CMOS analog map decoder for (8,4) hamming code

Journal ArticleAbstract-Design and test results for a fully integrated translinear tail-biting MAP error-control decoder are presented. Decoder designs have been reported for various applications which make use of analog computation, mostly for Viterbi-style decoders. MAP decoders are more complex, and are necessary components of powerful iterative decoding systems such as Turbo codes. Analog circuits may require less area and power than digital implementations in high-speed iterative applications. Our (8, 4) Hamming decoder, implemented in an AMI 0.5- m process, is the first functioning CMOS analog MAP decoder. While designed to operate in subthreshold, the decoder also functions above threshold with a small performance penalty. The chip has been tested at bit rates up to 2 Mb/s, and simulations indicate a top speed of about 10 Mb/s in strong inversion. The decoder circuit size is 0.82 mm2, and typical power consumption is 1 mW at 1 Mb/s

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

Toward the implementation of analog LDPC decoders for long codewords

Error control codes are used in virtually every digital communication system. Traditionally, decoders have been implemented digitally. Analog decoders have been recently shown to have the potential to outperform digital decoders in terms of area and power/speed ratio. Analog designers have attempted to fully understand and exploit this potential for large decoders. However, large codes are generally still implemented with digital circuits. Nevertheless, in this thesis a number of aspects of analog decoder implementation are investigated with the hope of enabling the design of large analog decoders. In this thesis, we study and modify analog circuits used in a decoding algorithm known as the sum-product algorithm for implementation in a CMOS 90 nm technology. We apply a current-mode approach at the input nodes of these circuits and show through simulations that the power/speed ratio will be improved. Interested in studying the dynamics of decoders, we model an LDPC code in MATLAB's Simulink. We then apply the linearization technique on the modeled LDPC code in order to linearize the decoder about an initial state as its solution point. Challenges associated with decoder linearization are discussed. We also design and implement a chip comprised of the sum-product circuits with different configurations and sizes in order to study the effect of mismatch on the accuracy of the outputs. Unfortunately, testing of the chip fails as a result of errors in either the packaging process or fabrication

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 Novel Stochastic Decoding of LDPC Codes with Quantitative Guarantees

Low-density parity-check codes, a class of capacity-approaching linear codes, are particularly recognized for their efficient decoding scheme. The decoding scheme, known as the sum-product, is an iterative algorithm consisting of passing messages between variable and check nodes of the factor graph. The sum-product algorithm is fully parallelizable, owing to the fact that all messages can be update concurrently. However, since it requires extensive number of highly interconnected wires, the fully-parallel implementation of the sum-product on chips is exceedingly challenging. Stochastic decoding algorithms, which exchange binary messages, are of great interest for mitigating this challenge and have been the focus of extensive research over the past decade. They significantly reduce the required wiring and computational complexity of the message-passing algorithm. Even though stochastic decoders have been shown extremely effective in practice, the theoretical aspect and understanding of such algorithms remains limited at large. Our main objective in this paper is to address this issue. We first propose a novel algorithm referred to as the Markov based stochastic decoding. Then, we provide concrete quantitative guarantees on its performance for tree-structured as well as general factor graphs. More specifically, we provide upper-bounds on the first and second moments of the error, illustrating that the proposed algorithm is an asymptotically consistent estimate of the sum-product algorithm. We also validate our theoretical predictions with experimental results, showing we achieve comparable performance to other practical stochastic decoders.Comment: This paper has been submitted to IEEE Transactions on Information Theory on May 24th 201

Design techniques for low-power wide-band direct digital frequency synthesizers of spread spectrum communication applications

For frequency agile communication systems, fast frequency switching in fine frequency steps with good spectral purity is crucial. Direct Digital Frequency Synthesizer (DDFS) is best suitable for these applications, but is not widely employed in wireless communication systems due to its high power consumption. In general, low power and high integration design are two challenges for mixed signal-circuits and communication systems designers. In this dissertation, new design techniques for DDFS at both architecture and circuit levels are proposed and investigated in order to minimize power consumption and optimize performance. A ROM-less low power wide band DDFS prototype using segmented sine wave Digital-to-Analog Converter (DAC) were designed, fabricated and tested to demonstrate the new design techniques.;First, to further reduce power consumption and save chip area, two new phase interpolation ROM less DDFS architectures are proposed. Segmentation technique is applied to the design of sine wave DAC for DDFS: (1) based upon trigonometric identities, a segmented sine wave DAC with fine nonlinear interpolation DAC\u27s is proposed; (2) based upon first order Taylor series and simple linear interpolation, a segmented sine wave DAC with a fine linear interpolation DAC is proposed. Second, a figure of merit (FM) is defined to find the optimal sine wave DAC segmentations for various resolutions of the segmented sine wave DAC\u27s. The device mismatch effects on the performance of segmented sine wave were also discussed. Third, For DDFS using current-steering segmented sine wave DAC with 12-b phase resolution and 11-b amplitude resolution, a behavioral model in Verilog was used to verify the functionality and validate the architecture. Finally, a DDFS prototype was designed and fabricated in a standard 0.25mum CMOS process. The measured SFDR is better than 50 dB with output frequencies up to 3/8 of the 300 MHz clock frequency. The prototype occupies an active area of 1.4 mm2 and consumes 240 mW for 300 MHz clock frequency. The new techniques reduce the power dissipation and die area substantially when compared to conventional ROM based DDFS designs with on-chip DAC