Critical Issues of Centralized and Cloudified LTE-FDD Radio Access Networks

Cloudification of the Centralized-Radio Access Network (C-RAN) in which signal processing runs on general purpose processors inside virtual machines has lately received significant attention. Due to short deadlines in the LTE Frequency Division Duplex access method, processing time fluctuations introduced by the virtualization process have a deep impact on C-RAN performance. This paper evaluates bottlenecks of the OpenAirInterface (OAI is an open-source software-based implementation of LTE) cloud performance, provides feasibility studies on C-RAN execution, and introduces a cloud architecture that significantly reduces the encountered execution problems. In typical cloud environments, the OAI processing time deadlines cannot be guaranteed. Our proposed cloud architecture shows good characteristics for the OAI cloud execution. As an example, in our setup more than 99.5% processed LTE subframes reach reasonable processing deadlines close to performance of a dedicated machine.

Ultra Low Power FPGA-Based Architecture for Wake-up Radio in Wireless Sensor Networks

In this paper the capabilities of ultra low power FPGAs to implement Wake-up Radios (WuR) for ultra low energy Wireless Sensor Networks (WSNs) are analyzed. The main goal is to evaluate the utilization of very low power configurable devices to take advantage of their speed, flexibility and low power consumption instead of the more common approaches based on ASICs or microcontrollers. In this context, energy efficiency is a key aspect, considering that usually the instant power consumption is considered a figure of merit, more than the total energy consumed by the application.

Wake up Radio Architecture for Wireless Sensor Networks Using an Ultra Low Power FPGA

In this paper an implementation of a Wake up Radio(WuR) with addressing capabilities based on an ultra low power FPGA for ultra low energy Wireless Sensor Networks (WSNs) is proposed. The main goal is to evaluate the utilization of very low power configurable devices to take advantage of their speed, flexibility and low power consumption instead of the traditional approaches based on ASICs or microcontrollers, for communication frame decoding and communication data control.

Radio propagation modeling and measurements for ZigBee based indoor wireless sensor networks

The deployment of nodes in Wireless Sensor Networks (WSNs) arises as one of the biggest challenges of this field, which involves in distributing a large number of embedded systems to fulfill a specific application. The connectivity of WSNs is difficult to estimate due to the irregularity of the physical environment and affects the WSN designers? decision on deploying sensor nodes. Therefore, in this paper, a new method is proposed to enhance the efficiency and accuracy on ZigBee propagation simulation in indoor environments. The method consists of two steps: automatic 3D indoor reconstruction and 3D ray-tracing based radio simulation. The automatic 3D indoor reconstruction employs unattended image classification algorithm and image vectorization algorithm to build the environment database accurately, which also significantly reduces time and efforts spent on non-radio propagation issue. The 3D ray tracing is developed by using kd-tree space division algorithm and a modified polar sweep algorithm, which accelerates the searching of rays over the entire space. Signal propagation model is proposed for the ray tracing engine by considering both the materials of obstacles and the impact of positions along the ray path of radio. Three different WSN deployments are realized in the indoor environment of an office and the results are verified to be accurate. Experimental results also indicate that the proposed method is efficient in pre-simulation strategy and 3D ray searching scheme and is suitable for different indoor environments.

Performance analysis of multi-radio AODV in hybrid wireless mesh networks

Wireless Mesh Networks (WMNs), based on commodity hardware, present a promising technology for a wide range of applications due to their self-configuring and self-healing capabilities, as well as their low equipment and deployment costs. One of the key challenges that WMN technology faces is the limited capacity and scalability due to co-channel interference, which is typical for multi-hop wireless networks. A simple and relatively low-cost approach to address this problem is the use of multiple wireless network interfaces (radios) per node. Operating the radios on distinct orthogonal channels permits effective use of the frequency spectrum, thereby, reducing interference and contention. In this paper, we evaluate the performance of the multi-radio Ad-hoc On-demand Distance Vector (AODV) routing protocol with a specific focus on hybrid WMNs. Our simulation results show that under high mobility and traffic load conditions, multi-radio AODV offers superior performance as compared to its single-radio counterpart. We believe that multi-radio AODV is a promising candidate for WMNs, which need to service a large number of mobile clients with low latency and high bandwidth requirements.

