Viterbi Decoder Research Articles

Low-power body-coupled transceiver for miniaturized body area networks

As wearable devices continue to proliferate, seamlessly integrating them into wireless body-area networks (WBANs) becomes increasingly crucial. Body-coupled communication (BCC) emerges as a promising WBAN technology, utilizing the human body itself as a transmission channel. This paper presents a novel BCC transceiver designed for efficiency and miniaturization. The proposed transceiver prioritizes reliable data transmission with a convolutional encoder. It leverages a simple direct digital synthesizer (DDS) for frequency shift keying (FSK) modulation, minimizing chip area. At the receiver, a Viterbi decoder (VD) ensures accurate data recovery. This design shines in its resource efficiency. It occupies less than 1% of an Artix-7 FPGA, operates at 268.77 MHz with a mere 111 mW power consumption, and achieves a remarkable data rate of 13.78 Mbps. This translates to a hardware efficiency of 44.46 Kbps/slice, surpassing existing transceivers. Moreover, the BCC transceiver exhibits a stellar bit error rate (BER) of over 10⁻⁷ under realistic body channel conditions. Overall, this work presents a highly efficient BCC transceiver with significant improvements in chip area, power consumption, and data rate compared to existing designs. This paves the way for practical and miniaturized WBAN solutions for future wearable applications.

Polymorphic dynamic programming by algebraic shortcut fusion

Dynamic programming (DP) is a broadly applicable algorithmic design paradigm for the efficient, exact solution of otherwise intractable, combinatorial problems. However, the design of such algorithms is often presented informally in an ad-hoc manner. It is sometimes difficult to justify the correctness of these DP algorithms. To address this issue, this paper presents a rigorous algebraic formalism for systematically deriving DP algorithms, based on semiring polymorphism. We start with a specification, construct a (brute-force) algorithm to compute the required solution which is self-evidently correct because it exhaustively generates and evaluates all possible solutions meeting the specification. We then derive, primarily through the use of shortcut fusion, an implementation of this algorithm which is both efficient and correct. We also demonstrate how, with the use of semiring lifting, the specification can be augmented with combinatorial constraints and through semiring lifting, show how these constraints can also be fused with the derived algorithm. This paper furthermore demonstrates how existing DP algorithms for a given combinatorial problem can be abstracted from their original context and re-purposed to solve other combinatorial problems. This approach can be applied to the full scope of combinatorial problems expressible in terms of semirings. This includes, for example: optimization, optimal probability and Viterbi decoding, probabilistic marginalization, logical inference, fuzzy sets, differentiable softmax, and relational and provenance queries. The approach, building on many ideas from the existing literature on constructive algorithmics, exploits generic properties of (semiring) polymorphic functions, tupling and formal sums (lifting), and algebraic simplifications arising from constraint algebras. We demonstrate the effectiveness of this formalism for some example applications arising in signal processing, bioinformatics and reliability engineering. Python software implementing these algorithms can be downloaded from: http://www.maxlittle.net/software/dppolyalg.zip.

An approach to ensure joint illumination & communication performance of a forward error corrected indoor visible light communication (VLC) system in presence of ambient light interference

Abstract In recent time of looming radio frequency (RF) spectrum crisis, visible light communication using lighting infrastructure emerged as a potential alternative at an indoor environment. This paper addresses the setback associated with ambient light interference in an indoor Visible Light Communication (VLC) system to ensure joint communication and illumination performance inside an office room. A novel VLC architecture with suitable white light emitting diode (WLED) luminaire arrangement is presented to minimize the dispersion of signal to interference plus noise ratio (SINR) across the room. Luminaires are categorized in two groups viz. data transmitting illuminants and illuminants for lighting purpose. The first group is dedicated to transmit data as well as serves the purpose of illumination. The other set creates only ambient illumination to achieve quality lighting attributes. The proposed forward error corrected receiver configuration discards the ambient light noise originated by the illuminants that serve the ambient illumination. Tail biting convolutional encoder and viterbi decoder are used at the encoding section of the transmitter and decoding section of the receiver respectively to improve bit error rate. Results obtained through MATLAB simulation shows better average bit error rate (BER) in the order of 10−8 measured at uniformly distributed 25 grid points over the working plane. At the same time achieved average horizontal illuminance with good uniformity comply with ISO recommendation.

