26 research outputs found

    Performance Prediction of Nonbinary Forward Error Correction in Optical Transmission Experiments

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    In this paper, we compare different metrics to predict the error rate of optical systems based on nonbinary forward error correction (FEC). It is shown that the correct metric to predict the performance of coded modulation based on nonbinary FEC is the mutual information. The accuracy of the prediction is verified in a detailed example with multiple constellation formats, FEC overheads in both simulations and optical transmission experiments over a recirculating loop. It is shown that the employed FEC codes must be universal if performance prediction based on thresholds is used. A tutorial introduction into the computation of the threshold from optical transmission measurements is also given.Comment: submitted to IEEE/OSA Journal of Lightwave Technolog

    Low-Density Parity-Check Coded High-order Modulation Schemes

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    In this thesis, we investigate how to support reliable data transmissions at high speeds in future communication systems, such as 5G/6G, WiFi, satellite, and optical communications. One of the most fundamental problems in these communication systems is how to reliably transmit information with a limited number of resources, such as power and spectral. To obtain high spectral efficiency, we use coded modulation (CM), such as bit-interleaved coded modulation (BICM) and delayed BICM (DBICM). To be specific, BICM is a pragmatic implementation of CM which has been largely adopted in both industry and academia. While BICM approaches CM capacity at high rates, the capacity gap between BICM and CM is still noticeable at lower code rates. To tackle this problem, DBICM, as a variation of BICM, introduces a delay module to create a dependency between multiple codewords, which enables us to exploit extrinsic information from the decoded delayed sub-blocks to improve the detection of the undelayed sub-blocks. Recent work shows that DBICM improves capacity over BICM. In addition, BICM and DBICM schemes protect each bit-channel differently, which is often referred to as the unequal error protection (UEP) property. Therefore, bit mapping designs are important for constructing pragmatic BICM and DBICM. To provide reliable communication, we have jointly designed bit mappings in DBICM and irregular low-density parity-check (LDPC) codes. For practical considerations, spatially coupled LDPC (SC-LDPC) codes have been considered as well. Specifically, we have investigated the joint design of the multi-chain SC-LDPC and the BICM bit mapper. In addition, the design of SC-LDPC codes with improved decoding threshold performance and reduced rate loss has been investigated in this thesis as well. The main body of this thesis consists of three parts. In the first part, considering Gray-labeled square M-ary quadrature amplitude modulation (QAM) constellations, we investigate the optimal delay scheme with the largest spectrum efficiency of DBICM for a fixed maximum number of delayed time slots and a given signal-to-noise ratio. Furthermore, we jointly optimize degree distributions and channel assignments of LDPC codes using protograph-based extrinsic information transfer charts. In addition, we proposed a constrained progressive edge growth-like algorithm to jointly construct LDPC codes and bit mappings for DBICM, taking the capacity of each bit-channel into account. Simulation results demonstrate that the designed LDPC-coded DBICM systems significantly outperform LDPC-coded BICM systems. In the second part, we proposed a windowed decoding algorithm for DBICM, which uses the extrinsic information of both the decoded delayed and undelayed sub-blocks, to improve the detection for all sub-blocks. We show that the proposed windowed decoding significantly outperforms the original decoding, demonstrating the effectiveness of the proposed decoding algorithm. In the third part, we apply multi-chain SC-LDPC to BICM. We investigate various connections for multi-chain SC-LDPC codes and bit mapping designs and analyze the performance of the multi-chain SC-LDPC codes over the equivalent binary erasure channels via density evolution. Numerical results demonstrate the superiority of the proposed design over existing connected-chain ensembles and over single-chain ensembles with the existing bit mapping design

    Optimization of bit interleaved coded modulation using genetic algorithms

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    Modern wireless communication systems must be optimized with respect to both bandwidth efficiency and energy efficiency. A common approach to achieve these goals is to use multi-level modulation such as quadrature-amplitude modulation (QAM) for bandwidth efficiency and an error-control code for energy efficiency. In benign additive white Gaussian noise (AWGN) channels, Ungerboeck proposed trellis-coded modulation (TCM), which combines modulation and coding into a joint operation. However, in fading channels, it is important to maximize diversity. As shown by Zehavi, diversity is maximized by performing coding and modulation separately and interleaving bits that are passed from the encoder to the modulator. Such systems are termed BICM for bit-interleaved coded modulation. Later, Li and Ritcey proposed a method for improving the performance of BICM systems by iteratively passing information between the demodulator and decoder. Such systems are termed BICM-ID , for BICM with Iterative Decoding. The bit error rate (BER) curve of a typical BICM-ID system is characterized by a steeply sloping waterfall region followed by an error floor with a gradual slope.;This thesis is focused on optimizing BICM-ID systems in the error floor region. The problem of minimizing the error bound is formulated as an instance of the Quadratic Assignment Problem (QAP) and solved using a genetic algorithm. First, an optimization is performed by fixing the modulation and varying the bit-to-symbol mapping. This approach provides the lowest possible error floor for a BICM-ID system using standard QAM and phase-shift keying (PSK) modulations. Next, the optimization is performed by varying not only the bit-to-symbol mapping, but also the location of the signal points within the two-dimensional constellation. This provides an error floor that is lower than that achieved with the best QAM and PSK systems, although at the cost of a delayed waterfall region

