Dynamic Base Station Repositioning to Improve Spectral Efficiency of Drone Small Cells

With recent advancements in drone technology, researchers are now considering the possibility of deploying small cells served by base stations mounted on flying drones. A major advantage of such drone small cells is that the operators can quickly provide cellular services in areas of urgent demand without having to pre-install any infrastructure. Since the base station is attached to the drone, technically it is feasible for the base station to dynamic reposition itself in response to the changing locations of users for reducing the communication distance, decreasing the probability of signal blocking, and ultimately increasing the spectral efficiency. In this paper, we first propose distributed algorithms for autonomous control of drone movements, and then model and analyse the spectral efficiency performance of a drone small cell to shed new light on the fundamental benefits of dynamic repositioning. We show that, with dynamic repositioning, the spectral efficiency of drone small cells can be increased by nearly 100\% for realistic drone speed, height, and user traffic model and without incurring any major increase in drone energy consumption.Comment: Accepted at IEEE WoWMoM 2017 - 9 pages, 2 tables, 4 figure

Keberkesanan program simulasi penapis sambutan dedenyut terhingga (FIR) terhadap kefahaman pelajar kejuruteraan elektrik

Kefahaman merupakan aset bagi setiap pelajar. Ini kerana melalui kefahaman pelajar dapat mengaplikasikan konsep yang dipelajari di dalam dan di luar kelas. Kajian ini dijalankan bertujuan menilai keberkesanan program simulasi penapis sambutan dedenyut terhingga (FIR) terhadap kefahaman pelajar kejuruteraan elektrik FKEE, UTHM dalam mata pelajaran Pemprosesan Isyarat Digital (DSP) bagi topik penapis FIR. Metodologi kajian ini berbentuk kaedah reka bentuk kuasi�eksperimental ujian pra-pasca bagi kumpulan-kumpulan tidak seimbang. Seramai 40 responden kajian telah dipilih dan dibahagi secara rawak kepada dua kllmpulan iaitu kumpulan rawatan yang menggunakan program simulasi penapis FIR dan kumpulan kawalan yang menggunakan kaedah pembelajaran berorientasikan modul pembelajaran DSP UTHM. Setiap responden menduduki dua ujian pencapaian iaitu ujian pra dan ujian pasca yang berbentuk kuiz. Analisis data berbentuk deskriptif dan inferens dilakllkan dengan menggunakan Peri sian Statistical Package for Social Science (SPSS) versi 11.0. Dapatan kajian menunjukkan kedua-dua kumpulan pelajar telah mengalami peningkatan dari segi kefahaman iaitu daripada tahap tidak memuaskan kepada tahap kepujian selepas menggunakan kaedah pembelajaran yang telah ditetapkan bagi kumpulan masing-masing. Walaubagaimanapun, pelajar kumpulan rawatan menunjukkan peningkatan yang lebih tinggi sedikit berbanding pelajar kumpulan kawalan. Namun begitu, dapatan kajian secara ujian statistik menunjukkan tidak terdapat perbezaan yang signifikan dari segi pencapaian markah ujian pasca di antara pelajar kumpulan rawatan dengan pelajar kumpulan kawalan. Sungguhpun begitu, penggunaan program simulasi penapis FIR telah membantu dalam peningkatan kefahaman pelajar mengenai topik penapis FIR

A study into prolonging Wireless Sensor Network lifetime during disaster scenarios

A Wireless Sensor Network (WSN) has wide potential for many applications. It can be employed for normal monitoring applications, for example, the monitoring of environmental conditions such as temperature, humidity, light intensity and pressure. A WSN is deployed in an area to sense these environmental conditions and send information about them to a sink. In certain locations, disasters such as forest fires, floods, volcanic eruptions and earth-quakes can happen in the monitoring area. During the disaster, the events being monitored have the potential to destroy the sensing devices; for example, they can be sunk in a flood, burnt in a fire, damaged in harmful chemicals, and burnt in volcano lava etc. There is an opportunity to exploit the energy of these nodes before they are totally destroyed to save the energy of the other nodes in the safe area. This can prolong WSN lifetime during the critical phase. In order to investigate this idea, this research proposes a new routing protocol called Maximise Unsafe Path (MUP) routing using Ipv6 over Low power Wireless Personal Area Networks (6LoWPAN). The routing protocol aims to exploit the energy of the nodes that are going to be destroyed soon due to the environment, by concentrating packets through these nodes. MUP adapts with the environmental conditions. This is achieved by classifying four different levels of threat based on the sensor reading information and neighbour node condition, and represents this as the node health status, which is included as one parameter in the routing decision. High priority is given to a node in an unsafe condition compared to another node in a safer condition. MUP does not allow packet routing through a node that is almost failed in order to avoid packet loss when the node fails. To avoid the energy wastage caused by selecting a route that requires a higher energy cost to deliver a packet to the sink, MUP always forwards packets through a node that has the minimum total path cost. MUP is designed as an extension of RPL, an Internet Engineering Task Force (IETF) standard routing protocol in a WSN, and is implemented in the Contiki Operating System (OS). The performance of MUP is evaluated using simulations and test-bed experiments. The results demonstrate that MUP provides a longer network lifetime during a critical phase of typically about 20\% when compared to RPL, but with a trade-off lower packet delivery ratio and end-to-end delay performances. This network lifetime improvement is crucial for the WSN to operate for as long as possible to detect and monitor the environment during a critical phase in order to save human life, minimise loss of property and save wildlife