Energy efficient architectures and techniques for green radio access networks

Energy consumption in wireless networks, and in particular in cellular mobile networks, is now of major concern in respect of their potential adverse impact upon the environment and their escalating operating energy costs. The recent phenomenal growth of data services in cellular mobile networks has exacerbated the energy consumption issue and is forcing researchers to address how to design future wireless networks that take into account energy consumption constraints. One fundamental approach to reduce energy consumption of wireless networks is to adopt new radio access architectures and radio techniques. The Mobile VCE (MVCE) Green Radio project, established in 2009, is considering such new architectural and technical approaches. This paper reports highlights the key research issues pursued in the MVCE Green Radio project.

Radio range adjustment for energy efficient wireless sensor networks

In wireless ad hoc sensor networks, energy use is in many cases the most important constraint since it corresponds directly to operational lifetime. Topology management schemes such as GAF put the redundant nodes for routing to sleep in order to save the energy. The radio range will affect the number of neighbouring nodes, which collaborate to forward data to a base station or sink. In this paper we study a simple linear network and deduce the relationship between optimal radio range and traffic. We find that half of the power can be saved if the radio range is adjusted appropriately compared with the best case where equal radio ranges are used.

Performance analysis of IEEE 802.11 cognitive radio ad hoc networks

IEEE 802.11 standard is the dominant technology for wireless local area networks (WLANs). In the last two decades, the Distributed coordination function (DCF) of IEEE 802.11 standard has become the one of the most important media access control (MAC) protocols for mobile ad hoc networks (MANETs). The DCF protocol can also be combined with cognitive radio, thus the IEEE 802.11 cognitive radio ad hoc networks (CRAHNs) come into being. There were several literatures which focus on the modeling of IEEE 802.11 CRAHNs, however, there is still no thorough and scalable analytical models for IEEE 802.11 CRAHNs whose cognitive node (i.e., secondary user, SU) has spectrum sensing and possible channel silence process before the MAC contention process. This paper develops a unified analytical model for IEEE 802.11 CRAHNs for comprehensive MAC layer queuing analysis. In the proposed model, the SUs are modeled by a hyper generalized 2D Markov chain model with an M/G/1/K model while the primary users (PUs) are modeled by a generalized 2D Markov chain and an M/G/1/K model. The performance evaluation results show that the quality-of-service (QoS) of both the PUs and SUs can be statistically guaranteed with the suitable settings of duration of channel sensing and silence phase in the case of under loading.

A framework for modelling mobile radio access networks for intelligent fault management

Postprint

Capacity forecasting for radio access networks

The mobile networks market (focus of this work) strategy is based on the consolidation of the installed structure and the optimization of the already existent resources. The increasingly competition and aggression of this market requires, to the mobile operators, a continuous maintenance and update of the networks in order to obtain the minimum number of fails and provide the best experience for its subscribers. In this context, this dissertation presents a study aiming to assist the mobile operators improving future network modifications. In overview, this dissertation compares several forecasting methods (mostly based on time series analysis) capable of support mobile operators with their network planning. Moreover, it presents several network indicators about the more common bottlenecks.

COMPRESSIVE QUANTIZATION FOR SCALABLE CLOUD RADIO ACCESS NETWORKS

With the proliferation of new mobile devices and applications, the demand for ubiquitous wireless services has increased dramatically in recent years. The explosive growth in the wireless traffic requires the wireless networks to be scalable so that they can be efficiently extended to meet the wireless communication demands. In a wireless network, the interference power typically grows with the number of devices without necessary coordination among them. On the other hand, large scale coordination is always difficult due to the low-bandwidth and high-latency interfaces between access points (APs) in traditional wireless networks. To address this challenge, cloud radio access network (C-RAN) has been proposed, where a pool of base band units (BBUs) are connected to the distributed remote radio heads (RRHs) via high bandwidth and low latency links (i.e., the front-haul) and are responsible for all the baseband processing. But the insufficient front-haul link capacity may limit the scale of C-RAN and prevent it from fully utilizing the benefits made possible by the centralized baseband processing. As a result, the front-haul link capacity becomes a bottleneck in the scalability of C-RAN. In this dissertation, we explore the scalable C-RAN in the effort of tackling this challenge. In the first aspect of this dissertation, we investigate the scalability issues in the existing wireless networks and propose a novel time-reversal (TR) based scalable wireless network in which the interference power is naturally mitigated by the focusing effects of TR communications without coordination among APs or terminal devices (TDs). Due to this nice feature, it is shown that the system can be easily extended to serve more TDs. Motivated by the nice properties of TR communications in providing scalable wireless networking solutions, in the second aspect of this dissertation, we apply the TR based communications to the C-RAN and discover the TR tunneling effects which alleviate the traffic load in the front-haul links caused by the increment of TDs. We further design waveforming schemes to optimize the downlink and uplink transmissions in the TR based C-RAN, which are shown to improve the downlink and uplink transmission accuracies. Consequently, the traffic load in the front-haul links is further alleviated by the reducing re-transmissions caused by transmission errors. Moreover, inspired by the TR-based C-RAN, we propose the compressive quantization scheme which applies to the uplink of multi-antenna C-RAN so that more antennas can be utilized with the limited front-haul capacity, which provide rich spatial diversity such that the massive TDs can be served more efficiently.

