Power and spreading factor control in low power wide area networks

Reynders, Brecht; Meert, Wannes; Pollin, Sofie

doi:10.1109/icc.2017.7996380

Cited by 171 publications

(195 citation statements)

References 5 publications

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“…That matches the variation of the SNR threshold in Table I (ψ i ) and is also aligned with the ADR power and SF allocation method defined by LoRaWAN. Still, in Figure 2, the dotted curve shows the discrete practical power allocation, obtained by rounding up the continuous values of (5). That mostly impacts the power of nodes closer to the gateway.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…Figure 2 also shows the average power in the network from (6) as 12.63 dBm -an average power reduction of 27%. Figures 3 and 4 show results using two approaches: power allocation as in (5), and all nodes with maximum power (14 dBm). The most noticeable aspect is that proper power allocation allows all nodes in the network to experience similar outage probabilities close to the target T C 0 = 0.01.…”

Section: Numerical Resultsmentioning

confidence: 99%

“…Our model preserves the PPP properties for each point as long as the fixed communication distances and transmit powers satisfy P 1 g 1 P k g k = 1 in (3), which is guaranteed by (5).…”

Section: A Outage Probability With Transmit Power Allocationmentioning

confidence: 96%

See 2 more Smart Citations

Performance Analysis of Single-Cell Adaptive Data Rate-Enabled LoRaWAN

Hoeller

Souza

Montejo‐Sánchez

et al. 2020

IEEE Wireless Commun. Lett.

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LoRaWAN enables massive connectivity for Internet-of-Things applications. Many published works employ stochastic geometry to derive outage models of LoRaWAN over fading channels assuming fixed transmit power and distance-based spreading factor (SF) allocation. However, in practice, LoRaWAN employs the Adaptive Data Rate (ADR) mechanism, which dynamically adjusts SF and transmit power of nodes based on channel state. The community addressed the performance of ADR using simulations, but analytical models have not been introduced. In this letter, we seek to close this gap. We build over an analytical LoRaWAN model to consider the performance of steady-state ADR-enabled LoRaWAN. We derive outage expressions and an optimization procedure to maximize the number of users under reliability constraints. Results show that power allocation reduces interference and improves network capacity while reducing average power.

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Section: Numerical Resultsmentioning

confidence: 99%

Section: Numerical Resultsmentioning

confidence: 99%

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Performance Analysis of Single-Cell Adaptive Data Rate-Enabled LoRaWAN

Hoeller

Souza

Montejo‐Sánchez

et al. 2020

IEEE Wireless Commun. Lett.

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“…In addition, the authors in [11] propose an link probing regime to select transmission parameters in order to achieve lower energy consumption. In [12], the authors present a scheme to optimize the packet error rate fairness to avoid near-far problems.…”

Section: Related Workmentioning

confidence: 99%

A Novel Rate and Channel Control Scheme Based on Data Extraction Rate for LoRa Networks

Zhou

Xing

Hou

et al. 2019

2019 IEEE Wireless Communications and Networking Conference (WCNC)

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Long Range (LoRa) has become one of the most popular Low Power Wide Area (LPWA) technologies, which provides a desirable trade-off among communication range, battery life, and deployment cost. In LoRa networks, several transmission parameters can be allocated to ensure efficient and reliable communication. For example, the configuration of the spreading factor allows tuning the data rate and the transmission distance. However, how to dynamically adjust the setting that minimizes the collision probability while meeting the required communication performance is an open challenge. This paper proposes a novel Data Rate and Channel Control (DRCC) scheme for LoRa networks so as to improve wireless resource utilization and support a massive number of LoRa nodes. The scheme estimates channel conditions based on the short-term Data Extraction Rate (DER), and opportunistically adjusts the spreading factor to adapt the variation of channel conditions. Furthermore, the channel control is carried out to balance the link load of all available channels with the global information of the channel usage, which is able to lower the access collisions under dense deployments. Our experiments demonstrate that the proposed DRCC performs well on improving the reliability and capacity compared with other spreading factor allocation schemes in dense deployment scenarios.

