Resource Allocation in Service Area based Networks

By applying joint transmission in the downlink and joint detection in the uplink, the novel service area architecture allows multiple mobile stations to be simultaneously active on the same OFDM subcarrier without causing interference to each other. Moreover, the proposed adaptive subcarrier and power allocation techniques are shown to be able to improve the spectral efficiency significantly in service area based networks. The significance of the frequency selectivity of wireless channels, the correlation among users’ spatial signatures and the presence of interferences to resource allocation is also assessed through simulations.Durch den Einsatz von Joint Detection in der Aufwärtsstrecke und Joint Transmission in der Abwärtsstrecke ermöglicht die neuartige Service Area Architektur es mehreren Mobilstationen in dem selben OFDM-Subträger gleichzeitig interferenzfrei aktiv zu sein. Darüber hinaus wrid gezeigt, dass die vorgeschlagenen adaptiven Subträger- und Leistungsallokationstechniken die spektrale Effizienz eines Service Area basierten Mobilfunksystems erheblich erhöhen können. Die Bedeutung der Frequnzselektivität der Funkkanäle, der Korrelation zwischen räumlichen Signaturen der Teinehmer und der Existenz der Interferenz für die adaptive Ressourcenallokation wird ebenfalls durch Computersimulationen bewertet

Optimum power allocation and bit loading with code rate constraints

In this paper, a new power allocation and bit loading policy is defined for those systems working with a preselected binary channel code and specific bit error rate (BER) requirements. It consists on the maximization of the spectral efficiency with a constraint on the average mutual information per coded bit (bit MI), exploiting the relationship of the bit MI with the BER and the code rate. An irregular modulation approach is employed in order to express the policy as a convex optimization problem, solved without the need of greedy algorithms. Results are compared with those obtained with other algorithms in the literature.Postprint (published version

Channel equalization to achieve high bit rates in discrete multitone systems

textMulticarrier modulation (MCM) techniques such as orthogonal frequency division multiplexing (OFDM) and discrete multi-tone (DMT) modulation are attractive for high-speed data communications due to the ease with which MCM can combat channel dispersion. With all the benefits MCM could give, DMT modulation has an extra ability to perform dynamic bit loading, which has the potential to exploit fully the available bandwidth in a slowly time-varying channel. In broadband wireline communications, DMT modulation is standardized for asymmetric digital subscribe line (ADSL) and very-high-bit-rate digital subscriber line (VDSL) modems. ADSL and VDSL standards are used by telephone companies to provide high speed data service to residences and offices. In an ADSL receiver, an equalizer is required to compensate for the channel’s dispersion in the time domain and the channel’s distortion in the frequency domain of the transmitted waveform. This dissertation proposes design methods for linear equalizers to increase the bit rate of the connection. The methods are amenable to implementation on programmable fixed-point digital signal processors, which are employed in ADSL/VDSL transceivers. A conventional ADSL equalizer consists of a time-domain equalizer, a fast Fourier transform, and a frequency domain equalizer. The time domain equalizer (TEQ) is a finite impulse response filter that when coupled with a discretized channel produces an equivalent channel whose impulse response is shorter than that of the discretized channel. This channel shortening is required by the ADSL standards. In this dissertation, I first propose a linear phase TEQ design that exploits symmetry in existing eigen-filter approaches such as minimum mean square error(MMSE), maximum shortening signal to noise ratio (MSSNR) and minimum intersymbol interference (Min-ISI) equalizers. TEQs with symmetric coefficients can reach the same performance as non-symmetric ones with much lower training complexity. Second, I improve Min-ISI design. I reformulate the cost function to make long TEQs design feasible. I remove the dependency of transmission delay in order to reduce the complexity associated with delay optimization. The quantized weighting is introduced to further lower the complexity. I also propose an iterative optimization procedure of Min-ISI that completely avoids Cholesky decomposition hence is better suited for a fixed-point implementation. Finally I propose a dual-path TEQ structure, which designs a standard singleFIR TEQ to achieve good bit rate over the entire transmission bandwidth, and designs another FIR TEQ to improve the bit rate over a subset of subcarriers. Dualpath TEQ can be viewed as a special case of a complex valued filter bank structure that delivers the best bit rate of existing DMT equalizers. However, dual-path TEQ provides a very good tradeoff between achievable bit rate vs. implementation complexity on a programmable digital signal processor.Electrical and Computer Engineerin

