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Alexios Balatsoukas-Stimming

Publications and source records attributed to Alexios Balatsoukas-Stimming.

71 records · Page 4Linked to original sources

PolarBear: A 28-nm FD-SOI ASIC for Decoding of Polar Codes

Polar codes are a recently proposed class of block codes that provably achieve the capacity of various communication channels. They received a lot of attention as they can do so with low-complexity encoding and decoding algorithms, and they have an explicit construction. Their recent inclusion in a 5G communication standard will only spur more research. However, only a couple of ASICs featuring decoders for polar codes were fabricated, and none of them implements a list-based decoding algorithm. In this paper, we present ASIC measurement results for a fabricated 28 nm CMOS chip that implements two different decoders: the first decoder is tailored toward error-correction performance and flexibility. It supports any code rate as well as three different decoding algorithms: successive cancellation (SC), SC flip and SC list (SCL). The flexible decoder can also decode both non-systematic and systematic polar codes. The second decoder targets speed and energy efficiency. We present measurement results for the first silicon-proven SCL decoder, where its coded throughput is shown to be of 306.8 Mbps with a latency of 3.34 us and an energy per bit of 418.3 pJ/bit at a clock frequency of 721 MHz for a supply of 1.3 V. The energy per bit drops down to 178.1 pJ/bit with a more modest clock frequency of 308 MHz, lower throughput of 130.9 Mbps and a reduced supply voltage of 0.9 V. For the other two operating modes, the energy per bit is shown to be of approximately 95 pJ/bit. The less flexible high-throughput unrolled decoder can achieve a coded throughput of 9.2 Gbps and a latency of 628 ns for a measured energy per bit of 1.15 pJ/bit at 451 MHz.

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Blind Detection of Polar Codes

Polar codes were recently chosen to protect the control channel information in the next-generation mobile communication standard (5G) defined by the 3GPP. As a result, receivers will have to implement blind detection of polar coded frames in order to keep complexity, latency, and power consumption tractable. As a newly proposed class of block codes, the problem of polar-code blind detection has received very little attention. In this work, we propose a low-complexity blind-detection algorithm for polar-encoded frames. We base this algorithm on a novel detection metric with update rules that leverage the a priori knowledge of the frozen-bit locations, exploiting the inherent structures that these locations impose on a polar-encoded block of data. We show that the proposed detection metric allows to clearly distinguish polar-encoded frames from other types of data by considering the cumulative distribution functions of the detection metric, and the receiver operating characteristic. The presented results are tailored to the 5G standardization effort discussions, i.e., we consider a short low-rate polar code concatenated with a CRC.

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Comparison of Polar Decoders with Existing Low-Density Parity-Check and Turbo Decoders

Polar codes are a recently proposed family of provably capacity-achieving error-correction codes that received a lot of attention. While their theoretical properties render them interesting, their practicality compared to other types of codes has not been thoroughly studied. Towards this end, in this paper, we perform a comparison of polar decoders against LDPC and Turbo decoders that are used in existing communications standards. More specifically, we compare both the error-correction performance and the hardware efficiency of the corresponding hardware implementations. This comparison enables us to identify applications where polar codes are superior to existing error-correction coding solutions as well as to determine the most promising research direction in terms of the hardware implementation of polar decoders.

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A Multi-Gbps Unrolled Hardware List Decoder for a Systematic Polar Code

Polar codes are a new class of block codes with an explicit construction that provably achieve the capacity of various communications channels, even with the low-complexity successive-cancellation (SC) decoding algorithm. Yet, the more complex successive-cancellation list (SCL) decoding algorithm is gathering more attention lately as it significantly improves the error-correction performance of short- to moderate-length polar codes, especially when they are concatenated with a cyclic redundancy check code. However, as SCL decoding explores several decoding paths, existing hardware implementations tend to be significantly slower than SC-based decoders. In this paper, we show how the unrolling technique, which has already been used in the context of SC decoding, can be adapted to SCL decoding yielding a multi-Gbps SCL-based polar decoder with an error-correction performance that is competitive when compared to an LDPC code of similar length and rate. Post-place-and-route ASIC results for 28 nm CMOS are provided showing that this decoder can sustain a throughput greater than 10 Gbps at 468 MHz with an energy efficiency of 7.25 pJ/bit.

