Self-Reconfigurable Analog Arrays: Off-The Shelf Adaptive Electronics for Space Applications

Development of analog electronic solutions for space avionics is expensive and lengthy. Lack of flexible analog devices, counterparts to digital Field Programmable Gate Arrays (FPGA), prevents analog designers from benefits of rapid prototyping. This forces them to expensive and lengthy custom design, fabrication, and qualification of application specific integrated circuits (ASIC). The limitations come from two directions: commercial Field Programmable Analog Arrays (FPAA) have limited variability in the components offered on-chip; and they are only qualified for best case scenarios for military grade (-55C to +125C). In order to avoid huge overheads, there is a growing trend towards avoiding thermal and radiation protection by developing extreme environment electronics, which maintain correct operation while exposed to temperature extremes (-180degC to +125degC). This paper describes a recent FPAA design, the Self-Reconfigurable Analog Array (SRAA) developed at JPL. It overcomes both limitations, offering a variety of analog cells inside the array together with the possibility of self-correction at extreme temperatures

Data Conversion Within Energy Constrained Environments

Within scientific research, engineering, and consumer electronics, there is a multitude of new discrete sensor-interfaced devices. Maintaining high accuracy in signal quantization while staying within the strict power-budget of these devices is a very challenging problem. Traditional paths to solving this problem include researching more energy-efficient digital topologies as well as digital scaling.;This work offers an alternative path to lower-energy expenditure in the quantization stage --- content-dependent sampling of a signal. Instead of sampling at a constant rate, this work explores techniques which allow sampling based upon features of the signal itself through the use of application-dependent analog processing. This work presents an asynchronous sampling paradigm, based off the use of floating-gate-enabled analog circuitry. The basis of this work is developed through the mathematical models necessary for asynchronous sampling, as well the SPICE-compatible models necessary for simulating floating-gate enabled analog circuitry. These base techniques and circuitry are then extended to systems and applications utilizing novel analog-to-digital converter topologies capable of leveraging the non-constant sampling rates for significant sample and power savings

Mixed Signal Integrated Circuit Design for Custom Sensor Interfacing

Low-power analog integrated circuits (ICs) can be utilized at the interface between an analog sensor and a digital system\u27s input to decrease power consumption, increase system accuracy, perform signal processing, and make the necessary adjustments for compatibility between the two devices. This interfacing has typically been done with custom integrated solutions, but advancements in floating-gate technologies have made reconfigurable analog ICs a competitive option. Whether the solution is a custom design or built from a reconfigurable system, digital peripheral circuits are needed to configure their operation for these analog circuits to work with the best accuracy.;Using an analog IC as a front end signal processor between an analog sensor and wireless sensor mote can greatly decrease battery consumption. Processing in the digital domain requires more power than when done on an analog system. An Analog Signal Processor (ASP) can allow the digital wireless mote to remain in sleep mode while the ASP is always listening for an important event. Once this event occurs, the ASP will wake the wireless mote, allowing it to record the event and send radio transmissions if necessary. As most wireless sensor networks employ the use of batteries as a power source, an energy harvesting system in addition to an ASP can be used to further supplement this battery consumption.;This thesis documents the development of mixed-signal integrated circuits for use as interfaces between analog sensors and digital Wireless Sensor Networks (WSNs). The following work outlines, as well as shows the results, of development for sensor interfacing utilizing both custom mixed signal integrated circuits as well as a Field Programmable Analog Array (FPAA) for post fabrication customization. An Analog Signal Processor (ASP) has been used in an Acoustic Vehicle Classification system. To keep these interfacing methods low power, a prototype energy harvesting system using commercial-off-the-shelf (COTS) devices is detailed which has led to the design of a fully integrated solution

Low-Power Reconfigurable Sensing Circuitry for the Internet-of-Things Paradigm

With ubiquitous wireless communication via Wi-Fi and nascent 5th Generation mobile communications, more devices -- both smart and traditionally dumb -- will be interconnected than ever before. This burgeoning trend is referred to as the Internet-of-Things. These new sensing opportunities place a larger burden on the underlying circuitry that must operate on finite battery power and/or within energy-constrained environments. New developments of low-power reconfigurable analog sensing platforms like field-programmable analog arrays (FPAAs) present an attractive sensing solution by processing data in the analog domain while staying flexible in design. This work addresses some of the contemporary challenges of low-power wireless sensing via traditional application-specific sensing and with FPAAs. A large emphasis is placed on furthering the development of FPAAs by making them more accessible to designers without a strong integrated-circuit background -- much like FPGAs have done for digital designers

Floating-Gate Design and Linearization for Reconfigurable Analog Signal Processing