User-Created Content and Online Social Networks

Traditional media are under assault from digital technologies. Online advertising is eroding the financial basis of newspapers and television, demarcations between different forms of media are fading, and audiences are fragmenting. We can podcast our favourite radio show, data accompanies television programs, and we catch up with newspaper stories on our laptops. Yet mainstream media remain enormously powerful. The Media and Communications in Australia offers a systematic introduction to this dynamic field. Fully updated and revised to take account of recent developments, this third edition outlines the key media industries and explains how communications technologies are impacting on them. It provides a thorough overview of the main approaches taken in studying the media, and includes new chapters on social media, gaming, telecommunications, sport and cultural diversity. With contributions from some of Australia's best researchers and teachers in the field, The Media and Communications in Australia is the most comprehensive and reliable introduction to media and communications available. It is an ideal student text, and a reference for teachers of media and anyone interested in this influential industry.

Poster abstract : Energy-efficient rate adaptive MAC Protocol (RA-MAC) for long-lived sensor networks

This paper introduces an energy-efficient Rate Adaptive MAC (RA-MAC) protocol for long-lived Wireless Sensor Networks (WSN). Previous research shows that the dynamic and lossy nature of wireless communication is one of the major challenges to reliable data delivery in a WSN. RA-MAC achieves high link reliability in such situations by dynamically trading off radio bit rate for signal processing gain. This extra gain reduces the packet loss rate which results in lower energy expenditure by reducing the number of retransmissions. RA-MAC selects the optimal data rate based on channel conditions with the aim of minimizing energy consumption. We have implemented RA-MAC in TinyOS on an off-the-shelf sensor platform (TinyNode), and evaluated its performance by comparing RA-MAC with state-ofthe- art WSN MAC protocol (SCP-MAC) by experiments.

An empirical study of data collection protocols for wireless sensor networks

In the past few years, numerous data collection protocols have been developed for wireless sensor networks (WSNs). However, there has been no comparison of their relative performance in realistic environments. Here we report the results of an empirical study using a Fleck3 sensor network testbed for four different data collection protocols: One phase pull Directed Diffusion (DD), Expected Number of Transmissions (ETX), ETX with explicit acknowledgment (ETX-eAck), and ETX with implicit acknowledgment (ETX-iAck). Our empirical study provides useful insights for future sensor network deployments. When the required application end-to-end reliability is not strict (e.g., 70%) and link quality is good, DD and ETX are the best options because of their simplicity and low routing overhead. Both ETX-eAck and ETX-iAck achieve more than 90% end-to-end reliability when the link quality is reasonable (less than 25% packet loss). When the link quality is good, ETX-iAck introduces significantly less routing overhead (up to 50%) than ETX-eAck. However, if the radio transceiver supports variable packet length, ETX-eAck can outperform ETX-iAck when the link quality is poor. The important message from this paper is that choice of data collection protocol should come after the operating environment is understood. This understanding must include the characteristics of the radio transceiver, and link loss statistics from a long-term (across seasons and weather variation) radio survey of the site.

Wireless adhoc sensor and actuator networks on the farm

Agriculture accounts for a significant portion of the GDP in most developed countries. However, managing farms, particularly largescale extensive farming systems, is hindered by lack of data and increasing shortage of labour. We have deployed a large heterogeneous sensor network on a working farm to explore sensor network applications that can address some of the issues identified above. Our network is solar powered and has been running for over 6 months. The current deployment consists of over 40 moisture sensors that provide soil moisture profiles at varying depths, weight sensors to compute the amount of food and water consumed by animals, electronic tag readers, up to 40 sensors that can be used to track animal movement (consisting of GPS, compass and accelerometers), and 20 sensor/actuators that can be used to apply different stimuli (audio, vibration and mild electric shock) to the animal. The static part of the network is designed for 24/7 operation and is linked to the Internet via a dedicated high-gain radio link, also solar powered. The initial goals of the deployment are to provide a testbed for sensor network research in programmability and data handling while also being a vital tool for scientists to study animal behavior. Our longer term aim is to create a management system that completely transforms the way farms are managed.