Les systèmes de téléphonie mobile de 4ème et 5ème générations ont adopté comme techniques de codage de canal les turbocodes, les codes LDPC et les codes polaires binaires. Cependant, ces codes ne permettent pas de répondre aux exigences, en termes d’efficacité spectrale et de fiabilité, pour les réseaux de communications futurs (2030 et au-delà), qui devront supporter de nouvelles applications telles que les communications holographiques, les véhicules autonomes, l’internet tactile … Un premier pas a été fait il y a quelques années vers la définition de codes correcteurs d’erreurs plus puissants avec l’étude de codes LDPC non binaires, qui ont montré une meilleure performance que leurs équivalents binaires pour de petites tailles de code et/ou lorsqu'ils sont utilisés sur des canaux non binaires. En contrepartie, les codes LDPC non binaires présentent une complexité de décodage plus importante que leur équivalent binaire. Des études similaires ont commencé à émerger du côté des turbocodes. Tout comme pour leurs homologues LDPC, les turbocodes non binaires présentent d’excellentes performances pour de petites tailles de blocs. Du point de vue du décodage, les turbocodes non binaires sont confrontés au même problème d’augmentation de la complexité de traitement que les codes LDPC non binaire. Dans cette thèse nous avons proposé une nouvelle structure de turbocodes non binaires en optimisant les différents blocs qui la constituent. Nous avons réduit la complexité de ces codes grâce à la définition d’un algorithme de décodage simplifié. Les codes obtenus ont montré des performances intéressantes en comparaison avec les codes correcteur d’erreur de la littérature. / Nowadays communication standards have adopted different binary forward error correction codes. Turbo codes were adopted for the long term evolution standard, while binary LDPC codes were standardized for the fifth generation of mobile communication (5G) along side with the polar codes. Meanwhile, the focus of the communication community is shifted towards the requirement of beyond 5G standards. Networks for the year 2030 and beyond are expected to support novel forward-looking scenarios, such as holographic communications, autonomous vehicles, massive machine-type communications, tactile Internet… To respond to the expected requirements of new communication systems, non-binary LDPC codes were defined, and they are shown to achieve better error correcting performance than the binary LDPC codes. This performance gain was followed by a high decoding complexity, depending on the field order.Similar studies emerged in the context of turbo codes, where the non-binary turbo codes were defined, and have shown promising error correcting performance, while imposing high complexity. The aim of this thesis is to propose a new low-complex structure of non-binary turbocodes. The constituent blocks of this structure were optimized in this work, and a new low complexity decoding algorithm was proposed targeting a future hardware implementation. The obtained results are promising, where the proposed codes are shown to outperform existing binary and non-binary codes from the literature.

Research Doctorate - Doctor of Philosophy (PhD) / This thesis presents results on optimal coding and decoding of discrete-time stochastic signals, in the sense of minimizing a distortion metric subject to a constraint on the bit-rate and on the signal transfer function from source to reconstruction. The first (preliminary) contribution of this thesis is the introduction of new distortion metric that extends the mean squared error (MSE) criterion. We give this extension the name Weighted-Correlation MSE (WCMSE), and use it as the distortion metric throughout the thesis. The WCMSE is a weighted sum of two components of the MSE: the variance of the error component uncorrelated to the source, on the one hand, and the remainder of the MSE, on the other. The WCMSE can take account of signal transfer function constraints by assigning a larger weight to deviations from a target signal transfer function than to source-uncorrelated distortion. Within this framework, the second contribution is the solution of a family of feedback quantizer design problems for wide sense stationary sources using an additive noise model for quantization errors. These associated problems consist of finding the frequency response of the filters deployed around a scalar quantizer that minimize the WCMSE for a fixed quantizer signal-to-(granular)-noise ratio (SNR). This general structure, which incorporates pre-, post-, and feedback filters, includes as special cases well known source coding schemes such as pulse coded modulation (PCM), Differential Pulse-Coded Modulation (DPCM), Sigma Delta converters, and noise-shaping coders. The optimal frequency response of each of the filters in this architecture is found for each possible subset of the remaining filters being given and fixed. These results are then applied to oversampled feedback quantization. In particular, it is shown that, within the linear model used, and for a fixed quantizer SNR, the MSE decays exponentially with oversampling ratio, provided optimal filters are used at each oversampling ratio. If a subtractively dithered quantizer is utilized, then the noise model is exact, and the SNR constraint can be directly related to the bit-rate if entropy coding is used, regardless of the number of quantization levels. On the other hand, in the case of fixed-rate quantization, the SNR is related to the number of quantization levels, and hence to the bit-rate, when overload errors