324,226 research outputs found
Power-Aware Planning and Design for Next Generation Wireless Networks
Mobile network operators have witnessed a transition from being voice dominated to video/data domination, which leads to a dramatic traffic growth over the past decade. With the 4G wireless communication systems being deployed in the world most recently, the fifth generation (5G) mobile and wireless communica- tion technologies are emerging into research fields. The fast growing data traffic volume and dramatic expansion of network infrastructures will inevitably trigger tremendous escalation of energy consumption in wireless networks, which will re- sult in the increase of greenhouse gas emission and pose ever increasing urgency on the environmental protection and sustainable network development. Thus, energy-efficiency is one of the most important rules that 5G network planning and design should follow.
This dissertation presents power-aware planning and design for next generation wireless networks. We study network planning and design problems in both offline planning and online resource allocation. We propose approximation algo- rithms and effective heuristics for various network design scenarios, with different wireless network setups and different power saving optimization objectives. We aim to save power consumption on both base stations (BSs) and user equipments (UEs) by leveraging wireless relay placement, small cell deployment, device-to- device communications and base station consolidation.
We first study a joint signal-aware relay station placement and power alloca- tion problem with consideration for multiple related physical constraints such as channel capacity, signal to noise ratio requirement of subscribers, relay power and
network topology in multihop wireless relay networks. We present approximation schemes which first find a minimum number of relay stations, using maximum transmit power, to cover all the subscribers meeting each SNR requirement, and then ensure communications between any subscriber and a base station by ad- justing the transmit power of each relay station. In order to save power on BS, we propose a practical solution and offer a new perspective on implementing green wireless networks by embracing small cell networks. Many existing works have proposed to schedule base station into sleep to save energy. However, in reality, it is very difficult to shut down and reboot BSs frequently due to nu- merous technical issues and performance requirements. Instead of putting BSs into sleep, we tactically reduce the coverage of each base station, and strategi- cally place microcells to offload the traffic transmitted to/from BSs to save total power consumption.
In online resource allocation, we aim to save tranmit power of UEs by en- abling device-to-device (D2D) communications in OFDMA-based wireless net- works. Most existing works on D2D communications either targeted CDMA- based single-channel networks or aimed at maximizing network throughput. We formally define an optimization problem based on a practical link data rate model, whose objective is to minimize total power consumption while meeting user data rate requirements. We propose to solve it using a joint optimization approach by presenting two effective and efficient algorithms, which both jointly determine mode selection, channel allocation and power assignment.
In the last part of this dissertation, we propose to leverage load migration and base station consolidation for green communications and consider a power- efficient network planning problem in virtualized cognitive radio networks with the objective of minimizing total power consumption while meeting traffic load demand of each Mobile Virtual Network Operator (MVNO). First we present a
Mixed Integer Linear Programming (MILP) to provide optimal solutions. Then we present a general optimization framework to guide algorithm design, which solves two subproblems, channel assignment and load allocation, in sequence. In addition, we present an effective heuristic algorithm that jointly solves the two subproblems.
Numerical results are presented to confirm the theoretical analysis of our schemes, and to show strong performances of our solutions, compared to several baseline methods
Robustness of HEAF(2) for Estimating the Intensity of Long-Range Dependent Network Traffic
The intensity of Long-Range Dependence (LRD) for communications network traffic can be measured using the Hurst parameter. LRD characteristics in computer networks, however, present a fundamentally different set of problems in research towards the future of network design. There are various estimators of the Hurst parameter, which differ in the reliability of their results. Getting robust and reliable estimators can help to improve traffic characterization, performance modelling, planning and engineering of real networks. Earlier research [1] introduced an estimator called the Hurst Exponent from the Autocorrelation Function (HEAF) and it was shown why lag 2 in HEAF (i.e. HEAF (2)) is considered when estimating LRD of network traffic. This paper considers the robustness of HEAF(2) when estimating the Hurst parameter of data traffic (e.g. packet sequences) with outliers
Multi-UAV Data Collection Framework for Wireless Sensor Networks
In this paper, we propose a framework design for wireless sensor networks
based on multiple unmanned aerial vehicles (UAVs). Specifically, we aim to
minimize deployment and operational costs, with respect to budget and power
constraints. To this end, we first optimize the number and locations of cluster
heads (CHs) guaranteeing data collection from all sensors. Then, to minimize
the data collection flight time, we optimize the number and trajectories of
UAVs. Accordingly, we distinguish two trajectory approaches: 1) where a UAV
hovers exactly above the visited CH; and 2) where a UAV hovers within a range
of the CH. The results of this include guidelines for data collection design.