Bit and power loading for MIMO systems with statistical channel knowledge at the transmitter

In MIMO (multiple input-multiple output) communication, the adaptation of the modulation and coding at the transmitter side according to the channel characteristics allows reducing the transmission power and/or enhancing the data rates. However, it is not always feasible to have instantaneous knowledge of the channel at the transmitter. This Thesis focuses on the case that the receiver has (perfect) instantaneous Channel State Information (CSIR) but the transmitter has only access to its distribution (CDIT). This is a practical case that applies, particularly, to situations where the channel varies rapidly. Under CDIT, the input cannot be adapted to the instantaneous state of the channel and thus SVD (singular value decomposition) cannot be used to diagonalize the channel. Achieving capacity requires a complex Gaussian input vector with a covariance that depends on the channel distribution. In practice, however, discrete constellations are used instead of Gaussian signals. Determining the optimum signalling strategy with discrete constellations is difficult in general, and thus a pragmatic approach is using the spatial signalling directions indicated by the capacityachieving covariance. Several classical practical bit and power loading algorithms are available for parallel-channel settings. To guarantee the quality of service, a certain average bit error probability (BER) is required at the receiver side. Different types of receiver correspond to differente relationships between the BER and the SINR. With the feedback of the parameters of the SINR (Signal-to-Interference-plus-Noise Ratio) distribution, two optimization problems for single user MIMO systems with correlation at the transmitter side can be solved, namely rate maximization with a total power constraint and power minimization with a target bit rate. The goal of this Thesis is to devise practical bit and power loading schemes for MIMO that can operate on the basis of CDIT only. For practical reasons, three typical receivers are considered, namely zero-forcing (ZF), minimum mean squared error (MMSE) and zero-forcing with successive interference cancellation (ZF-SIC). The following problems are addressed: • Maximization of the bit rates with discrete constellations, using the transmit directions given by the capacity achieving input covariance, at a certain average bit error probability (BER) and a constraint of total transmit power. • Minimization of the transmit power with discrete constellations, using the transmit directions given by the capacity achieving input covariance, at a certain average bit error probability (BER) and a target transmit bit rate. • Evaluation and comparison of the power gain when optimizing the transmission with the three mentioned types of receivers relative to a non-optimized transmission. In order to address these items, in this work it is essential to establish a relationship between the average BER corresponding to each of the three receivers and the powers allocated at the transmitter under the premise of CDIT. By utilizing these BER approximations, two dual optimization problems, bit maximization and power minimization, are solved for the practical case of statistical channel knowledge at the transmitter side and discrete constellations. Using a Gamma or a generalized Gamma distribution of the SINR, BER approximations can be obtained through integration. For a single user MIMO system with correlated channel, to accomplish the optimization process the mathematical methods used are a Levin-Campello algorithm for ZF, exhaustive search with additional constraints for MMSE and tree search with bit rate boundary for ZF-SIC. The accuracy of the developed expressions is verified with Monte Carlo simulations. The transmission environment is specified to be a Rayleigh flat-fading channel with correlation at the transmitter side. The Thesis is structured as follows. An introduction is presented at the first chapter, explaining the contents of this Thesis. Following a description of the basic process which takes place at the transmitter side, the second chapter presents the characteristics of the MIMO channel. Moreover, the system models of three typical receivers are described, namely ZF, MMSE and ZF-SIC. The third chapter starts with a review of capacity, and leads to the so-called waterfilling distribution. The dual optimization problems, bit rate maximization and power minimization, are defined with the objective of enhancing the performance via processing at the transmitter side. In some practical systems, Levin-Campello develops a solution for the dual optimization problems for discrete constellations that is described. Also, in order to further understand the power minimization problem for discrete constellations considering the loss of mutual information due to a given modulation, Mercury/Waterfilling is reviewed. In chapter IV, the BER of a ZF receiver is computed by using its SINR distribution, which is a Gamma distribution. For convenience, it is further accurately approximated at the high SNR regime. From the relationship between BER and power for different constellations, the two dual problems can be solved by a Levin-Campello algorithm, as the streams are independent with each other. To facilitate using the Levin-Campello algorithm, BER approximations are simplified to be