Alyosha Molnar

Low-Power 2.4-GHz Transceiver With Passive RX Front-End and 400-mV Supply

An ultra low power 2.4-GHz transceiver targeting wireless sensor network applications is presented. The receiver front-end is fully passive, utilizing an integrated resonant matching network to achieve voltage gain and interface directly to a passive mixer. The receiver achieves a 7-dB noise figure and -7.5-dBm IIP3 while consuming 330 muW from a 400-mV supply. The binary FSK transmitter delivers 300 muW to a balanced 50-Omega load with 30% overall efficiency and 45% power amplifier (PA) efficiency. Performance of the receiver topology is analyzed and simple expressions for the gain and noise figure of both the passive mixer and matching network are derived. An analysis of passive mixer input impedance reveals the potential to reject interferers at the mixer input with characteristics similar to an extremely high-Q parallel LC filter centered at the switching frequency

Implications of Passive Mixer Transparency for Impedance Matching and Noise Figure in Passive Mixer-First Receivers

In this paper, a class of passive mixer-first, LNA-less receivers is analyzed in depth. Quadrature passive mixers are shown to present the impedance of their baseband port to the RF port and vice versa. This transparency property, in combination with resistive feedback differential amplifiers, and “complex” feedback between the I and Q paths, can be used to control the impedance at the RF port. This impedance can be tuned using only baseband components (i.e., resistors). The noise limits of such an architecture are analyzed and simulated, and are shown to be comparable to standard RF-LNA-first receivers. Accounting for the higher harmonics of the LO frequency proves critical in accurately analyzing the behavior of these circuits and their ability to provide an impedance match with low noise figure. Additionally, it is shown that expanding quadrature passive mixers to harmonic rejection mixers allows for even better noise performance and wider matching range.

An ultra-low power 900 MHz RF transceiver for wireless sensor networks

A 900 MHz, ultra-low power RF transceiver is presented for wireless sensor networks. It radiates -6 dBm in transmit mode and has a receive sensitivity of -94 dBm while consuming less than 1.3 mW in either mode from a 3 volt battery. Two of these transceivers have been demonstrated communicating over 16 meters through walls at a bit rate of 20 kbps while using only 4 off-chip components.

An Ultra-Low Power 2.4GHz RF Transceiver for Wireless Sensor Networks in 0.13/spl mu/m CMOS with 400mV Supply and an Integrated Passive RX Front-End

A 2.4GHz RF transceiver in 130nm CMOS for sensor networks is presented. The transceiver operates from 400mV to accommodate a single solar cell power supply. The RX dissipates 200 to 750muW and achieves a 6.7dB NF and a -6.2dBm IIP3 at 330muW. At 300muW output power, the PA is 44% efficient and the overall TX is 30% efficient

The In-Crowd Algorithm for Fast Basis Pursuit Denoising

We introduce a fast method, the “in-crowd” algorithm, for finding the exact solution to basis pursuit denoising problems. The in-crowd algorithm discovers a sequence of subspaces guaranteed to arrive at the support set of the final solution of l1 -regularized least squares problems. We provide theorems showing that the in-crowd algorithm always converges to the correct global solution to basis pursuit denoising problems. We show empirically that the in-crowd algorithm is faster than the best alternative solvers (homotopy, fixed point continuation and spectral projected gradient for l1 minimization) on certain well- and ill-conditioned sparse problems with more than 1000 unknowns. We compare the in-crowd algorithms performance in high- and low-noise regimes, demonstrate its performance on more dense problems, and derive expressions giving its computational complexity.

A passive-mixer-first receiver with baseband-controlled RF impedance matching, ≪ 6dB NF, and ≫ 27dBm wideband IIP3

A software-defined radio (SDR) ideally allows all of the parameters of the radio to be programmed dynamically. SDRs so far have shown flexibility in bandwidth (BW) [1], local oscillator (LO) frequency [2-4], gain, and modulation type. However, the impedance an RF front-end presents to its antenna has proven difficult to tune [5]. Since antenna impedance can vary significantly across frequency and different environments, a software-controlled input impedance is desirable. Meanwhile, recent work suggests that connecting the antenna directly to a passive mixer without an RF LNA can provide significant benefits, such as extremely low power [6] or greatly increased tuning range and linearity [2]. This paper demonstrates a passive mixer-first SDR with an RF impedance that is controlled by baseband components whose impedance is reflected through the passive mixer to the RF port.

Crossover inhibition in the retina: circuitry that compensates for nonlinear rectifying synaptic transmission

In the mammalian retina, complementary ON and OFF visual streams are formed at the bipolar cell dendrites, then carried to amacrine and ganglion cells via nonlinear excitatory synapses from bipolar cells. Bipolar, amacrine and ganglion cells also receive a nonlinear inhibitory input from amacrine cells. The most common form of such inhibition crosses over from the opposite visual stream: Amacrine cells carry ON inhibition to the OFF cells and carry OFF inhibition to the ON cells (”crossover inhibition”). Although these synapses are predominantly nonlinear, linear signal processing is required for computing many properties of the visual world such as average intensity across a receptive field. Linear signaling is also necessary for maintaining the distinction between brightness and contrast. It has long been known that a subset of retinal outputs provide exactly this sort of linear representation of the world; we show here that rectifying (nonlinear) synaptic currents, when combined thorough crossover inhibition can generate this linear signaling. Using simple mathematical models we show that for a large set of cases, repeated rounds of synaptic rectification without crossover inhibition can destroy information carried by those synapses. A similar circuit motif is employed in the electronics industry to compensate for transistor nonlinearities in analog circuits.

Light field image sensors based on the Talbot effect

We present a pixel-scale sensor that uses the Talbot effect to detect the local intensity and incident angle of light. The sensor comprises two local diffraction gratings stacked above a photodiode. When illuminated by a plane wave, the upper grating generates a self-image at the half Talbot depth. The second grating, placed at this depth, blocks or passes light depending upon incident angle. Several such structures, tuned to different incident angles, are sufficient to extract local incident angle and intensity. Furthermore, arrays of such structures are sufficient to localize light sources in three dimensions without any additional optics.

Low power RF design for sensor networks

The design of RF circuits for short-range, low-power wireless communication is discussed. A derivation of optimum link range and transceiver power budget is presented based on simple models for indoor path loss and power vs. performance tradeoffs in a generic transceiver. Design techniques aimed at efficiently reaching these parameters are discussed for individual circuit blocks. Finally, some published transceivers are discussed with respect to the optimization and design techniques presented.

A Light-Field Image Sensor in 180 nm CMOS

This paper presents a CMOS image sensor which captures local incident angle and intensity information from the light it records. The 400×384 pixel array employs 7.5 μm angle-sensitive pixels, which use pairs of local diffraction gratings above a photodiode to detect incident angle. The gratings are implemented with the metal interconnect layers of CMOS manufacturing technology and therefore require no post-processing or external optics. Fabricated in a 180 nm mixed-mode CMOS process, the sensor requires only a single lens to create a light-field image. Using the information contained in a single image, we demonstrate range finding with 2.5 mm precision at 1 m and post-capture refocus on complex visual scenes.