are negligible. It is shown that, for sources with unbounded support, the latter condition is violated for sufficiently large oversampling ratios. By deriving an upper bound on the contribution of overload errors to the total WCMSE, a lower bound for the decay rate of the WCMSE as a function of the oversampling ratio is found for fixed-rate quantization of sources with finite or infinite support. The third main contribution of the thesis is the introduction of the rate-distortion function (RDF) when WCMSE is the distortion metric, denoted by WCMSE-RDF. We provide a complete characterization for Gaussian sources. The resulting WCMSE-RDF yields, as special cases, Shannon's RDF, as well as the recently introduced RDF for source-uncorrelated distortions (RDF-SUD). For cases where only source-uncorrelated distortion is allowed, the RDF-SUD is extended to include the possibility of linear-time invariant feedback between reconstructed signal and coder input. It is also shown that feedback quantization schemes can achieve a bit-rate only 0.254 bits/sample above this RDF by using the same filters that minimize the reconstruction MSE for a quantizer-SNR constraint. The fourth main contribution of this thesis is to provide a set of conditions under which knowledge of a realization of the RDF can be used directly to solve encoder-decoder design optimization problems. This result has direct implications in the design of subband coders with feedback, as well as in the design of encoder-decoder pairs for applications such as networked control. As the fifth main contribution of this thesis, the RDF-SUD is utilized to show that, for Gaussian sta-tionary sources with memory and MSE distortion criterion, an upper bound on the information-theoretic causal RDF can be obtained by means of an iterative numerical procedure, at all rates. This bound is tighter than 0:5 bits/sample. Moreover, if there exists a realization of the causal RDF in which the re-construction error is jointly stationary with the source, then the bound obtained coincides with the causal RDF. The iterative procedure proposed here to obtain Ritc(D) also yields a characterization of the filters in a scalar feedback quantizer having an operational rate that exceeds the bound by less than 0:254 bits/sample. This constitutes an upper bound on the optimal performance theoretically attainable by any causal source coder for stationary Gaussian sources under the MSE distortion criterion.

Channel coding has been largely used for the purpose of improving error performance on a communications system. Typical methods based on added redundancy allow for error detection and correction, this improvement however comes at a cost of bandwidth. This thesis focuses on channel coding for the bandwidth-limited channel where no bandwidth expansion is allowed. We first discuss the idea of coding for the bandwidth-limited channel as seen from the signal space point of view where the purpose of coding is to maximize the Euclidian distance between constellation points without increasing the total signal power and under the condition that no extra bits can be added. We then see the problem from another angle and identify the tradeoffs related to bandwidth and error performance. This thesis intends to find a simple way of achieving an improvement in error performance for the bandwidth-limited channel without the use of lattice codes or trellis-coded modulation. The proposed system is based on convolutional coding followed by multilevel transmission. It achieved a coding gain of 2 dB on Eb/No or equivalently, a coding gain of approximately 2.7 dB on SNRnorm without increase in bandwidth. This coding gain is better than that obtained by a more sophisticated lattice code Gosset E8 at the same error rate.

Coding is an essential technology for efficient fiber-optic communications and secure quantum communications. In particular, low-density parity-check (LDPC) coding is favoured due to its strong error correction capability and high-throughput implementation feasibility. In fiber-optic communications, it has been realized that advanced high-order modulation formats and soft-decision forward error correction (FEC) such as LDPC codes are the key technologies for the next-generation high-speed optical communications. Therefore, energy-efficient LDPC coding in combination with advanced modulation formats is an important topic that needs to be studied for fiber-optic communications. In secure quantum communications, large-alphabet quantum key distribution (QKD) is becoming attractive recently due to its potential in improving the efficiency of key exchange. To recover the carried information bits, efficient information reconciliation is desirable, for which the use of LDPC coding is essential. In this dissertation, we first explore different efficient LDPC coding schemes for optical transmission of polarization-division multiplexed quadrature-amplitude modulation (QAM) signals. We show that high energy efficiency can be achieved without incurring extra overhead and complexity. We then study the transmission performance of LDPC-coded turbo equalization for QAM signals in a realistic fiber link as well as that of pragmatic turbo equalizers. Further, leveraging the polarization freedom of light, we expand the signal constellation into a four-dimensional (4D) space and evaluate the performance of LDPC-coded 4D signals in terms of transmission reach. Lastly, we study the security of a proposed weak-coherent-state large-alphabet QKD protocol and investigate the information reconciliation efficiency based on LDPC coding.