Analog and mixed-signal integrated circuits have found a place in modern electronics design as a viable alternative to digital pre-processing. With metrics that boast high accuracy and low power consumption, analog pre-processing has opened the door to low-power state-monitoring systems when it is utilized in place of a power-hungry digital signal-processing stage. However, the complicated design process required by analog and mixed-signal systems has been a barrier to broader applications. The implementation of floating-gate transistors has begun to pave the way for a more reasonable approach to analog design. Floating-gate technology has widespread use in the digital domain. Analog and mixed-signal use of floating-gate transistors has only become a rising field of study in recent years. Analog floating gates allow for low-power implementation of mixed-signal systems, such as the field-programmable analog array, while simultaneously opening the door to complex signal-processing techniques. The field-programmable analog array, which leverages floating-gate technologies, is demonstrated as a reliable replacement to signal-processing tasks previously only solved by custom design. Living in an analog world demands the constant use and refinement of analog signal processing for the purpose of interfacing with digital systems. This work offers a comprehensive look at utilizing floating-gate transistors as the core element for analog signal-processing tasks. This work demonstrates the floating gate\u27s merit in large reconfigurable array-driven systems and in smaller-scale implementations, such as linearization techniques for oscillators and analog-to-digital converters. A study on analog floating-gate reliability is complemented with a temperature compensation scheme for implementing these systems in ever-changing, realistic environments

Reconfigurable Reflectarrays and Array Lenses for Dynamic Antenna Beam Control: A Review

Advances in reflectarrays and array lenses with electronic beam-forming capabilities are enabling a host of new possibilities for these high-performance, low-cost antenna architectures. This paper reviews enabling technologies and topologies of reconfigurable reflectarray and array lens designs, and surveys a range of experimental implementations and achievements that have been made in this area in recent years. The paper describes the fundamental design approaches employed in realizing reconfigurable designs, and explores advanced capabilities of these nascent architectures, such as multi-band operation, polarization manipulation, frequency agility, and amplification. Finally, the paper concludes by discussing future challenges and possibilities for these antennas.Comment: 16 pages, 12 figure

An Evolvable Combinational Unit for FPGAs

A complete hardware implementation of an evolvable combinational unit for FPGAs is presented. The proposed combinational unit consisting of a virtual reconfigurable circuit and evolutionary algorithm was described in VHDL independently of a target platform, i.e. as a soft IP core, and realized in the COMBO6 card. In many cases the unit is able to evolve (i.e. to design) the required function automatically and autonomously, in a few seconds, only on the basis of interactions with an environment. A number of circuits were successfully evolved directly in the FPGA, in particular, 3-bit multipliers, adders, multiplexers and parity encoders. The evolvable unit was also tested in a simulated dynamic environment and used to design various circuits specified by randomly generated truth tables

MFPA: Mixed-Signal Field Programmable Array for Energy-Aware Compressive Signal Processing

Compressive Sensing (CS) is a signal processing technique which reduces the number of samples taken per frame to decrease energy, storage, and data transmission overheads, as well as reducing time taken for data acquisition in time-critical applications. The tradeoff in such an approach is increased complexity of signal reconstruction. While several algorithms have been developed for CS signal reconstruction, hardware implementation of these algorithms is still an area of active research. Prior work has sought to utilize parallelism available in reconstruction algorithms to minimize hardware overheads; however, such approaches are limited by the underlying limitations in CMOS technology. Herein, the MFPA (Mixed-signal Field Programmable Array) approach is presented as a hybrid spin-CMOS reconfigurable fabric specifically designed for implementation of CS data sampling and signal reconstruction. The resulting fabric consists of 1) slice-organized analog blocks providing amplifiers, transistors, capacitors, and Magnetic Tunnel Junctions (MTJs) which are configurable to achieving square/square root operations required for calculating vector norms, 2) digital functional blocks which feature 6-input clockless lookup tables for computation of matrix inverse, and 3) an MRAM-based nonvolatile crossbar array for carrying out low-energy matrix-vector multiplication operations. The various functional blocks are connected via a global interconnect and spin-based analog-to-digital converters. Simulation results demonstrate significant energy and area benefits compared to equivalent CMOS digital implementations for each of the functional blocks used: this includes an 80% reduction in energy and 97% reduction in transistor count for the nonvolatile crossbar array, 80% standby power reduction and 25% reduced area footprint for the clockless lookup tables, and roughly 97% reduction in transistor count for a multiplier built using components from the analog blocks. Moreover, the proposed fabric yields 77% energy reduction compared to CMOS when used to implement CS reconstruction, in addition to latency improvements