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Sliding Window Spectrum Sensing for Full-Duplex Cognitive Radios with Low Access-Latency

In a cognitive radio system the failure of secondary user (SU) transceivers to promptly vacate the channel can introduce significant access-latency for primary or high-priority users (PU). In conventional cognitive radio systems, the backoff latency is exacerbated by frame structures that only allow sensing at periodic intervals. Concurrent transmission and sensing using self-interference suppression has been suggested to improve the performance of cognitive radio systems, allowing decisions to be taken at multiple points within the frame. In this paper, we extend this approach by proposing a sliding-window full-duplex model allowing decisions to be taken on a sample-by-sample basis. We also derive the access-latency for both the existing and the proposed schemes. Our results show that the access-latency of the sliding scheme is decreased by a factor of 2.6 compared to the existing slotted full-duplex scheme and by a factor of approximately 16 compared to a half-duplex cognitive radio system. Moreover, the proposed scheme is significantly more resilient to the destructive effects of residual self-interference compared to previous approaches.

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Hardware Decoders for Polar Codes: An Overview

Polar codes are an exciting new class of error correcting codes that achieve the symmetric capacity of memoryless channels. Many decoding algorithms were developed and implemented, addressing various application requirements: from error-correction performance rivaling that of LDPC codes to very high throughput or low-complexity decoders. In this work, we review the state of the art in polar decoders implementing the successive-cancellation, belief propagation, and list decoding algorithms, illustrating their advantages.

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Fast Low-Complexity Decoders for Low-Rate Polar Codes

Polar codes are capacity-achieving error-correcting codes with an explicit construction that can be decoded with low-complexity algorithms. In this work, we show how the state-of-the-art low-complexity decoding algorithm can be improved to better accommodate low-rate codes. More constituent codes are recognized in the updated algorithm and dedicated hardware is added to efficiently decode these new constituent codes. We also alter the polar code construction to further decrease the latency and increase the throughput with little to no noticeable effect on error-correction performance. Rate-flexible decoders for polar codes of length 1024 and 2048 are implemented on FPGA. Over the previous work, they are shown to have from 22% to 28% lower latency and 26% to 34% greater throughput when decoding low-rate codes. On 65 nm ASIC CMOS technology, the proposed decoder for a (1024, 512) polar code is shown to compare favorably against the state-of-the-art ASIC decoders. With a clock frequency of 400 MHz and a supply voltage of 0.8 V, it has a latency of 0.41 $μ$s and an area efficiency of 1.8 Gbps/mm$^2$ for an energy efficiency of 77 pJ/info. bit. At 600 MHz with a supply of 1 V, the latency is reduced to 0.27 $μ$s and the area efficiency increased to 2.7 Gbps/mm$^2$ at 115 pJ/info. bit.

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Partitioned Successive-Cancellation List Decoding of Polar Codes

Successive-cancellation list (SCL) decoding is an algorithm that provides very good error-correction performance for polar codes. However, its hardware implementation requires a large amount of memory, mainly to store intermediate results. In this paper, a partitioned SCL algorithm is proposed to reduce the large memory requirements of the conventional SCL algorithm. The decoder tree is broken into partitions that are decoded separately. We show that with careful selection of list sizes and number of partitions, the proposed algorithm can outperform conventional SCL while requiring less memory.

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Quantized Message Passing for LDPC Codes

We propose a quantized decoding algorithm for low- density parity-check codes where the variable node update rule of the standard min-sum algorithm is replaced with a look-up table (LUT) that is designed using an information-theoretic criterion. We show that even with message resolutions as low as 3 bits, the proposed algorithm can achieve better error rates than a floating-point min-sum decoder. Moreover, we study in detail the effect of different decoder design parameters, like the design SNR and the LUT tree structure on the performance of our decoder, and we propose some complexity reduction techniques, such as LUT re-use and message alphabet downsizing.

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A Fully-Unrolled LDPC Decoder Based on Quantized Message Passing

In this paper, we propose a finite alphabet message passing algorithm for LDPC codes that replaces the standard min-sum variable node update rule by a mapping based on generic look-up tables. This mapping is designed in a way that maximizes the mutual information between the decoder messages and the codeword bits. We show that our decoder can deliver the same error rate performance as the conventional decoder with a much smaller message bit-width. Finally, we use the proposed algorithm to design a fully unrolled LDPC decoder hardware architecture.