Research Doctorate - Doctor of Philosophy (PhD) / This thesis presents results on optimal coding and decoding of discrete-time stochastic signals, in the sense of minimizing a distortion metric subject to a constraint on the bit-rate and on the signal transfer function from source to reconstruction. The first (preliminary) contribution of this thesis is the introduction of new distortion metric that extends the mean squared error (MSE) criterion. We give this extension the name Weighted-Correlation MSE (WCMSE), and use it as the distortion metric throughout the thesis. The WCMSE is a weighted sum of two components of the MSE: the variance of the error component uncorrelated to the source, on the one hand, and the remainder of the MSE, on the other. The WCMSE can take account of signal transfer function constraints by assigning a larger weight to deviations from a target signal transfer function than to source-uncorrelated distortion. Within this framework, the second contribution is the solution of a family of feedback quantizer design problems for wide sense stationary sources using an additive noise model for quantization errors. These associated problems consist of finding the frequency response of the filters deployed around a scalar quantizer that minimize the WCMSE for a fixed quantizer signal-to-(granular)-noise ratio (SNR). This general structure, which incorporates pre-, post-, and feedback filters, includes as special cases well known source coding schemes such as pulse coded modulation (PCM), Differential Pulse-Coded Modulation (DPCM), Sigma Delta converters, and noise-shaping coders. The optimal frequency response of each of the filters in this architecture is found for each possible subset of the remaining filters being given and fixed. These results are then applied to oversampled feedback quantization. In particular, it is shown that, within the linear model used, and for a fixed quantizer SNR, the MSE decays exponentially with oversampling ratio, provided optimal filters are used at each oversampling ratio. If a subtractively dithered quantizer is utilized, then the noise model is exact, and the SNR constraint can be directly related to the bit-rate if entropy coding is used, regardless of the number of quantization levels. On the other hand, in the case of fixed-rate quantization, the SNR is related to the number of quantization levels, and hence to the bit-rate, when overload errors are negligible. It is shown that, for sources with unbounded support, the latter condition is violated for sufficiently large oversampling ratios. By deriving an upper bound on the contribution of overload errors to the total WCMSE, a lower bound for the decay rate of the WCMSE as a function of the oversampling ratio is found for fixed-rate quantization of sources with finite or infinite support. The third main contribution of the thesis is the introduction of the rate-distortion function (RDF) when WCMSE is the distortion metric, denoted by WCMSE-RDF. We provide a complete characterization for Gaussian sources. The resulting WCMSE-RDF yields, as special cases, Shannon's RDF, as well as the recently introduced RDF for source-uncorrelated distortions (RDF-SUD). For cases where only source-uncorrelated distortion is allowed, the RDF-SUD is extended to include the possibility of linear-time invariant feedback between reconstructed signal and coder input. It is also shown that feedback quantization schemes can achieve a bit-rate only 0.254 bits/sample above this RDF by using the same filters that minimize the reconstruction MSE for a quantizer-SNR constraint. The fourth main contribution of this thesis is to provide a set of conditions under which knowledge of a realization of the RDF can be used directly to solve encoder-decoder design optimization problems. This result has direct implications in the design of subband coders with feedback, as well as in the design of encoder-decoder pairs for applications such as networked control. As the fifth main contribution of this thesis, the RDF-SUD is utilized to show that, for Gaussian sta-tionary sources with memory and MSE distortion criterion, an upper bound on the information-theoretic causal RDF can be obtained by means of an iterative numerical procedure, at all rates. This bound is tighter than 0:5 bits/sample. Moreover, if there exists a realization of the causal RDF in which the re-construction error is jointly stationary with the source, then the bound obtained coincides with the causal RDF. The iterative procedure proposed here to obtain Ritc(D) also yields a characterization of the filters in a scalar feedback quantizer having an operational rate that exceeds the bound by less than 0:254 bits/sample. This constitutes an upper bound on the optimal performance theoretically attainable by any causal source coder for stationary Gaussian sources under the MSE distortion criterion.

