Improving Energy Efficiency and Reliability in WuR-Based IoT Systems: An Error Correction Approach

Rakovic, Valentin; Adamovski, Robert; Risteski, Aleksandar; Gavrilovska, Liljana

doi:10.1007/s11277-020-07464-2

Cited by 9 publications

(12 citation statements)

References 17 publications

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“…Furthermore, as ME coding has the best coding gain, it thus requires a lower power transmission than the other schemes. ME (7,3) and ME(15,4) consume, respectively 2.37 and 3.27 less than uncoded scheme at a distance of 28 m. It can also be seen that when applying Hamming the energy consumption is higher than the other schemes, Hamming (7,4) and Hamming(15,11) consume, respectively 1.75 and 1.19 more than uncoded scheme as the codeword is longer. The transmitter is turned on for longer time and the small coding gain achieved with Hamming does not compensate the power consumption of the PA.…”

Section: Energy Consumption Evaluationmentioning

confidence: 83%

“…In recent study [6] Basagni et al evaluated the range of WuR in a real field deployment. The study shows that WuR can receive the quasi totality of sent packets at a distance up to 24 m. Meanwhile, channel coding can be used to improve the sensitivity as presented by Rakovic et al in [7]. The study compares the performance of Hamming code, repetition code and Walsh code applied to WuRs.…”

Section: Introductionmentioning

confidence: 93%

“…Fig. 2 shows the BER as a function of E b N0 with uncoded scheme and when applying ME (7,3), ME(15,4), Hamming (7,4) and Hamming(15,11). Both theoretical and montecarlo simulations are presented.…”

Section: A Ber Evaluationmentioning

confidence: 99%

“…It can be seen that ME coding improves the BER compared to Hamming. With ME (7,3) and ME(15,4) at a BER of 10 −3 , E b N0 is equal to 9.2 dB and 8.7 dB, respectively and thus a coding gain of 1.8dB and 2.3dB is achieved. Meanwhile, with Hamming (7,4) and Hamming(15,11), E b N0 is equal to 10.7 dB and 10.1 dB, respectively for the same level of BER, and thus a small coding gain of 0.3dB and 0.9dB is achieved.…”

Section: A Ber Evaluationmentioning

confidence: 99%

“…With ME (7,3) and ME(15,4) at a BER of 10 −3 , E b N0 is equal to 9.2 dB and 8.7 dB, respectively and thus a coding gain of 1.8dB and 2.3dB is achieved. Meanwhile, with Hamming (7,4) and Hamming(15,11), E b N0 is equal to 10.7 dB and 10.1 dB, respectively for the same level of BER, and thus a small coding gain of 0.3dB and 0.9dB is achieved. It can also be seen that at a fixed E b N0 , ME coding reduces the BER compared to the other schemes.…”

Section: A Ber Evaluationmentioning

confidence: 99%

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Enhancing Wake-Up Radio Range Through Minimum Energy Coding

Djidi

Gautier

Courtay

et al. 2021

ICC 2021 - IEEE International Conference on Communications

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A substantial part of the research on wireless sensor networks is focused on the optimization of the energy consumption through either hardware or protocol communication stacks. Wake-up Receivers (WuRs) represent a new paradigm that offers both ultra low power consumption and low latency through asynchronous communications. However, WuRs have a low sensitivity and thus can misinterpret the received signal inducing a performance degradation of the whole communicating system. To tackle this issue, low power channel coding techniques can be used and we propose in this work to apply Hamming coding and Minimum Energy Coding (ME) to enhance WuR range. A performance study of these two types of coding shows that ME coding outperforms Hamming code in reducing both bit error rate and energy consumption. At a range of 28 m, ME coding saves about 3 times the energy at a bit error rate of 10 −3 compared to uncoded scheme. Furthermore, experimentation on the missed wake-ups when applying ME coding was done, showing a gain of 22% in reliability compared to uncoded scheme.

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