    Advanced constellation and demapper schemes for next generation digital terrestrial television broadcasting systems

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    206 p.Esta tesis presenta un nuevo tipo de constelaciones llamadas no uniformes. Estos esquemas presentan una eficacia de hasta 1,8 dB superior a las utilizadas en los últimos sistemas de comunicaciones de televisión digital terrestre y son extrapolables a cualquier otro sistema de comunicaciones (satélite, móvil, cable¿). Además, este trabajo contribuye al diseño de constelaciones con una nueva metodología que reduce el tiempo de optimización de días/horas (metodologías actuales) a horas/minutos con la misma eficiencia. Todas las constelaciones diseñadas se testean bajo una plataforma creada en esta tesis que simula el estándar de radiodifusión terrestre más avanzado hasta la fecha (ATSC 3.0) bajo condiciones reales de funcionamiento.Por otro lado, para disminuir la latencia de decodificación de estas constelaciones esta tesis propone dos técnicas de detección/demapeo. Una es para constelaciones no uniformes de dos dimensiones la cual disminuye hasta en un 99,7% la complejidad del demapeo sin empeorar el funcionamiento del sistema. La segunda técnica de detección se centra en las constelaciones no uniformes de una dimensión y presenta hasta un 87,5% de reducción de la complejidad del receptor sin pérdidas en el rendimiento.Por último, este trabajo expone un completo estado del arte sobre tipos de constelaciones, modelos de sistema, y diseño/demapeo de constelaciones. Este estudio es el primero realizado en este campo

    Channel Estimation in Coded Modulation Systems

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    With the outstanding performance of coded modulation techniques in fading channels, much research efforts have been carried out on the design of communication systems able to operate at low signal-to-noise ratios (SNRs). From this perspective, the so-called iterative decoding principle has been applied to many signal processing tasks at the receiver: demodulation, detection, decoding, synchronization and channel estimation. Nevertheless, at low SNRs, conventional channel estimators do not perform satisfactorily. This thesis is mainly concerned with channel estimation issues in coded modulation systems where different diversity techniques are exploited to combat fading in single or multiple antenna systems. First, for single antenna systems in fast time-varying fading channels, the thesis focuses on designing a training sequence by exploiting signal space diversity (SSD). Motivated by the power/bandwidth efficiency of the SSD technique, the proposed training sequence inserts pilot bits into the coded bits prior to constellation mapping and signal rotation. This scheme spreads the training sequence during a transmitted codeword and helps the estimator to track fast variation of the channel gains. A comprehensive comparison between the proposed training scheme and the conventional training scheme is then carried out, which reveals several interesting conclusions with respect to both error performance of the system and mean square error of the channel estimator. For multiple antenna systems, different schemes are examined in this thesis for the estimation of block-fading channels. For typical coded modulation systems with multiple antennas, the first scheme makes a distinction between the iteration in the channel estimation and the iteration in the decoding. Then, the estimator begins iteration when the soft output of the decoder at the decoding iteration meets some specified reliability conditions. This scheme guarantees the convergence of the iterative receiver with iterative channel estimator. To accelerate the convergence process and decrease the complexity of successive iterations, in the second scheme, the channel estimator estimates channel state information (CSI) at each iteration with a combination of the training sequence and soft information. For coded modulation systems with precoding technique, in which a precoder is used after the modulator, the training sequence and data symbols are combined using a linear precoder to decrease the required training overhead. The power allocation and the placement of the training sequence to be precoded are obtained based on a lower bound on the mean square error of the channel estimation. It is demonstrated that considerable performance improvement is possible when the training symbols are embedded within data symbols with an equi-spaced pattern. In the last scheme, a joint precoder and training sequence is developed to maximize the achievable coding gain and diversity order under imperfect CSI. In particular, both the asymptotic performance behavior of the system with the precoded training scheme under imperfect CSI and the mean square error of the channel estimation are derived to obtain achievable diversity order and coding gain. Simulation results demonstrate that the joint optimized scheme outperforms the existing training schemes for systems with given precoders in terms of error rate and the amount of training overhead

    Adaptive modulation, coding and power allocation in cognitive radio networks

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    Channel Coding in Molecular Communication