Approved for public release; distribution is unlimited. / Trellis-Coded Modulation (TCM) is employed with quadrature amplitude modulation (QAM) to provide error correction coding with no expense in bandwidth. There are two common implementations of TCM, namely pragmatic TCM and Ungerboeck TCM. Both schemes employ Viterbi algorithms for decoding but have different code construction. This thesis investigates and compares the performance of pragmatic TCM and Ungerboeck TCM by implementing the Viterbi decoding algorithm for both schemes with 16-QAM and 64-QAM. Both pragmatic and Ungerboeck TCM with six memory elements are considered. Simulations were carried out for both pragmatic and Ungerboeck TCM to evaluate their respective performance. The simulations were done using Matlab software, and an additive white Gaussian noise channel was assumed. The objective was to ascertain that pragmatic TCM, with its reduced-complexity decoding, is more suitable to adaptive modulation than Ungerboeck TCM. / Civilian

This work deals with forward error correction. In the work, basic methods and algorithms of error correction are described. For the presentation of encoding and decoding process of Hamming code, Reed-Müller code, Fire code, Reed-Solomon code and Trellis coded modulation programs in Matlab were created.

Made available in DSpace on 2014-12-17T14:55:43Z (GMT). No. of bitstreams: 1 AlineFGS_DISSERT.pdf: 1151209 bytes, checksum: 4ae192dd7519e3e14977154f7b70d951 (MD5) Previous issue date: 2010-06-14 / Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico / In this work, a performance analysis of transmission schemes employing turbo trellis coded modulation. In general, the performance analysis of such schemes is guided by evaluating the error probability of these schemes. The exact evaluation of this probability is very complex and inefficient from the computational point of view, a widely used alternative is the use of union bound of error probability, because of its easy implementation and computational produce bounds that converge quickly. Since it is the union bound, it should use to expurge some elements of distance spectrum to obtain a tight bound. The main contribution of this work is that the listing proposal is carried out from the puncturing at the level of symbol rather than bit-level as in most works of literature. The main reason for using the symbol level puncturing lies in the fact that the enummerating function of the turbo scheme is obtained directly from complex sequences of signals through the trellis and not indirectly from the binary sequences that require further binary to complex mapping, as proposed by previous works. Thus, algorithms can be applied through matrix from the adjacency matrix, which is obtained by calculating the distances of the complex sequences of the trellis. This work also presents two matrix algorithms for state reduction and the evaluation of the transfer function of this. The results presented in comparisons of the bounds obtained using the proposed technique with some turbo codes of the literature corroborate the proposition of this paper that the expurgated bounds obtained are quite tight and matrix algorithms are easily implemented in any programming software language / Neste trabalho ? feita uma an?lise de desempenho de esquemas de transmiss?o empregando modula??o codificada turbo em treli?a. Em geral, a an?lise de desempenho de tais esquemas ? guiada pelo c?lculo da probabilidade de erro destes esquemas. O c?lculo exato desta probabilidade ? muito complexo e ineficiente sob o ponto de vista computacional, uma alternativa muito utilizada ? o emprego de limitante da uni?o da probabilidade de erro, por ser de f?cil implementa??o computacional e produzir limitantes que convergem rapidamente. Por se tratar do limitante da uni?o, este deve utilizar de expurgo de alguns elementos do espectro de dist?ncias do c?digo para a obten??o de um limitante apertado. A principal contribui??o deste trabalho ? que a enumera??o proposta ? realizada a partir da perfura??o a n?vel de s?mbolo e n?o a n?vel de bit como na maioria dos trabalhos da literatura. O principal motivo do uso da perfura??o a n?vel de s?mbolo reside no fato que a fun??o enumeradora do esquema turbo ? obtida diretamente das seq??ncias complexas de sinais atrav?s da treli?a e n?o de forma indireta a partir da