established in convenient closedform equations. In chapter V, the BER of an MMSE receiver is also computed by using its SINR distribution, which can be modeled as a Gamma distribution or a generalized Gamma distribution. Some accurate closed-formed approximations are proposed and compared. In chapter VI, from these relationships between BER and power for different constellations, the two dual problems are solved by exhaustive search, as the streams are coupled with each other in the case of the MMSE receiver. In order to reduce the computational complexity, some additional constrains are added. For the two dual optimization problems, the total number of transmitted bits with an MMSE receiver cannot be less than those with a ZF receiver. Therefore, the starting point for the search is always the solution derived for ZF receivers, and the search progresses from that point towards higher loads until the constraints set in. The BER of MMSE can be approximated by the moment generating function (MGF), which includes the first three moments of SINR. Comparing two randomly selected antennas, when an increment of the number of bits is added to one of them, placing the increment in the antenna with better channel condition requires less total power to accomplish the transmission. Thus, it can be concluded that the better channel should be loaded with more bits. With this additional constraint, the computational complexity of the exhaustive search can be reduced even more reasonably. In chapter VII, taking into account the error propagation, a closed-form BER approximation can be derived for the ZF-SIC receiver by using the total probability theorem. Moreover, since the ordering of the decoding process can dramatically impact the system performance when using this receiver, a precoder is proposed to determine the decoder ordering to minimize the total power. Moreover, a boundary of possible bit rates for ZF-SIC is presented, considering the bit rate of ZF and ZF-PSIC (perfect SIC), for the two dual optimization problems. To make the search converge more efficiently, a tree search is implemented making use of this boundary. In the final chapter, the results obtained for the different receivers are compared to conclude the core of this Thesis. Then, some future work is outlined. ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------En los sistemas de comunicaciones multiantena (MIMO: multiple inputmultiple output), la adaptación de los esquemas de modulación y codificación en el extremo transmisor según las características del canal permite reducir la potencia de transmisión y/o aumentar la velocidad de transmisión. Sin embargo, no siempre es posible tener conocimiento instantáneo del canal en el transmisor. Esta Tesis se centra en el caso en que el receptor tiene (perfecta) información instantánea del canal (CSIR: Channel State Information at the Receiver), pero el transmisor únicamente tiene acceso a su distribución (CDIT: Channel Distribution Information at the Transmitter). Este es un caso práctico que sucede, en particular, en situaciones en las que el canal varía rápidamente. Con CDIT, la señal no se puede adaptar al estado instantáneo del canal y, por tanto, no es posible usar una descomposición en valores singulares para diagonalizar el canal. Alcanzar la capacidad requiere el uso de señales Gaussianas cuya correlación depende de la distribución del canal. En la práctica, sin embargo, se utilizan constelaciones discretas y no señales Gaussianas. Determinar la estrategia óptima de transmisión con constelaciones discretas es difícil en general y, por ello, tomaremos una aproximación pragmática consistente en utilizar las direcciones espaciales correspondientes a la matriz de covarianza que permite obtener la capacidad (con señales Gaussianas). Para constelaciones discretas y canales paralelos independientes existen varios algoritmos de carga adaptativa de bits y potencia (bit and power loading) clásicos, que no son directamente aplicables al sistema bajo estudio. Si deseamos garantizar la calidad de servicio, se requiere una cierta probabilidad de error promedio (BER: bit error rate) en el extremo receptor. A diferentes tipos de receptor corresponden relaciones distintas entre la BER y la relación señal a interferencia (SINR: signal to interference plus noise ratio). Con la realimentación de los parámetros de la distribución de SINR al transmisor es posible resolver dos problemas duales de optimización en sistemas MIMO de usuario único con canal con correlación en el extremo transmisor: maximización de la tasa binaria con una restricción de potencia y minimización de la potencia transmitida con una restricción de la tasa binaria objetivo. El objetivo de esta Tesis es diseñar esquemas prácticos de carga adaptativa de bits y potencia para sistemas MIMO, que puedan operar sobre la base de conocimiento estadístico del canal en el transmisor (CDIT) únicamente. Por motivos prácticos, consideramos tres tipos de receptores típicos: receptor de forzado a cero (ZF), receptor de mínimo error cuadrático medio (MMSE), y receptor ZF con cancelación sucesiva de interferencias (ZF-SIC). Para estos tres receptores se abordan los siguientes problemas: • Maximizar la tasa binaria con constelaciones discretas, usando las direcciones espaciales de transmisión dictadas por la matriz de covarianza que alcanza la capacidad, garantizando una cierta probabilidad de error promedio y con la restricción