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LLR-based Successive Cancellation List Decoding of Polar Codes

We show that successive cancellation list decoding can be formulated exclusively using log-likelihood ratios. In addition to numerical stability, the log-likelihood ratio based formulation has useful properties which simplify the sorting step involved in successive cancellation list decoding. We propose a hardware architecture of the successive cancellation list decoder in the log-likelihood ratio domain which, compared to a log-likelihood domain implementation, requires less irregular and smaller memories. This simplification together with the gains in the metric sorter, lead to $56\%$ to $137\%$ higher throughput per unit area than other recently proposed architectures. We then evaluate the empirical performance of the CRC-aided successive cancellation list decoder at different list sizes using different CRCs and conclude that it is important to adapt the CRC length to the list size in order to achieve the best error-rate performance of concatenated polar codes. Finally, we synthesize conventional successive cancellation decoders at large block-lengths with the same block-error probability as our proposed CRC-aided successive cancellation list decoders to demonstrate that, while our decoders have slightly lower throughput and larger area, they have a significantly smaller decoding latency.

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Faulty Successive Cancellation Decoding of Polar Codes for the Binary Erasure Channel

We study faulty successive cancellation decoding of polar codes for the binary erasure channel. To this end, we introduce a simple erasure-based fault model and we show that, under this model, polarization does not happen, meaning that fully reliable communication is not possible at any rate. Moreover, we provide numerical results for the frame erasure rate and bit erasure rate and we study an unequal error protection scheme that can significantly improve the performance of the faulty successive cancellation decoder with negligible overhead.

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On Metric Sorting for Successive Cancellation List Decoding of Polar Codes

We focus on the metric sorter unit of successive cancellation list decoders for polar codes, which lies on the critical path in all current hardware implementations of the decoder. We review existing metric sorter architectures and we propose two new architectures that exploit the structure of the path metrics in a log-likelihood ratio based formulation of successive cancellation list decoding. Our synthesis results show that, for the list size of $L=32$, our first proposed sorter is $14\%$ faster and $45\%$ smaller than existing sorters, while for smaller list sizes, our second sorter has a higher delay in return for up to $36\%$ reduction in the area.

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A Low-Complexity Improved Successive Cancellation Decoder for Polar Codes

Under successive cancellation (SC) decoding, polar codes are inferior to other codes of similar blocklength in terms of frame error rate. While more sophisticated decoding algorithms such as list- or stack-decoding partially mitigate this performance loss, they suffer from an increase in complexity. In this paper, we describe a new flavor of the SC decoder, called the SC flip decoder. Our algorithm preserves the low memory requirements of the basic SC decoder and adjusts the required decoding effort to the signal quality. In the waterfall region, its average computational complexity is almost as low as that of the SC decoder.

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Baseband and RF Hardware Impairments in Full-Duplex Wireless Systems: Experimental Characterisation and Suppression

Hardware imperfections can significantly reduce the performance of full-duplex wireless systems by introducing non-idealities and random effects that make it challenging to fully suppress self-interference. Previous research has mostly focused on analyzing the impact of hardware imperfections on full-duplex systems, based on simulations and theoretical models. In this paper, we follow a measurement-based approach to experimentally identify and isolate these hardware imperfections leading to residual self-interference in full-duplex nodes. Our measurements show the important role of images arising from in-phase and quadrature (IQ) imbalance in the mixers. We also observe base-band non-linearities in the digital-to-analog converters (DAC), which can introduce strong harmonic components that have not been previously considered. A corresponding general mathematical model to suppress these components of the self-interference signal arising from the hardware non-idealities is developed from the observations and measurements. Results from a 10 MHz bandwidth full-duplex OFDM system, operating at 2.48 GHz, show up to 13 dB additional suppression, relative to state-of-the-art implementations can be achieved by jointly compensating for IQ imbalance and DAC non-linearities.

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Enabling Complexity-Performance Trade-Offs for Successive Cancellation Decoding of Polar Codes

Polar codes are one of the most recent advancements in coding theory and they have attracted significant interest. While they are provably capacity achieving over various channels, they have seen limited practical applications. Unfortunately, the successive nature of successive cancellation based decoders hinders fine-grained adaptation of the decoding complexity to design constraints and operating conditions. In this paper, we propose a systematic method for enabling complexity-performance trade-offs by constructing polar codes based on an optimization problem which minimizes the complexity under a suitably defined mutual information based performance constraint. Moreover, a low-complexity greedy algorithm is proposed in order to solve the optimization problem efficiently for very large code lengths.

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Density Evolution for Min-Sum Decoding of LDPC Codes Under Unreliable Message Storage

We analyze the performance of quantized min-sum decoding of low-density parity-check codes under unreliable message storage. To this end, we introduce a simple bit-level error model and show that decoder symmetry is preserved under this model. Subsequently, we formulate the corresponding density evolution equations to predict the average bit error probability in the limit of infinite blocklength. We present numerical threshold results and we show that using more quantization bits is not always beneficial in the context of faulty decoders.

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