seq??ncias bin?rias que exigem posterior mapeando bin?rio para complexo, como proposto por trabalhos anteriores. Assim, podem ser aplicados algoritmos completamente matriciais a partir da matriz adjac?ncia, que ? obtida a partir do c?lculo das dist?ncias das seq??ncias complexas da treli?a e n?o das seq??ncias bin?rias. Neste trabalho tamb?m s?o apresentados dois algoritmos matriciais de redu??o de estados do codificador bem como do c?lculo da fun??o de transfer?ncia deste. Os resultados apresentados em forma de compara??es dos limitantes obtidos utilizando a t?cnica proposta com alguns c?digos turbo da literatura corroboram com a proposi??o deste trabalho que os limitantes expurgados obtidos s?o apertados e os algoritmos completamente matriciais s?o facilmente implementados em qualquer software de programa??o simb?lica

Nowadays, the digital terrestrial television (DTT) market is characterized by the high capacity needed for high definition TV services. There is a need for an efficient use of the broadcast spectrum, which requires new technologies to guarantee increased capacities. Non-Uniform Constellations (NUC) arise as one of the most innovative techniques to approach those requirements. NUCs reduce the gap between uniform Gray-labelled Quadrature Amplitude Modulation (QAM) constellations and the theoretical unconstrained Shannon limit. With these constellations, symbols are optimized in both in-phase (I) and quadrature (Q) components by means of signal geometrical shaping, considering a certain signal-to-noise ratio (SNR) and channel model. There are two types of NUC, one-dimensional and two-dimensional NUCs (1D-NUC and 2D-NUC, respectively). 1D-NUCs maintain the squared shape from QAM, but relaxing the distribution between constellation symbols in a single component, with non-uniform distance between them. These constellations provide better SNR performance than QAM, without any demapping complexity increase. 2D-NUCs also relax the square shape constraint, allowing to optimize the symbol positions in both dimensions, thus achieving higher capacity gains and lower SNR requirements. However, the use of 2D-NUCs implies a higher demapping complexity, since a 2D-demapper is needed, i.e. I and Q components cannot be separated. In this dissertation, NUCs are analyzed from both transmit and receive point of views, using either single-input single-output (SISO) or multiple-input multiple-output (MIMO) antenna configurations. In SISO transmissions, 1D-NUCs and 2D-NUCs are optimized for a wide range of SNRs and different constellation orders. The optimization of rotated 2D-NUCs is also investigated. Even though the demapping complexity is not increased, the SNR gain of these constellations is not significant. The highest rotation gain is obtained for low-order constellations and high SNRs. However, with multi-RF techniques, the SNR gain is drastically increased, since I and Q components are transmitted in different RF channels. In this thesis, multi-RF gains of NUCs with and without rotation are provided for some representative scenarios. At the receiver, two different implementation bottlenecks are explored. First, the demapping complexity of all considered constellations is analyzed. Afterwards, two complexity reduction algorithms for 2D-NUCs are proposed. Both algorithms drastically reduce the number of distances to compute. Moreover, both are finally combined in a single demapper. Quantization of NUCs is also explored in this dissertation, since LLR values and I/Q components are modified when using these constellations, compared to traditional QAM constellations. A new algorithm that is based on the optimization of the quantizer levels for a particular constellation is proposed. The use of NUCs in multi-antenna communications is also investigated. It includes the optimization in one or two antennas, the use of power imbalance, the cross-polar discrimination (XPD) between receive antennas, or the use of different demappers. Assuming different values for the parameters evaluated, new Multi-Antenna Non-Uniform Constellations (MA-NUC) are obtained by means of a particularized re-optimization process, specific for MIMO. At the receiver, an extended demapping complexity analysis is performed, where it is shown that the use of 2D-NUCs in MIMO extremely increases the demapping complexity. As an alternative, an