de la potencia total a transmitir. • Minimizar la potencia de transmisión con constelaciones discretas, usando las direcciones espaciales de transmisión dictadas por la matriz de covarianza que alcanza la capacidad, garantizando una cierta probabilidad de error promedio y satisfaciendo un requisito de tasa binaria. • Obtener y comparar la ganancia de potencia de los tres tipos de receptores mencionados en relación con una transmisión sin optimizar. Para abordar estos problemas, es esencial establecer una relación entre la probabilidad de error promedio de cada uno de los receptores y la potencia asignada en el transmisor a cada flujo de datos MIMO, bajo la premisa de conocimiento CDIT. A partir de la distribución Gamma o Gamma generalizada de la SINR, se obtienen aproximaciones para la probabilidad de error promedio mediante integración. Para un sistema MIMO de usuario único con canal correlado, los métodos matemáticos empleados para resolver los problemas de optimización son: algoritmo “Levin-Campello” para ZF, búsqueda exhaustiva con restricciones adicionales para MMSE, y búsqueda en árbol con tasa binaria acotada para ZF-SIC. La precisión de las aproximaciones y las prestaciones de los algoritmos desarrollados se evalúan mediante simulación de Monte Carlo. El entorno de transmisión viene dado por un canal MIMO con desvanecimiento tipo Rayleigh, plano en frecuencia y con correlación en el extremo transmisor. La estructura de la Tesis es la siguiente. En el primer capítulo se presenta una introducción y se describe el contenido de la Tesis. A continuación, tras una descripción del procesado básico que tiene lugar en el transmisor, el capítulo II presenta las características del canal MIMO. Además, se describen el modelo del sistema y los tres receptores que se van a tratar: ZF, MMSE y ZF-SIC. El capítulo III comienza con una revisión de la capacidad, lo que conduce a la denominada distribución de “waterfilling” en sistemas MIMO. Los dos problemas de optimización duales, maximización de la tasa binaria y minimización de la potencia, se definen para mejorar las prestaciones mediante procesado en el extremo transmisor. En algunos sistemas prácticos, el algoritmo de Levin-Campello constituye una solución para estos problemas de optimización duales con constelaciones discretas, por lo que se presenta una revisión del mismo. Con el fin de comprender mejor el problema de minimización de potencia para constelaciones discretas, considerando la pérdida de información mutua debida a una modulación concreta, se revisa a continuación la distribución conocida como “mercury/waterfilling”. En el capítulo IV, se estima la probabilidad de error promedio para un receptor ZF utilizando la distribución de la SINR, que corresponde a una función de densidad de probabilidad Gama, y se encuentra una aproximación para relación señal a ruido alta que resulta muy precisa. A partir de la relación entre la BER y la potencia requerida para diferentes constelaciones, los dos problemas duales se pueden resolver mediante un algoritmo tipo “Levin-Campello”, dado que los flujos de datos son independientes. Para facilitar el uso de este algoritmo, se mejoran las aproximaciones de la BER, obteniendo cómodas ecuaciones en forma compacta. En el capítulo V, se estima la probabilidad de error promedio para un receptor MMSE, también utilizando la distribución de la SINR, que ahora corresponde a una Gama o Gama generalizada. Se proponen y comparan varias expresiones en forma cerrada. En el capítulo VI, a partir de la relación entre la BER y la potencia requerida para diversas constelaciones, se resuelven los dos problemas duales mediante búsqueda exhaustiva, dado que en este caso los flujos de datos están acoplados debido a que el receptor MMSE no cancela la interferencia. Para reducir la carga computacional se añaden algunas restricciones. Para los dos problemas duales, el número total de bits que se pueden transmitir cuando el receptor es MMSE no puede ser menor que el correspondiente a un receptor ZF. Así pues, el punto de partida de la búsqueda es la solución para el receptor ZF y la búsqueda progresa desde ese punto hacia mayores tasas mientras lo permiten las restricciones. La probabilidad de error tras el receptor MMSE se puede aproximar a trav´es de la MGF (moment generating function) que incluye los tres primeros momentos de la SINR. Comparando dos antenas cualesquiera se demuestra que si hay que añadir un cierto incremento de bits en una de ellas, la antena con mejor canal es la que requiere menor incremento de potencia total para transmitirlo. Así, se puede concluir que los mejores canales deben llevar mayor número de bits y esto permite añadir una restricción adicional a la búsqueda, que conlleva, de este modo, una carga computacional razonable. En el capítulo VII, se obtiene una aproximación cerrada para la BER de un receptor ZF-SIC considerando la propagación de errores, a partir del teorema de la probabilidad total. Dado que el orden del proceso de decodificación tiene un impacto importante en las prestaciones del sistema con este receptor, se propone un precodificador que determina el orden que minimiza la potencia total. Por otra parte, se presentan unas cotas de las tasas binarias posibles con ZF-SIC, considerando las de ZF y ZF-PSIC (perfect SIC) para los dos problemas duales de optimización. Haciendo uso de estas cotas, se emplea una búsqueda en árbol para agilizar la convergencia

