Spreading Factor Allocation for Massive Connectivity in LoRa Systems

Lim, Jin-Taek; Han, Youngnam

doi:10.1109/lcomm.2018.2797274

Cited by 156 publications

(128 citation statements)

References 7 publications

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“…To analyze how an SF allocation scheme influences the network performance, we compare EIB with two additional SF allocation strategies, namely equal-area-based (EAB) [28] and path-loss-based (PLB) [29], [30] schemes. The EAB scheme uses equal-area annuli while PLB defines annuli based on a path loss model and the SF-specific SNR thresholds.…”

Section: Sf Allocation Strategiesmentioning

confidence: 99%

Scalability Analysis of a LoRa Network Under Imperfect Orthogonality

Mahmood

Sisinni

Guntupalli

et al. 2019

IEEE Trans. Ind. Inf.

198

197

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Low-power wide-area network (LPWAN) technologies are gaining momentum for internet-of-things (IoT) applications since they promise wide coverage to a massive number of battery-operated devices using grant-free medium access. LoRaWAN, with its physical (PHY) layer design and regulatory efforts, has emerged as the widely adopted LPWAN solution. By using chirp spread spectrum modulation with qausi-orthogonal spreading factors (SFs), LoRa PHY offers coverage to wide-area applications while supporting high-density of devices. However, thus far its scalability performance has been inadequately modeled and the effect of interference resulting from the imperfect orthogonality of the SFs has not been considered. In this paper, we present an analytical model of a single-cell LoRa system that accounts for the impact of interference among transmissions over the same SF (co-SF) as well as different SFs (inter-SF). By modeling the interference field as Poisson point process under duty-cycled ALOHA, we derive the signal-to-interference ratio (SIR) distributions for several interference conditions. Results show that, for a duty cycle as low as 0.33%, the network performance under co-SF interference alone is considerably optimistic as the inclusion of inter-SF interference unveils a further drop in the success probability and the coverage probability of approximately 10% and 15%, respectively for 1500 devices in a LoRa channel. Finally, we illustrate how our analysis can characterize the critical device density with respect to cell size for a given reliability target.Index Terms-Low power wide area networks, LoRaWAN, interference analysis, coverage probability, fading channels A. Mahmood, L. Guntupalli, R. Rondón and M. Gidlund are with the

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Section: Sf Allocation Strategiesmentioning

confidence: 99%

Scalability Analysis of a LoRa Network Under Imperfect Orthogonality

Mahmood

Sisinni

Guntupalli

et al. 2019

IEEE Trans. Ind. Inf.

198

197

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“…, 5. The pathloss-based SF allocation assigns the users while respecting Table I in [4], [6]. We can observe that the pathloss-based SF allocation, and the fair SF allocation tend to assign more users to lower SFs, while the other algorithms assign the users to all SFs.…”

Section: Sf Allocation Algorithms: Fairness or Unfairness?mentioning

confidence: 98%

“…The received signal at the gateway should exceed its sensitivity. The receiver sensitivity of the gateway depends on SF as shown in Table I in [4], [6]. In the literature, there are different ways to allocate the SFs between the users, as was mentioned in Section I.…”

Section: A Unfair and Fair Sf Allocation Algorithmsmentioning

confidence: 99%

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Minimum Throughput Maximization in LoRa Networks Powered by Ambient Energy Harvesting

Benkhelifa

Qin

McCann

2019

ICC 2019 - 2019 IEEE International Conference on Communications (ICC)

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In this paper, we investigate the uplink transmissions in low-power wide-area networks (LPWAN) where the users are self-powered by the energy harvested from the ambient environment. Demonstrating their potential in supporting diverse Internet-of-Things (IoT) applications, we focus on long range (LoRa) networks where the LoRa users are using the harvested energy to transmit data to a gateway via different spreading codes. Precisely, we study the throughput fairness optimization problem for LoRa users by jointly optimizing the spreading factor (SF) assignment, energy harvesting (EH) time duration, and the transmit power of LoRa users. First, through examination of the various permutations of collisions among users, we derive a general expression of the packet collision time between LoRa users, which depends on the SFs and EH duration requirements. Then, after reviewing prior SF allocation work, we develop two types of algorithms that either assure fair SF assignment indeed purposefully 'unfair' allocation schemes for the LoRa users. Our results unearth three new findings. Firstly, we demonstrate that, to maximize the minimum rate, the unfair SF allocation algorithm outperforms the other approaches. Secondly, considering the derived expression of packet collision between simultaneous users, we are now able to improve the performance of the minimum rate of LoRa users and show that it is protected from inter-SF interference which occurs between users with different SFs. That is, imperfect SF orthogonality has no impact on minimum rate performance. Finally, we have observed that co-SF interference is the main limitation in the throughput performance, and not the energy scarcity.

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“…In the context of LoRa networks, a mathematical analysis on the uplink coverage is conducted in [9] via stochastic geometry, which yet considers only the strongest interferer and ignores the time dependence of (partially) overlapping packets. Recent works in [10] and [11] consider channel fading, aggregate interference, and accurate packet overlapping, and yet it is difficult to obtain the exact distribution of packet success probability analytically. In summary, a tractable and accurate analytical model is highly needed for the performance evaluation in LoRa networks, which also facilitates further system optimization with low-complexity and low-overhead design.…”

Section: Introductionmentioning

confidence: 99%

Achieving Max-Min Throughput in LoRa Networks

Lyu

2020

2020 International Conference on Computing, Networking and Communications (ICNC)

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With growing popularity, LoRa networks are pivotally enabling Long Range connectivity to low-cost and powerconstrained user equipments (UEs). Due to its wide coverage area, a critical issue is to effectively allocate wireless resources to support potentially massive UEs in the cell while resolving the prominent near-far fairness problem for cell-edge UEs, which is challenging to address due to the lack of tractable analytical model for the LoRa network and its practical requirement for lowcomplexity and low-overhead design. To achieve massive connectivity with fairness, we investigate the problem of maximizing the minimum throughput of all UEs in the LoRa network, by jointly designing high-level policies of spreading factor (SF) allocation, power control, and duty cycle adjustment based only on average channel statistics and spatial UE distribution. By leveraging on the Poisson rain model along with tailored modifications to our considered LoRa network, we are able to account for channel fading, aggregate interference and accurate packet overlapping, and still obtain a tractable and yet accurate closed-form formula for the packet success probability and hence throughput. We further propose an iterative balancing (IB) method to allocate the SFs in the cell such that the overall max-min throughput can be achieved within the considered time period and cell area. Numerical results show that the proposed scheme with optimized design greatly alleviates the near-far fairness issue, and significantly improves the cell-edge throughput.

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Spreading Factor Allocation for Massive Connectivity in LoRa Systems

Cited by 156 publications

References 7 publications

Scalability Analysis of a LoRa Network Under Imperfect Orthogonality

Scalability Analysis of a LoRa Network Under Imperfect Orthogonality

Minimum Throughput Maximization in LoRa Networks Powered by Ambient Energy Harvesting

Achieving Max-Min Throughput in LoRa Networks

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