efficient solution for 2D-NUCs and MIMO systems based on Soft-Fixed Sphere Decoding (SFSD) is proposed. The main drawback is that SFSD demappers do not work with 2D-NUCs, since they perform a Successive Interference Cancellation (SIC) step that needs to be performed in separated I and Q components. The proposed method quantifies the closest symbol using Voronoi regions and allows SFSD demappers to work. / Hoy en día, el mercado de la televisión digital terrestre (TDT) está caracterizado por la alta capacidad requerida para transmitir servicios de televisión de alta definición y el espectro disponible. Es necesario por tanto un uso eficiente del espectro radioeléctrico, el cual requiere nuevas tecnologías para garantizar mayores capacidades. Las constelaciones no-uniformes (NUC) emergen como una de las técnicas más innovadoras para abordar tales requerimientos. Las NUC reducen el espacio existente entre las constelaciones uniformes QAM y el límite teórico de Shannon. Con estas constelaciones, los símbolos se optimizan en ambas componentes fase (I) y cuadratura (Q) mediante técnicas geométricas de modelado de la señal, considerando un nivel señal a ruido (SNR) concreto y un modelo de canal específico. Hay dos tipos de NUC, unidimensionales y bidimensionales (1D-NUC y 2D-NUC, respectivamente). Las 1D-NUC mantienen la forma cuadrada de las QAM, pero permiten cambiar la distribución entre los símbolos en una componente concreta, teniendo una distancia no uniforme entre ellos. Estas constelaciones proporcionan un mejor rendimiento SNR que QAM, sin ningún incremento en la complejidad en el demapper. Las 2D-NUC también permiten cambiar la forma cuadrada de la constelación, permitiendo optimizar los símbolos en ambas dimensiones y por tanto obteniendo mayores ganancias en capacidad y menores requerimientos en SNR. Sin embargo, el uso de 2D-NUCs implica una mayor complejidad en el receptor. En esta tesis se analizan las NUC desde el punto de vista tanto de transmisión como de recepción, utilizando bien configuraciones con una antena (SISO) o con múltiples antenas (MIMO). En transmisiones SISO, se han optimizado 1D-NUCs para un rango amplio de distintas SNR y varios órdenes de constelación. También se ha investigado la optimización de 2D-NUCs rotadas. Aunque la complejidad no aumenta, la ganancia SNR de estas constelaciones no es significativa. La mayor ganancia por rotación se obtiene para bajos órdenes de constelación y altas SNR. Sin embargo, utilizando técnicas multi-RF, la ganancia aumenta drásticamente puesto que las componentes I y Q se transmiten en distintos canales RF. En esta tesis, se han estudiado varias ganancias multi-RF representativas de las NUC, con o sin rotación. En el receptor, se han identificado dos cuellos de botella diferentes en la implementación. Primero, se ha analizado la complejidad en el receptor para todas las constelaciones consideradas y, posteriormente, se proponen dos algoritmos para reducir la complejidad con 2D-NUCs. Además, los dos pueden combinarse en un único demapper. También se ha explorado la cuantización de estas constelaciones, ya que tanto los valores LLR como las componentes I/Q se ven modificados, comparando con constelaciones QAM tradicionales. Además, se ha propuesto un algoritmo que se basa en la optimización para diferentes niveles de cuantización, para una NUC concreta. Igualmente, se ha investigado en detalle el uso de NUCs en MIMO. Se ha incluido la optimización en una sola o en dos antenas, el uso de un desbalance de potencia, factores de discriminación entre antenas receptoras (XPD), o el uso de distintos demappers. Asumiendo distintos valores, se han obtenido nuevas constelaciones multi-antena (MA-NUC) gracias a un nuevo proceso de re-optimización específico para MIMO. En el receptor, se ha extendido el análisis de complejidad en el demapper, la cual se incrementa enormemente con el uso de 2D-NUCs y sistemas MIMO. Como alternativa, se propone una solución basada en el algoritmo Soft-Fixed Sphere Decoding (SFSD). El principal problema es que estos demappers no funcionan con 2D-NUCs, puesto que necesitan de un paso adicional en el que las componentes I y Q necesitan separarse. El método propuesto cuantifica el símbolo más cercano utilizando las regiones de Voronoi, permitiendo el uso de este tipo de receptor. / Actualment, el mercat de la televisió digital