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    This dissertation establishes and analyzes a complete molecular transmission system from a communication engineering perspective. Its focus is on diffusion-based molecular communication in an unbounded three-dimensional fluid medium. As a basis for the investigation of transmission algorithms, an equivalent discrete-time channel model (EDTCM) is developed and the characterization of the channel is described by an analytical derivation, a random walk based simulation, a trained artificial neural network (ANN), and a proof of concept testbed setup. The investigated transmission algorithms cover modulation schemes at the transmitter side, as well as channel equalizers and detectors at the receiver side. In addition to the evaluation of state-of-the-art techniques and the introduction of orthogonal frequency-division multiplexing (OFDM), the novel variable concentration shift keying (VCSK) modulation adapted to the diffusion-based transmission channel, the lowcomplex adaptive threshold detector (ATD) working without explicit channel knowledge, the low-complex soft-output piecewise linear detector (PLD), and the optimal a posteriori probability (APP) detector are of particular importance and treated. To improve the error-prone information transmission, block codes, convolutional codes, line codes, spreading codes and spatial codes are investigated. The analysis is carried out under various approaches of normalization and gains or losses compared to the uncoded transmission are highlighted. In addition to state-of-the-art forward error correction (FEC) codes, novel line codes adapted to the error statistics of the diffusion-based channel are proposed. Moreover, the turbo principle is introduced into the field of molecular communication, where extrinsic information is exchanged iteratively between detector and decoder. By means of an extrinsic information transfer (EXIT) chart analysis, the potential of the iterative processing is shown and the communication channel capacity is computed, which represents the theoretical performance limit for the system under investigation. In addition, the construction of an irregular convolutional code (IRCC) using the EXIT chart is presented and its performance capability is demonstrated. For the evaluation of all considered transmission algorithms the bit error rate (BER) performance is chosen. The BER is determined by means of Monte Carlo simulations and for some algorithms by theoretical derivation

    Harvesting time-frequency-space diversity with coded modulation for underwater acoustic communications

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2009.Includes bibliographical references (leaves 172-180).The goal of this thesis is to design a low-complexity, high data-rate acoustic communications system with robust performance under various channel conditions. The need for robust performance emerges because underwater acoustic (UWA) channels have time-varying statistics, thus a coded modulation scheme optimally designed for a specific channel model will be suboptimal when the channel statistics change. A robust approach should use a coded modulation scheme that provides good performance in both additive white Gaussian noise (AWGN) and Rayleigh fading channels (and, consequently in the Rice fading channel, an intermediate channel model between the latter two). Hence, high data-rate coded modulation schemes should exhibit both large free Euclidean and Hamming distances. In addition, coded modulation is regarded as a way to achieve time diversity over interleaved flat fading channels. UWA channels offer additional diversity gains in both frequency and space; therefore a system that exploits diversity in all three domains is highly desirable. Two systems with the same bit-rate and complexity but different free Euclidean and Hamming distances are designed and compared. The first system combines Trellis Coded Modulation (TCM) based on an 8-PSK signal set, symbol interleaving and orthogonal frequency-division multiplexing (OFDM). The second system combines bit-interleaved coded modulation (BICM), based on a convolutional code and a 16-QAM signal set, with OFDM.(cont.) Both systems are combined with specific space-time block codes (STBC) when two or three transmit antennas are used. Moreover, pilot-symbol-aided channel estimation is performed by using a robust 2-D Wiener filter, which copes with channel model mismatch by employing appropriate time and frequency correlation functions. The following result was obtained by testing the aforementioned systems using both simulated and experimental data from RACE '08: the BICM scheme performs better when the UWA channel exhibits limited spatial diversity. This result implies that coded modulation schemes emphasizing higher Hamming distances are preferred when there is no option for many receive/transmit hydrophones. The TCM scheme, on the other hand, becomes a better choice when the UWA channel demonstrates a high spatial diversity order. This result implies that coded modulation schemes emphasizing higher free Euclidean distances are preferred when multiple receive/transmit hydrophones are deployed.by Konstantinos Pelekanakis.Ph.D

    Machine Learning in Digital Signal Processing for Optical Transmission Systems

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    The future demand for digital information will exceed the capabilities of current optical communication systems, which are approaching their limits due to component and fiber intrinsic non-linear effects. Machine learning methods are promising to find new ways of leverage the available resources and to explore new solutions. Although, some of the machine learning methods such as adaptive non-linear filtering and probabilistic modeling are not novel in the field of telecommunication, enhanced powerful architecture designs together with increasing computing power make it possible to tackle more complex problems today. The methods presented in this work apply machine learning on optical communication systems with two main contributions. First, an unsupervised learning algorithm with embedded additive white Gaussian noise (AWGN) channel and appropriate power constraint is trained end-to-end, learning a geometric constellation shape for lowest bit-error rates over amplified and unamplified links. Second, supervised machine learning methods, especially deep neural networks with and without internal cyclical connections, are investigated to combat linear and non-linear inter-symbol interference (ISI) as well as colored noise effects introduced by the components and the fiber. On high-bandwidth coherent optical transmission setups their performances and complexities are experimentally evaluated and benchmarked against conventional digital signal processing (DSP) approaches. This thesis shows how machine learning can be applied to optical communication systems. In particular, it is demonstrated that machine learning is a viable designing and DSP tool to increase the capabilities of optical communication systems
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