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Future wireless sensor networks require reliable, batteryless, miniaturized, low-cost sensor nodes with ultralow power consumption. Remote RF powering provides a reliable wireless power source for such monolithically integrated sensor nodes. Combining highly integrated ultralow power millimeter-wave (mm-wave) sensing, wireless power transfer, and on-chip antenna is a path toward batteryless, fully monolithically integrated, millimeter-sized sensor nodes with only a few milligrams of weight. In this paper, a passive fully integrated monolithic wireless sensor for mm-wave sensing is presented in a 65-nm CMOS technology, including an on-chip wireless power receiver, on-chip antenna, and a low-power transmitter.

With the growing attention at 60 GHz ISM band on millimeter-wave therapy for diseases treatment of sedative, anti-inflammatory actions or immune system stimulation, growing demand for new biomedical monitoring and treating systems with more bandwidth, high data rates and low power creates new challenges for 60 GHz body area network. Most smart wireless sensors wireless sensing operates on battery, which limits their life-time. To overcome this limitation, a system of radio-triggered batteryless monolithic wireless sensor based on mm-wave wireless power transfer technique is introduced in this work. From the system power budget analysis, it could support 10 bits communication within 10 cm, which would be sufficient for mm-wave wireless sensing application. Furthermore, it is identified that the receiver is power limited. Based on the system evaluation, an injection locked oscillator based self-mixing receiver is presented. In this architecture, the IJLO based LO scheme is used to save receiver power consumption. The sensitivity of the receiver is improved by applying the IJLO into the self-mixing architecture. This single chip receiver is implemented in a 65 nm CMOS technology. The DC power consumption of this receiver is only 16.4 mA from 1 V power supply. This power consumption is lower than other mm-wave receivers, which is an important step towards fully integrated monolithic sensor nodes.

Wideband cognitive radios (CRs) receive signals from multiple transmitters simultaneously to increase spectrum utilization. Processing a wideband spectrum is challenging due to large dynamic range (DR) of the received signal and required high sampling speed of the ADC. The power consumption of high sampling speed/high-resolution ADCs have been prohibitive for handheld radios. However, in CR applications strong inband signals that pose large DR requirements can be filtered out, since CR needs to detect unused spectrum bands where no signal is present. Spatial domain filtering approaches through use of multiple antennas to reduce DR of the wideband signal are proposed. Algorithms and architectures are developed for vector beamforming (multiple antennas and a single ADC) and full multiple-input multiple-output (MIMO) (multiple antennas with an ADC per antenna) analog spatial filters for adaptive interference suppression. Simulation results indicate that for realistic indoor propagation environments the ADC resolution of an analog beamformer can be reduced by 4 bits when the receiver operates at 2 bits/s/Hz, reducing ADC power consumption by approximately 90%. Moreover, simulations indicate that full MIMO analog spatial filter can reduce ADC resolution with over 3 bits per ADC when the receiver operates at 5 bits/s/Hz, reducing ADC power consumption by approximately 85%. [ABSTRACT FROM PUBLISHER]