Low Power Decoding Circuits for Ultra Portable Devices

A wide spread of existing and emerging battery driven wireless devices do not necessarily demand high data rates. Rather, ultra low power, portability and low cost are the most desired characteristics. Examples of such applications are wireless sensor networks (WSN), body area networks (BAN), and a variety of medical implants and health-care aids. Being small, cheap and low power for the individual transceiver nodes, let those to be used in abundance in remote places, where access for maintenance or recharging the battery is limited. In such scenarios, the lifetime of the battery, in most cases, determines the lifetime of the individual nodes. Therefore, energy consumption has to be so low that the nodes remain operational for an extended period of time, even up to a few years. It is known that using error correcting codes (ECC) in a wireless link can potentially help to reduce the transmit power considerably. However, the power consumption of the coding-decoding hardware itself is critical in an ultra low power transceiver node. Power and silicon area overhead of coding-decoding circuitry needs to be kept at a minimum in the total energy and cost budget of the transceiver node. In this thesis, low power approaches in decoding circuits in the framework of the mentioned applications and use cases are investigated. The presented work is based on the 65nm CMOS technology and is structured in four parts as follows: In the first part, goals and objectives, background theory and fundamentals of the presented work is introduced. Also, the ECC block in coordination with its surrounding environment, a low power receiver chain, is presented. Designing and implementing an ultra low power and low cost wireless transceiver node introduces challenges that requires special considerations at various levels of abstraction. Similarly, a competitive solution often occurs after a conclusive design space exploration. The proposed decoder circuits in the following parts are designed to be embedded in the low power receiver chain, that is introduced in the first part. Second part, explores analog decoding method and its capabilities to be embedded in a compact and low power transceiver node. Analog decod- ing method has been theoretically introduced over a decade ago that followed with early proof of concept circuits that promised it to be a feasible low power solution. Still, with the increased popularity of low power sensor networks, it has not been clear how an analog decoding approach performs in terms of power, silicon area, data rate and integrity of calculations in recent technologies and for low data rates. Ultra low power budget, small size requirement and more relaxed demands on data rates suggests a decoding circuit with limited complexity. Therefore, the four-state (7,5) codes are considered for hardware implementation. Simulations to chose the critical design factors are presented. Consequently, to evaluate critical specifications of the decoding circuit, three versions of analog decoding circuit with different transistor dimensions fabricated. The measurements results reveal different trade-off possibilities as well as the potentials and limitations of the analog decoding approach for the target applications. Measurements seem to be crucial, since the available computer-aided design (CAD) tools provide limited assistance and precision, given the amount of calculations and parameters that has to be included in the simulations. The largest analog decoding core (AD1) takes 0.104mm2 on silicon and the other two (AD2 and AD3) take 0.035mm2 and 0.015mm2, respectively. Consequently, coding gain in trade-off with silicon area and throughput is presented. The analog decoders operate with 0.8V supply. The achieved coding gain is 2.3 dB at bit error rates (BER)=0.001 and 10 pico-Joules per bit (pJ/b) energy efficiency is reached at 2 Mbps. Third part of this thesis, proposes an alternative low power digital decoding approach for the same codes. The desired compact and low power goal has been pursued by designing an equivalent digital decoding circuit that is fabricated in 65nm CMOS technology and operates in low voltage (near-threshold) region. The architecture of the design is optimized in system and circuit levels to propose a competitive digital alternative. Similarly, critical specifications of the decoder in terms of power, area, data rate (speed) and integrity are reported according to the measurements. The digital implementation with 0.11mm2 area, consumes minimum energy at 0.32V supply which gives 9 pJ/b energy efficiency at 125 kb/s and 2.9 dB coding gain at BER=0.001. The forth and last part, compares the proposed design alternatives based on the fabricated chips and the results attained from the measurements to conclude the most suitable solution for the considered target applications. Advantages and disadvantages of both approaches are discussed. Possible extensions of this work is introduced as future work

A Bio-Inspired Two-Layer Mixed-Signal Flexible Programmable Chip for Early Vision

A bio-inspired model for an analog programmable array processor (APAP), based on studies on the vertebrate retina, has permitted the realization of complex programmable spatio-temporal dynamics in VLSI. This model mimics the way in which images are processed in the visual pathway, what renders a feasible alternative for the implementation of early vision tasks in standard technologies. A prototype chip has been designed and fabricated in 0.5 μm CMOS. It renders a computing power per silicon area and power consumption that is amongst the highest reported for a single chip. The details of the bio-inspired network model, the analog building block design challenges and trade-offs and some functional tests results are presented in this paper.Office of Naval Research (USA) N-000140210884European Commission IST-1999-19007Ministerio de Ciencia y Tecnología TIC1999-082

Second-order neural core for bioinspired focal-plane dynamic image processing in CMOS

