653 research outputs found
User relay assisted traffic shifting in LTE-advanced systems
In order to deal with uneven load distribution, mobility load balancing adjusts the handover region to shift edge users from a hot-spot cell to the less-loaded neighbouring cells. However, shifted users suffer the reduced signal power from neighbouring cells, which may result in link quality degradation. This paper employs a user relaying model and proposes a user relay assisted traffic shifting (URTS) scheme to deal with the above problem. In URTS, a shifted user selects a suitable non-active user as relay user to forward data, thus enhancing the link quality of the shifted user. Since the user relaying model consumes relay user’s energy, a utility function is designed in relay selection to reach a trade-off between the shifted user’s link quality improvement and the relay user’s energy consumption. Simulation results show that URTS scheme could improve SINR and throughput of shifted users. Also, URTS scheme keeps the cost of relay user’s energy consumption at an acceptable level
Self-Organising Load Balancing for OFDMA Cellular Networks
In this thesis, self-organising load balancing is investigated to deal with the uneven load distribution in OFDMA based cellular networks. In single-hop cellular networks, a self- organising cluster-based cooperative load balancing (CCLB) scheme is proposed to overcome the ‘virtual partner’ and the ‘aggravating load’ problems confronted in the conventional mobility load balancing schemes. Theoretical analysis and simulation results show that the proposed scheme can effectively reduce the call blocking probability, the handover failure rate, and the hot-spot cell’s load.
The proposed CCLB scheme consists of two stages: partner cell selection and traffic shifting. In the partner cell selection stage, a user-vote assisted clustering algorithm is proposed, which jointly considers the users’ channel condition and the surrounding cells’ load. This algorithm can select appropriate neighbouring cells as partners to construct the load balancing cluster, and deal with the ‘virtual partner’ problem. In the traffic shifting stage, a relative load response model (RLRM) is designed. RLRM coordinates multiple hot-spot cells’ shifting traffic towards their public partner, thus mitigating the ‘aggravating load’ problem of the public partner. Moreover, a traffic offloading optimisation algorithm is proposed to balance the hot-spot cell’s load within the load balancing cluster and to minimise its partners’ average call blocking probability.
The CCLB scheme is modified to apply in multi-hop cellular networks with relays deployed. Both fixed relay and mobile user relay scenarios are considered. For fixed relay cellular networks, a relay-level user shifting algorithm is proposed. This algorithm jointly considers users’ channel condition and spectrum usage of fixed relay, in order to reduce the handover failure rate and deal with the ‘aggravating load’ problem of fixed relay. In the mobile user relay scenario, the user relaying assisted traffic shifting algorithm is proposed to improve the link quality of shifted edge users, which brings about an increase in the achievable rate of shifted edge users and decrease in the handover failure rate
A Comprehensive Survey on Moving Networks
The unprecedented increase in the demand for mobile data, fuelled by new
emerging applications such as HD video streaming and heightened online
activities has caused massive strain on the existing cellular networks. As a
solution, the 5G technology has been introduced to improve network performance
through various innovative features such as mmWave spectrum and HetNets. In
essence, HetNets include several small cells underlaid within macro-cell to
serve densely populated regions. Recently, a mobile layer of HetNet has been
under consideration by the researchers and is often referred to as moving
networks. Moving networks comprise of mobile cells that are primarily
introduced to improve QoS for commuting users inside public transport because
the QoS is deteriorated due to vehicular penetration losses. Furthermore, the
users inside fast moving public transport also exert excessive load on the core
network due to large group handovers. To this end, mobile cells will play a
crucial role in reducing overall handover count and will help in alleviating
these problems by decoupling in-vehicle users from the core network.
To date, remarkable research results have been achieved by the research
community in addressing challenges linked to moving networks. However, to the
best of our knowledge, a discussion on moving networks in a holistic way is
missing in the current literature. To fill the gap, in this paper, we
comprehensively survey moving networks. We cover the technological aspects and
their applications in the futuristic applications. We also discuss the
use-cases and value additions that moving networks may bring to future cellular
architecture and identify the challenges associated with them. Based on the
identified challenges we discuss the future research directions.Comment: This survey has been submitted to IEEE Communications Surveys &
Tutorial
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
Evolution Toward 5G Mobile Networks - A Survey on Enabling Technologies
In this paper, an extensive review has been carried out on the trends of existing as well as proposed potential enabling technologies that are expected to shape the fifth generation (5G) mobile wireless networks. Based on the classification of the trends, we develop a 5G network architectural evolution framework that comprises three evolutionary directions, namely, (1) radio access network node and performance enabler, (2) network control programming platform, and (3) backhaul network platform and synchronization. In (1), we discuss node classification including low power nodes in emerging machine-type communications, and network capacity enablers, e.g., millimeter wave communications and massive multiple-input multiple-output. In (2), both logically distributed cell/device-centric platforms, and logically centralized conventional/wireless software defined networking control programming approaches are discussed. In (3), backhaul networks and network synchronization are discussed. A comparative analysis for each direction as well as future evolutionary directions and challenges toward 5G networks are discussed. This survey will be helpful for further research exploitations and network operators for a smooth evolution of their existing networks toward 5G networks
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Scalable base station switching framework for green cellular networks
With the recent unprecedented growth in the wireless market, network operators are obliged not only to find new techniques including dense deployment of base stations (BSs) in order to support high data rate services and high user density, but also to reduce the operating costs and energy consumption of various network elements. To solve these challenges, powering down certain BSs during low-traffic periods, so-called BS sleeping, has emerged as an effective green communications paradigm. While BS sleeping offers the potential to significantly lower energy consumption, it also raises many challenges, since when a BS is switched off, this can lead to, for example, coverage holes, sudden degradation in quality of service (QoS), higher transmit power dissipation in off-cell mobile stations (MSs), an inability to rapidly power up/down equipment and finally, a failure to uphold regulatory requirements. In order to realise greener network designs which both maximise energy savings whilst guaranteeing QoS, innovative BS switching mechanisms need to be developed.
This thesis presents a novel BS switching framework which improves energy efficiency (EE) in comparison with existing approaches, while guaranteeing the minimum QoS and seamless services. The major technical contributions in this framework are: i) a new BS to relay station (RS) switching model where certain BSs are switched to RS mode rather than being turned off, firstly using a fixed threshold based switching algorithm utilizing temporal traffic diversity, and ii) then subsequently by means of an adaptive threshold by exploiting the inherently asymmetric traffic profile between cells, i.e., by exploiting both the temporal and spatial traffic diversity; iii) a traffic-and-interference-aware BS switching strategy that considers the impact of inter-cell interference in the decision making process to dynamically determine the best BS set to be kept active for improved EE; and finally iv) a novel scalable multimode BS switching model which enables each BS to operate in different power modes i.e., macro/micro/sleep to explore energy savings potential even at higher traffic conditions.
The thesis findings conclusively confirm this new BS switching framework provides significant EE improvements from both BS and MS perspectives, under diverse network conditions and represents a notable step towards greener communications
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