Implementation of LPWAN over white spaces for practical deployment

Rahman, M.; Ismail, Dali; Modekurthy, Venkata P.; Saifullah, Abusayeed

doi:10.1145/3302505.3310080

Cited by 19 publications

(16 citation statements)

References 16 publications

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“…However, the spectrum availability for massive densities of devices still remains an open challenge [90]. In this respect, white space is a promising solution for transmission of sensor data over long distances [91,92] to supplement the capacity offered by 5G networks [90,93].…”

Section: Future Workmentioning

confidence: 99%

Efficient placement of edge computing devices for vehicular applications in smart cities

Premsankar

Ghaddar

Francesco

et al. 2018

NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium

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The author of this dissertation contributed to the development of the heuristic algorithms, the implementation of the simulator, the evaluation through simulation, the analysis of results, and writing the article.Publication IV empirically evaluates the impact of edge computing on emerging interactive applications and services. At the time of writing, there was no clear consensus on what specifically constitutes the edge of the network in edge computing. Thus, we first survey the state of the art in edge computing architectures and determine different deployment options for edge devices. Next, we experimentally evaluate edge computing when available at different physical locations and with different virtualization technologies. Specifically, we characterize the end-to-end latency (including

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Section: Future Workmentioning

confidence: 99%

Efficient placement of edge computing devices for vehicular applications in smart cities

Premsankar

Ghaddar

Francesco

et al. 2018

NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium

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“…In contrast, the average throughput drops sharply with an increase in the distance when CSI and CFO are not compensated for. Note that a CC13x0 device can successfully receive an OOK-modulated signal with 4.8kbaud symbol rate and 39kHz bandwidth [40]. Overall, our CC13x0-based SNOW implementation holds the potentials for low-rate IoT applications.…”

Section: Performance In Uplink Communicationmentioning

confidence: 92%

“…Texas Instruments introduced TI CC1310 and TI CC1350 LaunchPads as a part of the SimpleLink microcontroller (MCU) platform to support ultra-low-power and long-range communication having a Cortex-M3 processor with 8KB SRAM and up to 128KB of in-system programmable storage [2,40]. With a small form-factor (length: 8cm, width: 4cm), both CC1310 and CC1350 are designed to operate in the lower frequency bands (287-351MHz, 359-527MHz, and 718-1054MHz) including the TV band.…”

Section: An Overview Of Ti Cc13x0 Launchpadsmentioning

confidence: 99%

“…We configure the subcarrier center frequency, bandwidth, modulation, and the Tx power by setting appropriate values to the CC13x0 command inputs centerFreq, rxBw, modulation, and txPower, respectively, using Code Composer Studio (CCS) provided by Texas Instruments [40]. A graphical user interface alternative to CCS is SmartRF Studio.…”

Section: Configuring Ti Cc13x0mentioning

confidence: 99%

“…Through this implementation, we demonstrate that any COTS device that has a programmable physical layer (PHY), operates in the white spaces, and supports amplitude-shift-keying (ASK) or binary phase-shift-keying (BPSK) may work as a SNOW node in practical deployments. Along with our original TI CC1310-based SNOW implementation in [40], we thus implement SNOW on TI CC1350 that has a programmable PHY, costs approximately $30 USD (retail price) and is 10x smaller than a USRP B200 device, thereby making SNOW adoptable in practical IoT applications. Additionally, we emphasize the fact that this implementation maybe is adaptable in the diverse range of COTS IoT devices with minimal efforts (e.g., only needs to deal with new development software), which makes it highly portable and practical choice for SNOW.…”

Section: Introductionmentioning

confidence: 99%

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LPWAN in the TV White Spaces: A Practical Implementation and Deployment Experiences

Rahman¹,

Ismail²,

Modekurthy³

et al. 2021

Preprint

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Low-Power Wide-Area Network (LPWAN) is an enabling Internet-of-Things (IoT) technology that supports long-range, low-power, and low-cost connectivity to numerous devices. To avoid the crowd in the limited ISM band (where most LPWANs operate) and cost of licensed band, the recently proposed SNOW (Sensor Network over White Spaces) is a promising LPWAN platform that operates over the TV white spaces. As it is a very recent technology and is still in its infancy, the current SNOW implementation uses the USRP devices as LPWAN nodes, which has high costs (≈ $750 USD per device) and large form-factors, hindering its applicability in practical deployment. In this paper, we implement SNOW using low-cost, low form-factor, low-power, and widely available commercial off-the-shelf (COTS) devices to enable its practical and largescale deployment. Our choice of the COTS device (TI CC13x0: CC1310 or CC1350) consequently brings down the cost and form-factor of a SNOW node by 25x and 10x, respectively. Such implementation of SNOW on the CC13x0 devices, however, faces a number of challenges to enable link reliability and communication range. Our implementation addresses these challenges by handling peak-to-average power ratio problem, channel state information estimation, carrier frequency offset estimation, and near-far power problem. Our deployment in the city of Detroit, Michigan demonstrates that CC13x0-based SNOW can achieve uplink and downlink throughputs of 11.2kbps and 4.8kbps per node, respectively, over a distance of 1km. Also, the overall throughput in the uplink increases linearly with the increase in the number of SNOW nodes.

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A comprehensive survey on networking over TV white spaces

Rahman

Saifullah

2019

Pervasive and Mobile Computing

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TV white spaces refer to the allocated but locally unused TV spectrum and can be used by unlicensed devices as secondary users. Thanks to their lower frequencies (e.g., 54 -698 MHz in the US), communication over the TV spectrum has excellent propagation characteristics over long distances and through obstacles. These characteristics along with their wide availability make the TV white spaces a great choice and alternative to many existing wireless technologies, especially the ones that need long range and high bandwidth communication. In the last decade, there have been numerous efforts from academia, industries, and standards bodies for exploiting the potentials of the TV white spaces for several applications including wireless broadband Internet access.Their characteristics and features also hold potentials for many new applications including sensing and monitoring, Internet of Things, wireless control, smart utility, location-based services, and transportation and logistics. In this paper, we perform a retrospective review and comparative study of existing work on networking in the TV white spaces. Additionally, we discuss the associated research challenges such as dealing with the interference between primary and secondary TV spectrum users, TV white space temporal and spatial variations and fragmentation, antenna design, mobility, and security. We also describe the future research directions to handle the above challenges. To the best of our knowledge, this is the first comprehensive survey on the literature of TV white space networking research.

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Implementation of LPWAN over white spaces for practical deployment

Cited by 19 publications

References 16 publications

Efficient placement of edge computing devices for vehicular applications in smart cities

Efficient placement of edge computing devices for vehicular applications in smart cities

LPWAN in the TV White Spaces: A Practical Implementation and Deployment Experiences

A comprehensive survey on networking over TV white spaces

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