Analysis of BER and Coverage Performance of LoRa Modulation under Same Spreading Factor Interference

Elshabrawy, Tallal; Robert, Jörg

doi:10.1109/pimrc.2018.8581011

Cited by 57 publications

(78 citation statements)

References 8 publications

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“…More importantly, LoRa relies on LoRaWAN for the MAC Convenient approximations for the bit-error rate (BER) of the LoRa modulation when transmission takes place over additive white Gaussian noise (AWGN) and Rayleigh fading channels are given in [28], but collisions are not considered. Finally, the work of [29], which is most closely related to our work, provides an approximation for the BER of the LoRa modulation under AWGN and interference from a single LoRa interferer with the same spreading factor (same-SF). Capacity planning for LoRa with the aforementioned interference model is addressed in [30].…”

Section: Introductionmentioning

confidence: 95%

“…In the special case of integer offsets τ (i.e., λ = 0 and τ = L) the above integral can be simplified to a sum over all the integer offsets L. Moreover, in such a case, the sets Y Ii are equivalent, meaning that there is only one set of equivalent interference patterns Y I . Therefore, the above expression can be further simplified to the expression found in [29] P (ŝ = s|s) = 1 N 2…”

Section: Complexity Reductionmentioning

confidence: 99%

“…We note that for the Monte Carlo simulations we use a more conservative ǫ = 1 /10, since they are used as a comparison baseline. Aligned [29] MC Approx. SF=9: SF=10: SF=11:…”

Section: A Choice Of Discretization Stepmentioning

confidence: 99%

“…In Fig. 7, we show the results of a Monte Carlo simulation Aligned [29] Approx. SF=7: SF=12: SIR (dB) SNR (dB) Fig.…”

Section: B Symbol Error Ratementioning

confidence: 99%

“…Contributions: The work of [29] made a significant first step toward understanding the behavior of LoRa under same-SF interference. In this paper, based on our own previous work of [31], we extend the interference model of [29] to the more general (and more realistic) case where the interference is neither chip-nor phase-aligned with the signal-of-interest. We derive an expression for the symbol error rate (SER) under this new complete interference model.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

On the Error Rate of the LoRa Modulation With Interference

Afisiadis

Cotting

Burg

et al. 2020

IEEE Trans. Wireless Commun.

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LoRa is a chirp spread-spectrum modulation developed for the Internet of Things. In this work, we examine the performance of LoRa in the presence of both additive white Gaussian noise and interference from another LoRa user. To this end, we extend an existing interference model, which assumes perfect alignment of the signal of interest and the interference, to the more realistic case where the interfering user is neither chip-nor phase-aligned with the signal of interest and we derive an expression for the error rate. We show that the existing aligned interference model overestimates the effect of interference on the error rate. Moreover, we prove two symmetries in the interfering signal and we derive low-complexity approximate formulas that can significantly reduce the complexity of computing the symbol and frame error rates compared to the complete expression. Finally, we provide numerical simulations to corroborate the theoretical analysis and to verify the accuracy of our proposed approximations. ). layer, which uses an ALOHA-based channel access scheme in which collisions are not explicitly avoided. These collisions lead to same-technology inter-user interference which may ultimately become the capacity-limiting factor in massive IoT scenarios [13]. For this reason, it is of great interest and importance to study the performance of LoRa under sametechnology interference.The authors of [14] present a mathematical network model for LoRa that includes the capture effect, i.e., the fact that a LoRa packet can be correctly decoded even under interference from another LoRa packet. A stochastic geometry framework for modeling the performance of a single gateway LoRa network is used in [15]. An investigation of the latency, collision rate, and throughput for LoRaWAN under duty-cycle restrictions is performed in [16]. Several real-world deployments of LoRa have been tested, but in order to assess the network scalability of LoRaWAN to future network densities that are expected to be orders of magnitude larger, evaluations through network simulators need to be performed. For this reason, the works of [17], [18] added LoRa functionality to the well-known ns-3 network simulator. A simpler Python-based network simulator for the LoRa uplink was first described in [19], and later extended for the LoRa downlink in [20]. The impact of the downlink feedback on LoRa capacity was also studied in [21]. A general overview and performance evaluations of LoRaWAN can be found in [13], [22].The impact of interference coming from different technologies on the performance of the LoRa modulation has received some attention in the literature. Specifically, [23] studies the co-existence of LoRa with IEEE 802.15.4g, while [24] studies the co-existence of LoRa with ultra-narrowband technologies, such as Sigfox. The impact of interference coming from other LoRa nodes has also received some attention. Specifically, the work of [25] extended the simulator of [19] in order to study the impact of imperfect orthogonality between different LoRa spr...

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Section: Introductionmentioning

confidence: 95%

Section: Complexity Reductionmentioning

confidence: 99%

“…We note that for the Monte Carlo simulations we use a more conservative ǫ = 1 /10, since they are used as a comparison baseline. Aligned [29] MC Approx. SF=9: SF=10: SF=11:…”

Section: A Choice Of Discretization Stepmentioning

confidence: 99%

“…In Fig. 7, we show the results of a Monte Carlo simulation Aligned [29] Approx. SF=7: SF=12: SIR (dB) SNR (dB) Fig.…”

Section: B Symbol Error Ratementioning

confidence: 99%