An improved envelope amplifier architecture for envelope tracking RF power amplifiers is presented, consisting of two switching amplifiers and one linear amplifier. The first switching amplifier and the linear amplifier provide wideband and high-efficiency operation, while the second switching amplifier provides a reduced bandwidth variable supply to the linear amplifier to further reduce power loss. The first switching amplifier and the linear amplifier are fabricated together in a 150 nm CMOS process, while the second switching amplifier is external. Measurements show a maximum average efficiency of 82% for a 10 MHz LTE signal with a 6 dB PAPR at 29.7 dBm output power and an SFDR of 63 dBc for a single tone of 5 MHz driving an 8 Ω load.

A high-efficiency envelope tracking power amplifier for long-term evolution (LTE) handset mobile terminals is presented. The envelope amplifier consists of a wideband buffered linear amplifier as a voltage source and a hysteretically controlled switching amplifier as a dependent current source. The linear amplifier has a high current drive capability of approximately 500 mA while consuming only 12 mA of quiescent current. The impact of envelope shaping on system efficiency and stability is investigated. The envelope amplifier is implemented in a 0.15- μm CMOS process and tested with a GaAs HBT RF power amplifier. For a 20-MHz LTE signal with 6.6-dB peak-to-average power ratio, an overall efficiency of 43% is achieved at 29-dBm RF output power level with relative constellation error below 1.9% after digital pre-distortion.

Networks of spatially distributed radiofrequency identification sensors could be used to collect data in wearable or implantable biomedical applications. However, the development of scalable networks remains challenging. Here we report a wireless radiofrequency network approach that can capture sparse event-driven data from large populations of spatially distributed autonomous microsensors. We use a spectrally efficient, low-error-rate asynchronous networking concept based on a code-division multiple-access method. We experimentally demonstrate the network performance of several dozen submillimetre-sized silicon microchips and complement this with large-scale in silico simulations. To test the notion that spike-based wireless communication can be matched with downstream sensor population analysis by neuromorphic computing techniques, we use a spiking neural network machine learning model to decode prerecorded open source data from eight thousand spiking neurons in the primate cortex for accurate prediction of hand movement in a cursor control task.

Implemented in a 0.25-/spl mu/m SiGe BiCMOS process, a highly integrated low-power transmitter IC (TxIC) is developed for wideband code-division multiple-access handset applications. Based on a digital-IF heterodyne architecture, it eliminates the external IF surface acoustic wave filter by adopting a meticulous frequency plan and a special-purpose second-order-hold D/A conversion scheme. The TxIC features a low-power high-speed D/A converter designed to drive a dominantly capacitive load. For the upconversion mixer and the RF amplifier, adaptive biases are designed to minimize the quiescent power consumption and to provide current boost only when needed. The TxIC achieves <1% EVM. It consumes 180 mW (3-V supply) for the maximum output power of +5 dBm and reduces to 120 mW during power backoff.

Transmitting meaningful information into brain circuits by electronic means is a challenge facing brain-computer interfaces. A key goal is to find an approach to inject spatially structured local current stimuli across swaths of sensory areas of the cortex. Here, we introduce a wireless approach to multipoint patterned electrical microstimulation by a spatially distributed epicortically implanted network of silicon microchips to target specific areas of the cortex. Each sub-millimeter-sized microchip harvests energy from an external radio-frequency source and converts this into biphasic current injected focally into tissue by a pair of integrated microwires. The amplitude, period, and repetition rate of injected current from each chip are controlled across the implant network by implementing a pre-scheduled, collision-free bitmap wireless communication protocol featuring sub-millisecond latency. As a proof-of-concept technology demonstration, a network of 30 wireless stimulators was chronically implanted into motor and sensory areas of the cortex in a freely moving rat for three months. We explored the effects of patterned intracortical electrical stimulation on trained animal behavior at average RF powers well below regulatory safety limits.