Based on studies of the mammalian retina, a bioinspired model for mixed-signal array processing has been implemented on silicon. This model mimics the way in which images are processed at the front-end of natural visual pathways, by means of programmable complex spatio-temporal dynamic. When embedded into a focal-plane processing chip, such a model allows for online parallel filtering of the captured image; the outcome of such processing can be used to develop control feedback actions to adapt the response of photoreceptors to local image features. Beyond simple resistive grid filtering, it is possible to program other spatio-temporal processing operators into the model core, such as nonlinear and anisotropic diffusion, among others. This paper presents analog and mixed-signal very large-scale integration building blocks to implement this model, and illustrates their operation through experimental results taken from a prototype chip fabricated in a 0.5-μm CMOS technology.European Union IST 2001 38097Ministerio de Ciencia y Tecnología TIC 2003 09817 C02 01Office of Naval Research (USA) N00014021088

Radiation Hardened by Design Methodologies for Soft-Error Mitigated Digital Architectures

abstract: Digital architectures for data encryption, processing, clock synthesis, data transfer, etc. are susceptible to radiation induced soft errors due to charge collection in complementary metal oxide semiconductor (CMOS) integrated circuits (ICs). Radiation hardening by design (RHBD) techniques such as double modular redundancy (DMR) and triple modular redundancy (TMR) are used for error detection and correction respectively in such architectures. Multiple node charge collection (MNCC) causes domain crossing errors (DCE) which can render the redundancy ineffectual. This dissertation describes techniques to ensure DCE mitigation with statistical confidence for various designs. Both sequential and combinatorial logic are separated using these custom and computer aided design (CAD) methodologies. Radiation vulnerability and design overhead are studied on VLSI sub-systems including an advanced encryption standard (AES) which is DCE mitigated using module level coarse separation on a 90-nm process with 99.999% DCE mitigation. A radiation hardened microprocessor (HERMES2) is implemented in both 90-nm and 55-nm technologies with an interleaved separation methodology with 99.99% DCE mitigation while achieving 4.9% increased cell density, 28.5 % reduced routing and 5.6% reduced power dissipation over the module fences implementation. A DMR register-file (RF) is implemented in 55 nm process and used in the HERMES2 microprocessor. The RF array custom design and the decoders APR designed are explored with a focus on design cycle time. Quality of results (QOR) is studied from power, performance, area and reliability (PPAR) perspective to ascertain the improvement over other design techniques. A radiation hardened all-digital multiplying pulsed digital delay line (DDL) is designed for double data rate (DDR2/3) applications for data eye centering during high speed off-chip data transfer. The effect of noise, radiation particle strikes and statistical variation on the designed DDL are studied in detail. The design achieves the best in class 22.4 ps peak-to-peak jitter, 100-850 MHz range at 14 pJ/cycle energy consumption. Vulnerability of the non-hardened design is characterized and portions of the redundant DDL are separated in custom and auto-place and route (APR). Thus, a range of designs for mission critical applications are implemented using methodologies proposed in this work and their potential PPAR benefits explored in detail.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

An Analog Decoder for Turbo-Structured Low-Density Parity-Check Codes

In this work, we consider a class of structured regular LDPC codes, called Turbo-Structured LDPC (TS-LDPC). TS-LDPC codes outperform random LDPC codes and have much lower error floor at high Signal-to-Noise Ratio (SNR). In this thesis, Min-Sum (MS) algorithms are adopted in the decoding of TS-LDPC codes due to their low complexity in the implementation. We show that the error performance of the MS-based TS-LDPC decoder is comparable with the Sum-Product (SP) based decoder and the error floor property of TS-LDPC codes is preserved. The TS-LDPC decoding algorithms can be performed by analog or digital circuitry. Analog decoders are preferred in many communication systems due to their potential for higher speed, lower power dissipation and smaller chip area compared to their digital counterparts. In this work, implementation of the (120, 75) MS-based TS-LDPC analog decoder is considered. The decoder chip consists of an analog decoder heart, digital input and digital output blocks. These digital blocks are required to deliver the received signal to the analog decoder heart and transfer the estimated codewords to the off-chip module. The analog decoder heart is an analog processor performing decoding on the Tanner graph of the code. Variable and check nodes are the main building blocks of analog decoder which are designed and evaluated. The check node is the most complicated unit in MS-based decoders. The minimizer circuit, the fundamental block of a check node, is designed to have a good trade-off between speed and accuracy. In addition, the structure of a high degree minimizer is proposed considering the accuracy, speed, power consumption and robustness against mismatch of the check node unit. The measurement results demonstrate that the error performance of the chip is comparable with theory. The SNR loss at Bit-Error-Rate of 10−5 is only 0.2dB compared to the theory while information throughput is 750Mb/s and the energy efficiency of the decoder chip is 17pJ/b. It is shown that the proposed decoder outperforms the analog decoders that have been fabricated to date in the sense of error performance, throughput and energy efficiency. This decoder is the first analog decoder that has ever been implemented in a sub 100-nm technology and it improves the throughput of analog decoders by a factor of 56. This decoder sets a new state-of-the-art in analog decoding