Robust Delimitation of Aggregated Packets Based on Viterbi Decoding With Natural Redundancy in Protocols

Robust Delimitation of Aggregated Packets Based on Viterbi Decoding With Natural Redundancy in Protocols

Error resilient wireless video transmission via parallel processing using puncturing rule enabled coding and decoding

The innovation in wireless video transmission lies in the methodology's holistic approach, which combines parallel processing, puncturing rule-enabled coding, comprehensive error correction, and focused video frame reconstruction. The methodology includes several stages, including video frame processing, channel coding, error simulation, and Viterbi decoding, all of which are optimized for improved performance. Parallel processing is used at each stage to improve computational efficiency. Convolutional encoding is used concurrently, with a puncturing rule to tailor the encoding process for individual packets. Following that, a binary symmetric channel model is used to simulate bit errors, allowing the system's error-resilient characteristics to be evaluated. Beyond the analysis performed on previously studied videos, the proposed approach is thoroughly evaluated across three distinct video datasets. Furthermore, the study delves into BER analysis, encompassing various error probabilities and employing incremental redundancy. This investigation sheds light on the system's robustness in correcting errors in a variety of error scenarios. Throughput measurements provide important information about the achieved data transmission rate during successful receptions, whereas the elapsed time metric measures the overall efficiency of the transmission process. Furthermore, the proposed method assesses Mean Squared Error (MSE) at 0.48 and Peak Signal-to-Noise Ratio (PSNR) at 51.30 dB across the entire operational process. The combined findings highlight the proposed approach's superiority, positioning it as a promising solution for robust and efficient wireless video communication. This results in a more stable and efficient gearbox system, distinguishing it from existing system.

Error performance analysis of forward error correction using convolutional encoding in the presence of (1/f) noise

Any communication scheme's principal goal is providing error-free data transmission. By increasing the rate at which data could be transmitted through a channel and maintaining a given error rate, this coding is advantageous. The message bits to be transmitted will gradually receive more bits thanks to the convolution (channel) encoder. At the receiver end of the channel, a Viterbi decoder is utilized in order to extract original message sequence from the received data. Widely utilized error correction approaches in communication systems for the enhancement of bit error rate (BER) performance are Viterbi decoding and convolutional encoding. The Viterbi decoder and convolution encoder rate for constraints with lengths of 2 and 6 and bit rates of 1⁄2 and 1⁄3 are shown in this study in the presence of (1/f) noise. The performance regarding the convolutional encoding/hard decision Viterbi decoding forward error correction (FEC) method affects the simulation outcomes. The findings demonstrate that the BER as function of signal to noise ratio (SNR) acquired for uncoded binary phase shift keying (BPSK) with the existence of additive white Gaussian noise (AWGN) is inferior to that acquired with the use of a hard decision Viterbi decoder.

Trellis-Coded Modulation-Enabled Probabilistic Shaping With Simplified Viterbi Decoder for Bandwidth-Limited IMDD Systems

Trellis-Coded Modulation-Enabled Probabilistic Shaping With Simplified Viterbi Decoder for Bandwidth-Limited IMDD Systems

Тізбекті кодтардың көп шекті декодтау параметрлерін оңтайландыру алгоритмін әзірлеу

The most known and practically used coding/decoding schemes are investigated. The results of the analysis of algorithmic complexity and simulation of the operation of coding schemes for Gaussian channels show that only multi-threshold decoders of convolutional codes outperform all others for all considered block sizes and coding rates. The multithreshold decoder (MTD) is a development of the simplest Messian threshold decoder with an additional difference register added. This decoder allows decoding block and convolutional self-orthogonal codes. The operating principles of convolutional encoders are considered in detail, the characteristics of multithreshold decoders and the Viterbi decoder for convolutional codes are compared. The best self-orthogonal codes for MTD are chosen, the efficiency of MTD in channels with additive white Gaussian noise is studied. An algorithm for increasing the performance of multithreshold decoding (MTD) based on the optimization of the MTD parameters of symbolic self-orthogonal codes is proposed.

