An 802.11ba-Based Wake-Up Radio Receiver With Wi-Fi Transceiver Integration

Liu, Renzhi; Beevi, K T Asma; Dorrance, Richard; Dasalukunte, Deepak; Kristem, Vinod; Lopez, Mario A. Santana; Min, Alexander W.; Azizi, Shahrnaz; Park, Minyoung; Carlton, Brent

doi:10.1109/jssc.2019.2957651

Cited by 33 publications

(22 citation statements)

References 8 publications

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“…The prototype operates at a bias voltage of 2.6 V and is powered through a single LIR2032 battery. Our previous work [9] demonstrated that the address detector circuit is characterized by a sensitivity of −40 dBm when combined with the rectifier designed and implemented in 1.5 µF R 16 15 kΩ [41]. In [9], we show that the combination achieves a wake-up distance of 27.5 meters at a transmit power of 15.4 dBm.…”

Section: B Current Consumption Sensitivity and Data Ratementioning

confidence: 79%

“…The correlator is either permanently powered ON [12]- [20], duty-cycled [6], or placed in a low power mode [21]- [26]. Additionally, a local oscillator generates the clock required for synchronization [6], [12]- [16], [18], [20], [21]. A common baseband implementation is presented in [22], where a microcontroller is used as a bit correlator.…”

Section: Introductionmentioning

confidence: 99%

“…The added noise activates the bit correlator [22], [25] or causes a false wake-up of the IoT device [22], [23], [25]. The available solutions implement a preamble detector for interference avoidance [21], [25] or synchronization [6], [11], [16], [21], [28], but do not consider the preamble's potential for carrying instructions. The coded preamble concept has been suggested to enhance the wake-up signal's data delivery efficiency and improve noise immunity [29].…”

Section: Introductionmentioning

confidence: 99%

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Tunable, Asynchronous, and Nanopower Baseband Receiver for Charging and Wakeup of IoT Devices

Benbuk

Kouzayha

Costantine

et al. 2022

IEEE Internet Things J.

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This paper proposes a novel ultra-low power, tunable, and asynchronous baseband architecture for joint radio frequency (RF) wake-up and charging receivers. The designed system switches between the wake-up and charging operations based on the type of the received RF signal. To our knowledge, the proposed system is the first of a kind that introduces multiple power states to reduce the energy consumption by sequentially activating minimal components required for RF wake-up or charging. The fabricated prototype, using off-theshelf components, features a sensitivity of -40 dBm, a bit rate of 500 bps, and a current consumption of 225 nA at a bias voltage of 2.6 V in the listening state. Current consumption is estimated at 3.225 µA and 13.725 µA while processing the preamble and bit sequence, respectively. The address detector is powered OFF during charging to reduce the system's current consumption to 150 nA. Our experimental results show that shutting down the address detector during charging reduces charging time and allows charging from received power levels that are as low as -6 dBm. We demonstrate that, operating the detector with multiple power modes reduces its current consumption and enhances its noise immunity when compared to conventional address detectors with two power modes of operation.

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Section: B Current Consumption Sensitivity and Data Ratementioning

confidence: 79%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Tunable, Asynchronous, and Nanopower Baseband Receiver for Charging and Wakeup of IoT Devices

Benbuk

Kouzayha

Costantine

et al. 2022

IEEE Internet Things J.

View full text Add to dashboard Cite

show abstract

“…This helps in improved throughput with lower energy consumption. The formation of the network with said delivery rates causes congestion at a large denser network in a dynamic environment [14,15]. Li et al [16] had carried out a case study on performance evaluation for Wi-Fi sniffing that support optimal groups.…”

Section: Literature Surveymentioning

confidence: 99%

“…In LA, the initial stage of Wi-Fi process enables user for complete competitive analysis for determining the probability of occurrence of each node. This leads in decisive dead spots that avoids slow and unstable connections [14][15][16]. The inter-interference region can cause decrease in deployment efficiency with more IT investment.…”

Section: Introductionmentioning

confidence: 99%