QuIC-IoT: Model-Driven Short-Term IoT Deployment for Monitoring Physical Phenomena

The Internet-of-things ecosystem has been a driving force in the creation of smart communities where a variety of physical phenomena can be monitored continuously, e.g., air quality, traffic conditions on roads, energy consumption in buildings, etc. In this paper, we address how IoT can be quickly and effectively deployed for short-term and sporadic events (e.g., fire spread in a wildland area and flood propagation), where monitoring the evolving event is critical. In particular, we propose QuIC-IoT, a model-driven planning platform that aims to temporarily deploy a custom IoT infrastructure for monitoring short-term events, where phenomena-spread is driven by models that are physics-based. Our driving usecase event is a quasi-planned prescribed fire or RxFire - this is a wildfire resilience technique where intentional small fires are ignited apriori by forestry personnel to destroy fuel and help contain the spread of actual wildfires. Anomalies that may occur during these quasi-planned events must be rapidly captured by the IoT deployment, e.g., escaped RxFires can escalate to catastrophic wildfires under unpredictable conditions of wind, vegetation, etc. QuIC-IoT incorporates domain expert-developed models to guide IoT deployment; the event area is partitioned into subregions and a criticality metric that quantifies the likelihood of anomalies at each location is computed. QuIC-IoT allows us to mix fixed and quasi-mobile IoT devices to flexibly deploy IoT in challenging terrain and as the phenomena (RxBurn) evolves. We evaluate QuIC-IoT in two real-world forest settings (large and small) in Blodgett Forest, CA, USA, with concrete burn plans developed by wildfire experts. Our experimental results reveal that QuIC-IoT enables over 3X improvement in cost-effectiveness and performance (timely detection of anomalies) as compared to baseline IoT deployment algorithms

Buried RF Sensors for Smart Road Infrastructure: Empirical Communication Range Testing, Propagation by Line of Sight, Diffraction and Reflection Model and Technology Comparison for 868 MHz–2.4 GHz

Updating the road infrastructure requires the potential mass adoption of the road studs currently used in car detection, speed monitoring, and path marking. Road studs commonly include RF transceivers connecting the buried sensors to an offsite base station for centralized data management. Since traffic monitoring experiments through buried sensors are resource expensive and difficult, the literature detailing it is insufficient and inaccessible due to various strategic reasons. Moreover, as the main RF frequencies adopted for stud communication are either 868/915 MHz or 2.4 GHz, the radio coverage differs, and it is not readily predictable due to the low-power communication in the near proximity of the ground. This work delivers a reference study on low-power RF communication ranging for the two above frequencies up to 60 m. The experimental setup employs successive measurements and repositioning of a base station at three different heights of 0.5, 1 and 1.5 m, and is accompanied by an extensive theoretical analysis of propagation, including line of sight, diffraction, and wall reflection. Enhancing the tutorial value of this work, a correlation analysis using Pearson’s coefficient and root mean square error is performed between the field test and simulation results

A Survey on Cellular-connected UAVs: Design Challenges, Enabling 5G/B5G Innovations, and Experimental Advancements

As an emerging field of aerial robotics, Unmanned Aerial Vehicles (UAVs) have gained significant research interest within the wireless networking research community. As soon as national legislations allow UAVs to fly autonomously, we will see swarms of UAV populating the sky of our smart cities to accomplish different missions: parcel delivery, infrastructure monitoring, event filming, surveillance, tracking, etc. The UAV ecosystem can benefit from existing 5G/B5G cellular networks, which can be exploited in different ways to enhance UAV communications. Because of the inherent characteristics of UAV pertaining to flexible mobility in 3D space, autonomous operation and intelligent placement, these smart devices cater to wide range of wireless applications and use cases. This work aims at presenting an in-depth exploration of integration synergies between 5G/B5G cellular systems and UAV technology, where the UAV is integrated as a new aerial User Equipment (UE) to existing cellular networks. In this integration, the UAVs perform the role of flying users within cellular coverage, thus they are termed as cellular-connected UAVs (a.k.a. UAV-UE, drone-UE, 5G-connected drone, or aerial user). The main focus of this work is to present an extensive study of integration challenges along with key 5G/B5G technological innovations and ongoing efforts in design prototyping and field trials corroborating cellular-connected UAVs. This study highlights recent progress updates with respect to 3GPP standardization and emphasizes socio-economic concerns that must be accounted before successful adoption of this promising technology. Various open problems paving the path to future research opportunities are also discussed.Comment: 30 pages, 18 figures, 9 tables, 102 references, journal submissio