Vector Coding Optical Wireless Links

The quasi-static nature of the optical wireless channel means that the channel state information (CSI) can be readily available at the transmitter and receiver prior to data transmission. This implies that electrically band-limited optical wireless communication (OWC) systems can make use of optimal channel partitioning or vector coding based multi-channel modulation (MCM) to achieve high throughput by mitigating the non-linearities arising from the optical and electrical channel. This paper proposes a pulse amplitude modulation (PAM) based DC-biased optical vector coding (DCO-VC) MCM scheme for OWC. The throughput performance of DCO-VC is evaluated and compared to the well known DC-biased optical orthogonal frequency division multiplexing (DCO-OFDM) over hybrid (line-of-sight and diffuse) and diffuse (non line-of-sight only) visible light communication (VLC) channels with additive white Gaussian noise. For the completeness of the VLC physical layer, the performance comparison is based on an uncoded and a forward error correction transmission mode using well-known convolutional codes with Viterbi decoder. The results show that the coded DCO-VC outperforms DCO-OFDM system by achieving up to 2 and 3 dB signal to noise ratio gains over hybrid and diffuse VLC channels, respectively.

Soft-decision detection for phase/frequency modulation with symbol-wise Viterbi decoding

Soft-decision detection for phase/frequency modulation with symbol-wise Viterbi decoding

KNN-Based ML Model for the Symbol Prediction in TCM Trellis Coded Modulation TCM Decoder

Machine Learning is a booming technology today. In a machine learning set of training, data is to be provided to the model for training and that model predicts the output. Machine Learning models are trained using a computer program known as ML algorithms.The new machine learning-based Transition Metric Unit (TMU) of 4D- 8PSK Trellis coded Modulation TCM Decoder is presented in this work. The classic Viterbi decoder's branch metric unit, or TMU, takes on a complex structure. Trellis coded Modulation (TCM) is a combination of 8 PSK modulations and Error Correcting Code (ECC). TMU is one of the complex units of the TCM decoder, which is essentially a Viterbi decoder. Similar to how the first Branch metric is determined in the straightforward Viterbi decoder, the TCM decoder performs this BM computation via the TMU unit. The TMU becomes challenging and uses more dynamic power as a result of the enormous constraint length and the vast number of encoder states.In the proposed algorithm innovative KNN (K nearest neighbours) based ML model is developed. It is a supervised learning model in which input and output both are provided to the model, training data also called the labels, when a new set of data will come the model will give output based on its previous set experience and data.Here we are using this ML model for the symbol prediction at the receiver end of the TCM decoder based on the previous learning. Using the proposed innovation, the paper perceives the optimization of the TCM Decoder which will further reduce the H/W requirements and low latency which results in less power consumption.

Efficient signal transmission algorithms for remote sensing gamma radiation over developed mobil WiMax network

SummaryThis paper overcomes two key issues within radiation monitoring networks. Secure and accurate transmission of detected gamma radiation in remote areas is the first challenge. The second one is related to the robustness of transmitted signal under different fading scenarios. These issues are handled during signal transmission over worldwide interoperability for microwave access (WiMax) networks. The signals are experimentally captured using a 137Cs point source, a NaI (TI) detector, and an analog‐to‐digital converter with 16 MS/s. For the first issue, several algorithms are implemented for secure and efficient transmission of gamma‐based signals. These algorithms include encoding of captured signal, decoding, interleaving, and frequency transformation of modulated signal. Encoding and decoding of target signals are conducted using the Reed Solomon technique and convolutional encoding with a Viterbi decoder. A superior algorithm for channel interleaver using the combinational interleaving method is introduced. Fast lifting transform (FLT) is applied for transforming modulated signal into frequency domain. The results declare that CC = 1/2 with BPSK‐1/2 coding rate introduces a better BER of 0.00068. A higher SNR of 1.5 dB is accomplished by the combinational interleaving algorithm. For the second issue, several models are suggested for overcoming channel degradations under gamma, exponential, Poisson, and geometric fading. Closed‐form expressions that describe outage probability, bit error rate (BER), and symbol error rate (SER) are suggested. Geometric and gamma fading achieve respectively a lower BER of 0.18 and 0.48. These channels demonstrate similar channel performances at 3.6 dB. The proposed models are validated through comparison with published work. Finally, the proposed algorithms enable higher data rate transmission of detected 137Cs signals under higher robustness using WiMax networks.