terrestre (TDT) està caracteritzat per l'alta capacitat requerida per a transmetre servicis de televisió d'alta definició i l'espectre disponible. És necessari per tant un ús eficient de l'espectre radioelèctric, el qual requereix noves tecnologies per a garantir majors capacitats i millors servicis. Les constel·lacions no-uniformes (NUC) emergeixen com una de les tècniques més innovadores en els sistemes de televisió de següent generació per a abordar tals requeriments. Les NUC redueixen l'espai existent entre les constel·lacions uniformes QAM i el límit teòric de Shannon. Amb estes constel·lacions, els símbols s'optimitzen en ambdós components fase (I) i quadratura (Q) per mitjà de tècniques geomètriques de modelatge del senyal, considerant un nivell senyal a soroll (SNR) concret i un model de canal específic. Hi ha dos tipus de NUC, unidimensionals i bidimensionals (1D-NUC i 2D-NUC, respectivament). 1D-NUCs mantenen la forma quadrada de les QAM, però permet canviar la distribució entre els símbols en una component concreta, tenint una distància no uniforme entre ells. Estes constel·lacions proporcionen un millor rendiment SNR que QAM, sense cap increment en la complexitat al demapper. 2D-NUC també canvien la forma quadrada de la constel·lació, permetent optimitzar els símbols en ambdós dimensions i per tant obtenint majors guanys en capacitat i menors requeriments en SNR. No obstant això, l'ús de 2D-NUCs implica una major complexitat en el receptor, ja que es necessita un demapper 2D, on les components I i Q no poden ser separades. En esta tesi s'analitzen les NUC des del punt de vista tant de transmissió com de recepció, utilitzant bé configuracions amb una antena (SISO) o amb múltiples antenes (MIMO). En transmissions SISO, s'han optimitzat 1D-NUCs, per a un rang ampli de distintes SNR i diferents ordes de constel·lació. També s'ha investigat l'optimització de 2D-NUCs rotades. Encara que la complexitat no augmenta, el guany SNR d'estes constel·lacions no és significativa. El major guany per rotació s'obté per a baixos ordes de constel·lació i altes SNR. No obstant això, utilitzant tècniques multi-RF, el guany augmenta dràsticament ja que les components I i Q es transmeten en distints canals RF. En esta tesi, s'ha estudiat el guany multi-RF de les NUC, amb o sense rotació. En el receptor, s'han identificat dos colls de botella diferents en la implementació. Primer, s'ha analitzat la complexitat en el receptor per a totes les constel·lacions considerades i, posteriorment, es proposen dos algoritmes per a reduir la complexitat amb 2D-NUCs. Ambdós algoritmes redueixen dràsticament el nombre de distàncies. A més, els dos poden combinar-se en un únic demapper. També s'ha explorat la quantització d'estes constel·lacions, ja que tant els valors LLR com les components I/Q es veuen modificats, comparant amb constel·lacions QAM tradicionals. A més, s'ha proposat un algoritme que es basa en l'optimització per a diferents nivells de quantització, per a una NUC concreta. Igualment, s'ha investigat en detall l'ús de NUCs en MIMO. S'ha inclòs l'optimització en una sola o en dos antenes, l'ús d'un desbalanç de potència, factors de discriminació entre antenes receptores (XPD), o l'ús de distints demappers. Assumint distints valors, s'han obtingut noves constel·lacions multi-antena (MA-NUC) gràcies a un nou procés de re-optimització específic per a MIMO. En el receptor, s'ha modificat l'anàlisi de complexitat al demapper, la qual s'incrementa enormement amb l'ús de 2D-NUCs i sistemes MIMO. Com a alternativa, es proposa una solució basada en l'algoritme Soft-Fixed Sphere Decoding (SFSD) . El principal problema és que estos demappers no funcionen amb 2D-NUCs, ja que necessiten d'un pas addicional en què les components I i Q necessiten separar-se. El mètode proposat quantifica el símbol més pròxim utilitzan / Fuentes Muela, M. (2017). Non-Uniform Constellations for Next-Generation Digital Terrestrial Broadcast Systems [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/84743

ITC/USA 2014 Conference Proceedings / The Fiftieth Annual International Telemetering Conference and Technical Exhibition / October 20-23, 2014 / Town and Country Resort & Convention Center, San Diego, CA / This paper discusses the mission needs, design/development, and testing of the (L, S & C Band) Telemetry Receive/Record & Re-Radiation pod.