The characteristics of sensor nodes' K-means clustering are then discussed.
Next, we illustrate the performance of optimal and heuristic solutions for
trajectory planning. The genetic algorithm is shown to be near-optimal with
only degradation. The impacts of the trajectory approach, environment,
and UAVs' altitude are investigated. Finally, fairness of UAVs trajectories is
discussed.Comment: To be presented at 2019 IEEE Global Communications Conference
(Globecom
Antennas and Propagation Aspects for Emerging Wireless Communication Technologies
The increasing demand for high data rate applications and the delivery of zero-latency multimedia content drives technological evolutions towards the design and implementation of next-generation broadband wireless networks. In this context, various novel technologies have been introduced, such as millimeter wave (mmWave) transmission, massive multiple input multiple output (MIMO) systems, and non-orthogonal multiple access (NOMA) schemes in order to support the vision of fifth generation (5G) wireless cellular networks. The introduction of these technologies, however, is inextricably connected with a holistic redesign of the current transceiver structures, as well as the network architecture reconfiguration. To this end, ultra-dense network deployment along with distributed massive MIMO technologies and intermediate relay nodes have been proposed, among others, in order to ensure an improved quality of services to all mobile users. In the same framework, the design and evaluation of novel antenna configurations able to support wideband applications is of utmost importance for 5G context support. Furthermore, in order to design reliable 5G systems, the channel characterization in these frequencies and in the complex propagation environments cannot be ignored because it plays a significant role. In this Special Issue, fourteen papers are published, covering various aspects of novel antenna designs for broadband applications, propagation models at mmWave bands, the deployment of NOMA techniques, radio network planning for 5G networks, and multi-beam antenna technologies for 5G wireless communications
The Role of Inter-Controller Traffic for Placement of Distributed SDN Controllers
We consider a distributed Software Defined Networking (SDN) architecture
adopting a cluster of multiple controllers to improve network performance and
reliability. Besides the Openflow control traffic exchanged between controllers
and switches, we focus on the control traffic exchanged among the controllers
in the cluster, needed to run coordination and consensus algorithms to keep the
controllers synchronized. We estimate the effect of the inter-controller
communications on the reaction time perceived by the switches depending on the
data-ownership model adopted in the cluster. The model is accurately validated
in an operational Software Defined WAN (SDWAN). We advocate a careful placement
of the controllers, that should take into account both the above kinds of
control traffic. We evaluate, for some real ISP network topologies, the delay
tradeoffs for the controllers placement problem and we propose a novel
evolutionary algorithm to find the corresponding Pareto frontier. Our work
provides novel quantitative tools to optimize the planning and the design of
the network supporting the control plane of SDN networks, especially when the
network is very large and in-band control plane is adopted. We also show that
for operational distributed controllers (e.g. OpenDaylight and ONOS), the
location of the controller which acts as a leader in the consensus algorithm
has a strong impact on the reactivity perceived by switches.Comment: 14 page
Tweeting From the Moon
Lunar Communications Pathfinder is planned to enable small and large satellites and landers to carry out data intensive missions around the moon, without the need for complex and costly on-board communication equipment and access to global ground networks.
From the middle of this decade there are expected to be 5 to 15 active space missions on or around the moon, generating several GBytes of data per day. Lunar Communications Pathfinder is a commercial initiative with ESA and NASA as anchor tenants. The 300kg class small spacecraft is currently in manufacture for launch in 2025, and is aimed at alleviating pressure on the Deep Space Network. It will provide a commercial high speed communications service that will enable landers, orbiters, and even CubeSats to operate around the moon without requiring direct line of sight with the Earth. A small user terminal is in development as part of the service package, and a mission builder tool has been made available for planning purposes for prospective users. LCP provides a high speed intersatellite link back to Earth for a planned 8 year mission. The system is planned to be extended further with additional spacecraft, opening up the potential to provide a more comprehensive communications and navigation service.
Building on LCP, the ESA Moonlight initiative has contracted a study phase in order to develop the plans for the full constellation service beyond this initial spacecraft. LCP demonstrates how small satellites can provide innovative commercial services, and enable the ability for other small satellites and landers to carry out data intensive missions. This paper will detail the spacecraft, the system design trades, and how the service is expected to evolve
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