An efficient ultra-wideband digital transceiver for wireless applications on the field-programmable gate array platform

<p>The ultra-wideband (UWB) technology is a promising short-range communication technology for most wireless applications. The UWB works at higher frequencies and is affected by interferences with the same frequency standards. This manuscript has designed an efficient and low-cost implementation of IEEE 802.15.4a-based UWB-digital transceiver (DTR). The design module contains UWB transmitter (TX), channel, and UWB-receiver (RX) units. Convolutional encoding and modulation units like burst position modulation and binary phase-shift keying modulation are used to construct the UWB-TX. The synchronization and Viterbi decoder units are used to recover the original data bits and are affected by noise in UWB-RX. The UWB-DTR is synthesized using Xilinx ISE<sup>®</sup> environment with Verilog hardware description language (HDL) and implemented on Artix-7 field-programmable gate array (FPGA). The UWB-DTR utilizes less than 2% (slices and look-up table/LUTs), operates at 268 MHz, and consumes 91 mW of total power on FPGA. The transceiver achieves a 6.86 Mbps data rate, which meets the IEEE 802.15.4a standard. The UWB-DTR module obtains the bit error rate (BER) of 2×10<sup>-4</sup> by transmitting 105 data bits. The UWB-DTR module is compared with similar physical layer (PHY) transceivers with improvements in chip area (slices), power, data rate, and BER. </p>

Recurrent Neural Network Based Joint Equalization and Decoding Method for Trellis Coded Modulated Optical Communication System

In this paper, a joint equalization and decoding method based on recurrent neural networks (RNNs) is proposed for trellis coded modulation (TCM) systems. For traditional methods based on concatenated equalizers and Viterbi decoder, the information may be lost between the equalization and decoding. However, our proposed joint method can obtain the information bits directly from the received symbols and the error also can be corrected in iterations. In two-dimensional eight-level pulse amplitude modulation (2D-PAM8) links, we experimentally demonstrate that, compared with the traditional method based on Volterra filter and Viterbi decoder, the proposed joint method based on RNNs with similar complexity can achieve bit-error rate (BER) performance improvements of 1 dB, 1 dB, and 2 dB in 87.5 Gb/s, 100 Gb/s, and 112.5 Gb/s transmissions at 7% hard-decision forward-error-correction (HD-FEC) limit, respectively. For the 10 km standard single-mode fiber (SSMF) link at 87.5 Gb/s, the traditional method cannot get the BER below the 7% HD-FEC limit whereas the joint RNNs method with similar complexity can get the BER below the 7% HD-FEC limit. As the nonlinearity increases, the proposed joint method can achieve greater improvement of BER performance.

Hybrid HMM Decoder for Convolutional Codes by Joint Trellis-Like Structure and Channel Prior

The anti-interference capability of wireless links is a physical layer problem for edge computing. Although convolutional codes have inherent error correction potential due to the redundancy introduced in the data, the performance of the convolutional code is drastically degraded due to multipath effects on the channel. In this paper, we propose the use of a Hidden Markov Model (HMM) for the reconstruction of convolutional codes and decoding by the Viterbi algorithm. Furthermore, to implement soft-decision decoding, the observation of HMM is replaced by Gaussian mixture models (GMM). Our method provides superior error correction potential than the standard method because the model parameters contain channel state information (CSI). We evaluated the performance of the method compared to standard Viterbi decoding by numerical simulation. In the multipath channel, the hybrid HMM decoder can achieve a performance gain of 4.7 dB and 2 dB when using hard-decision and soft-decision decoding, respectively. The HMM decoder also achieves significant performance gains for the RSC code, suggesting that the method could be extended to turbo codes.