A Software-based Low-Jitter Servo Clock for Inexpensive Phasor Measurement Units

This paper presents the design and the implementation of a servo-clock (SC) for low-cost Phasor Measurement Units (PMUs). The SC relies on a classic Proportional Integral (PI) controller, which has been properly tuned to minimize the synchronization error due to the local oscillator triggering the on-board timer. The SC has been implemented into a PMU prototype developed within the OpenPMU project using a BeagleBone Black (BBB) board. The distinctive feature of the proposed solution is its ability to track an input Pulse-Per-Second (PPS) reference with good long-term stability and with no need for specific on-board synchronization circuitry. Indeed, the SC implementation relies only on one co-processor for real-time application and requires just an input PPS signal that could be distributed from a single substation clock

Learning to Decode the Surface Code with a Recurrent, Transformer-Based Neural Network

Quantum error-correction is a prerequisite for reliable quantum computation. Towards this goal, we present a recurrent, transformer-based neural network which learns to decode the surface code, the leading quantum error-correction code. Our decoder outperforms state-of-the-art algorithmic decoders on real-world data from Google's Sycamore quantum processor for distance 3 and 5 surface codes. On distances up to 11, the decoder maintains its advantage on simulated data with realistic noise including cross-talk, leakage, and analog readout signals, and sustains its accuracy far beyond the 25 cycles it was trained on. Our work illustrates the ability of machine learning to go beyond human-designed algorithms by learning from data directly, highlighting machine learning as a strong contender for decoding in quantum computers

High-speed Time-interleaved Digital-to-Analog Converter (TI-DAC) for Self-Interference Cancellation Applications

Nowadays, the need for higher data-rate is constantly growing to enhance the quality of the daily communication services. The full-duplex (FD) communication is exemplary method doubling the data-rate compared to half-duplex one. However, part of the strong output signal of the transmitter interferes to the receiver-side because they share the same antenna with limited attenuation and, as a result, the receiver’s performance is corrupted. Hence, it is critical to remove the leakage signal from the receiver’s path by designing another block called self-interference cancellation (SIC). The main goal of this dissertation is to develop the SIC block embedded in the current-mode FD receivers. To this end, the regenerated cancellation current signal is fed to the inputs of the base-band filter and after the mixer of a (direct-conversion) current-mode FD receiver. Since the pattern of the transmitter (the digital signal generated by DSP) is known, a high-speed digital-to-Analog converter (DAC) with medium-resolution can perfectly suppress main part of the leakage on the receiver path. A capacitive DAC (CDAC) is chosen among the available solutions because it is compatible with advanced CMOS technology for high-speed application and the medium-resolution designs. Although the main application of the design is to perform the cancellation, it can also be employed as a stand-alone DAC in the Analog (I/Q) transmitter. The SIC circuitry includes a trans-impedance amplifier (TIA), two DACs, high-speed digital circuits, and built-in-self-test section (BIST). According to the available specification for full-duplex communication system, the resolution and working frequency of the CDAC are calculated (designed) equal to 10-bit (3 binary+ 2 binary + 5 thermometric) and 1GHz, respectively. In order to relax the design of the TIA (settling time of the DAC), the CDAC implements using 2-way time-interleaved (TI) manner (the effective SIC frequency equals 2GHz) without using any calibration technique. The CDAC is also developed with the split-capacitor technique to lower the negative effects of the conventional binary-weighted DAC. By adding one extra capacitor on the left-side of the split-capacitor, LSB-side, the value of the split-capacitor can be chosen as an integer value of the unit capacitor. As a result, it largely enhances the linearity of the CADC and cancellation performance. If the block works as a stand-alone DAC with non-TI mode, the digital input code representing a Sinus waveform with an amplitude 1dB less than full-scale and output frequency around 10.74MHz, chosen by coherent sampling rule, then the ENOB, SINAD, SFDR, and output signal are 9.4-bit, 58.2 dB, 68.4dBc, and -9dBV. The simulated value of the |DNL| (static linearity) is also less than 0.7. The similar simulation was done in the SIC mode while the capacitive-array woks in the TI mode and cancellation current is set to the full-scale. Hence, the amount of cancelling the SI signal at the output of the TIA, SNDR, SFDR, SNDRequ. equals 51.3dB, 15.1 dB, 24dBc, 66.4 dB. The designed SIC cannot work as a closed-loop design. The layout was optimally drawn in order to minimize non-linearity, the power-consumption of the decoders, and reduce the complexity of the DAC. By distributing the thermometric cells across the array and using symmetrical switching scheme, the DAC is less subjected to the linear and gradient effect of the oxide. Based on the post-layout simulation results, the deviation of the design after drawing the layout is studied. To compare the results of the schematic and post-layout designs, the exact conditions of simulation above (schematic simulations) are used. When the block works as a stand-alone CDAC, the ENOB, SINAD, SFDR are 8.5-bit, 52.6 dB, 61.3 dBc. The simulated value of the |DNL| (static linearity) is also limited to 1.3. Likewise, the SI signal at the output of the TIA, SNDR, SFDR, SNDRequ. are equal to 44dB, 11.7 dB, 19 dBc, 55.7 dB