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“…More recently, [10] also unveiled a significant drop in performance when taking into account the inter-SF interferences in high-density deployments.In [13], the authors proposed a model for analyzing the performance of a multi-cell LoRa April 26, 2019 DRAFT 3 system considering co-SF interference, inter-SF interference, and the aggregated intra and intercell interferences. They also highlighted the necessity for an SF allocation scheme accounting for these interferences.In order to improve the LoRa system performance, a number of works have proposed resource optimization methods [14][15][16]. However, most papers, so far, have assumed perfect orthogonality among SFs.…”

mentioning

confidence: 99%

Joint Allocation Strategies of Power and Spreading Factors With Imperfect Orthogonality in LoRa Networks

Amichi¹,

Kaneko²,

Fukuda³

et al. 2020

IEEE Trans. Commun.

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The LoRa physical layer is one of the most promising Low Power Wide-Area Network (LPWAN) technologies for future Internet of Things (IoT) applications. It provides a flexible adaptation of coverage and data rate by allocating different Spreading Factors (SFs) and transmit powers to end-devices. We focus on improving throughput fairness while reducing energy consumption. Whereas most existing methods assume perfect SF orthogonality and ignore the harmful effects of inter-SF interferences, we formulate a joint SF and power allocation problem to maximize the minimum uplink throughput of end-devices, subject to co-SF and inter-SF interferences, and power constraints. This results into a mixed-integer non-linear optimization, which, for tractability, is split into two sub-problems: firstly, the SF assignment for fixed transmit powers, and secondly, the power allocation given the previously obtained assignment solution. For the first sub-problem, we propose a low-complexity many-to-one matching algorithm between SFs and end-devices. For the second one, given its intractability, we transform it using two types of constraints' approximation: a linearized and a quadratic version. Our performance evaluation demonstrates that the proposed joint SF allocation and power optimization enables to drastically enhance various performance objectives such as throughput, fairness and power consumption, and that it outperforms baseline schemes. 1 DRAFT 2 I. INTRODUCTIONA wide range of applications will be enabled by the advent of Internet of Things (IoT) technology, among which smart cities, intelligent transportation systems and environmental monitoring.Given the expected proliferation of such IoT devices in the near future, providing tailored wireless communication protocols with high spectral efficiency and low power consumption is becoming more and more urgent. Indeed, many of these services will depend on the future IoT Wireless Sensor Networks (WSNs), supported by the newly developed Low-Power Wide-Area Network (LPWAN) technologies such as LoRa, SigFox or Ingenu [2-5]. The LoRa physical layer uses the Chirp Spread Spectrum (CSS) modulation technique, where each chirp encodes 2 m values, for Spreading Factor (SF) m = 7 to 12 [6], and which allows multiple end-devices to use the same channel simultaneously. Based on the LoRa physical layer, LoRaWAN defines the MAC layer protocol standardized by LoRa Alliance [7]. It is an increasingly used LPWAN technology, as it operates in the ISM unlicensed bands and enables a flexible adaptation of transmission rates and coverages under low energy consumption [6]. The LoRaWAN architecture is a star topology,where end-devices communicate with the network server through gateways over several channels based on ALOHA mechanism, with duty cycle limitations [4]. In LoRaWAN, smaller SFs provide higher data rates but reduced ranges, while larger SFs allow longer ranges but lower rates [5].The main issue of LoRa-based networks such as LoRaWAN is the throughput limitation: the physical bitrate varies...

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Power and spreading factor control in low power wide area networks

Cited by 171 publications

References 5 publications

Performance Analysis of Single-Cell Adaptive Data Rate-Enabled LoRaWAN

Performance Analysis of Single-Cell Adaptive Data Rate-Enabled LoRaWAN

A Novel Rate and Channel Control Scheme Based on Data Extraction Rate for LoRa Networks

Joint Allocation Strategies of Power and Spreading Factors With Imperfect Orthogonality in LoRa Networks

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