Mobility Enhancement for IEEE 802.15.4 SUN-OFDM Using Channel Estimation and Viterbi Decoder With Likelihood Ratio Adjustment Methods

Mobility Enhancement for IEEE 802.15.4 SUN-OFDM Using Channel Estimation and Viterbi Decoder With Likelihood Ratio Adjustment Methods

Low Complexity Signal Detection for Massive MIMO in B5G Uplink System

Massive Multiple Input Multiple Output (M-MIMO) is realized as a mandatory technique for Beyond Fifth Generation (B5G) wireless networks. In next-generation node B (gNB) uplink transmission, M-MIMO requires a low-complexity signal detection scheme with an increased number of antennas to attain high channel capacity and reliability. To attain close-optimal performance in these B5G systems, the Minimum Mean Square Error (MMSE) detection scheme is preferred at the gNB but it demands a complex matrix inversion concerning the number of users. Hence, this article proposes a Modified Weighted Two Stage (MWTS) iterative algorithm with an appropriate initial solution to realize MMSE detection at reduced complexity. MWTS detection algorithm is formulated by integrating the first half iteration phase of weighted two stage with the previous phase and ignoring the second half iteration. Further to improve the performance of the B5G system, a low-complexity soft decision Viterbi decoder is introduced at gNB. With K users, the proposed modifications display a reduction in computational complexity of 4K <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> +16K as compared to the weighted two stage algorithm of 7K <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> +8K. Simulation results confirm that the proposed MWTS algorithm yields lower complexity and near-optimal performance close to MMSE detection.

A New Viterbi-Based Decoding Strategy for Market Risk Tracking: an Application to the Tunisian Foreign Debt Portfolio During 2010–2012

In this paper, a novel market risk tracking and prediction strategy is introduced. Our approach takes volatility clustering into account and allows for the possibility of regime shifts in the intra-portfolio's latent correlation structure. The proposed specification combines hidden Markov models (HMM) with latent factor models that takes into account the presence of both the conditional skewness and leverage effects in stock returns. A computationally efficient expectation-maximization (EM) algorithm based on the Viterbi decoder is developed to estimate the model parameters. Using daily exchange rate data of the Tunisian dinar versus the currencies of the main Tunisian government's creditors, during the 2011 revolution period, the model parameters are estimated. Then, the suitable model is used in conjunction with a Monte Carlo simulation strategy to predict the Value-at-Risk (VaR) of the Tunisian government's foreign debt portfolio. The backtesting results indicate that the new approach appears to give a good fit to the data and can improve the VaR predictions, particularly during financial instability periods.

Design and Implementation of a 6.5-Gb/s Multiradix Simplified Viterbi-Sphere Decoder for Trellis-Coded Generalized Spatial Modulation With Spatial Multiplexing

A simplified Viterbi-sphere decoder (VSD) for trellis-coded generalized spatial modulation (GSM) with spatial multiplexing (TCGSMX) is designed and implemented to exploit the soft information for achieving better performance. Multiple code rates are supported to combat different levels of spatial correlations in fading channels and to offer options for various transmission efficiencies. Hence, the proposed multiradix simplified VSD is configurable to process four radix-2 stages for 1/2 code rate, two radix-4 stages for 2/3 code rate, and one radix-8 stage for 3/4 code rate in one clock cycle to upgrade the throughput by fully pipelined architecture. To reduce the complexity, several techniques are employed, including the efficient settings of survival nodes of sphere decoding and sequence length for backtracing by Viterbi decoding. The chip has been fabricated in TSMC 40-nm CMOS technology. Compared to related works, the implementation provides higher throughput up to 6.5 Gb/s at 1.1-V supply voltage as well as 180.8-MHz operating frequency and consumes 374.3 mW for TCGSMX systems using 16-QAM and code rate of 1/2.

Low Power Trellis Coded Modulation (TCM) Decoder by Using Modified Resource Sharing Method for IoT Enabler

This paper proposes a new pre-computation approach based on the auxiliary trellis of the TCM decoder's ACSU (add compare select unit). The suggested method is based on pre-computation of path metrics and resource sharing of the ACSU unit. The Viterbi decoder itself is a power-consuming module of the communication system that comprises the TMU (transition metric unit) and ACSU (add compare select unit). By applying the suggested method, the authors would be able to achieve low dynamic power. The TCM decoder designed accordingly shows better SER/ BER results in comparison to the existing techniques. The 4D 8 PSK TCM encoder and decoder were implemented as per the design specifications given by consultative committee for space data system (CCSDS) for satellite applications. The simulations results are observed on 100 Mbps data for 8PSK modulation and the ¾ code rate of the TCM encoder. The results based on the new method show improved power-speed ratio with improved SER and BER.