
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