Interference Mitigation in Wireless Communications

The primary objective of this thesis is to design advanced interference resilient schemes for asynchronous slow frequency hopping wireless personal area networks (FH-WPAN) and time division multiple access (TDMA) cellular systems in interference dominant environments. We also propose an interference-resilient power allocation method for multiple-input-multiple-output (MIMO) systems. For asynchronous FH-WPANs in the presence of frequent packet collisions, we propose a single antenna interference canceling dual decision feedback (IC-DDF) receiver based on joint maximum likelihood (ML) detection and recursive least squares (RLS) channel estimation. For the system level performance evaluation, we propose a novel geometric method that combines bit error rate (BER) and the spatial distribution of the traffic load of CCI for the computation of packet error rate (PER). We also derived the probabilities of packet collision in multiple asynchronous FH-WPANs with uniform and nonuniform traffic patterns. For the design of TDMA receivers resilient to CCI in frequency selective channels, we propose a soft output joint detection interference rejection combining delayed decision feedback sequence estimation (JD IRC-DDFSE) scheme. In the proposed scheme, IRC suppresses the CCI, while DDFSE equalizes ISI with reduced complexity. Also, the soft outputs are generated from IRC-DDFSE decision metric to improve the performance of iterative or non-iterative type soft-input outer code decoders. For the design of interference resilient power allocation scheme in MIMO systems, we investigate an adaptive power allocation method using subset antenna transmission (SAT) techniques. Motivated by the observation of capacity imbalance among the multiple parallel sub-channels, the SAT method achieves high spectral efficiency by allocating power on a selected transmit antenna subset. For 4 x 4 V-BLAST MIMO systems, the proposed scheme with SAT showed analogous results. Adaptive modulation schemes combined with the proposed method increase the capacity gains. From a feasibility viewpoint, the proposed method is a practical solution to CCI-limited MIMO systems since it does not require the channel state information (CSI) of CCI.Ph.D.Committee Chair: Professor Gordon L. StBe

Bandwidth-efficient communication systems based on finite-length low density parity check codes

Low density parity check (LDPC) codes are linear block codes constructed by pseudo-random parity check matrices. These codes are powerful in terms of error performance and, especially, have low decoding complexity. While infinite-length LDPC codes approach the capacity of communication channels, finite-length LDPC codes also perform well, and simultaneously meet the delay requirement of many communication applications such as voice and backbone transmissions. Therefore, finite-length LDPC codes are attractive to employ in low-latency communication systems. This thesis mainly focuses on the bandwidth-efficient communication systems using finite-length LDPC codes. Such bandwidth-efficient systems are realized by mapping a group of LDPC coded bits to a symbol of a high-order signal constellation. Depending on the systems' infrastructure and knowledge of the channel state information (CSI), the signal constellations in different coded modulation systems can be two-dimensional multilevel/multiphase constellations or multi-dimensional space-time constellations. In the first part of the thesis, two basic bandwidth-efficient coded modulation systems, namely LDPC coded modulation and multilevel LDPC coded modulation, are investigated for both additive white Gaussian noise (AWGN) and frequency-flat Rayleigh fading channels. The bounds on the bit error rate (BER) performance are derived for these systems based on the maximum likelihood (ML) criterion. The derivation of these bounds relies on the union bounding and combinatoric techniques. In particular, for the LDPC coded modulation, the ML bound is computed from the Hamming distance spectrum of the LDPC code and the Euclidian distance profile of the two-dimensional constellation. For the multilevel LDPC coded modulation, the bound of each decoding stage is obtained for a generalized multilevel coded modulation, where more than one coded bit is considered for level. For both systems, the bounds are confirmed by the simulation results of ML decoding and/or the performance of the ordered-statistic decoding (OSD) and the sum-product decoding. It is demonstrated that these bounds can be efficiently used to evaluate the error performance and select appropriate parameters (such as the code rate, constellation and mapping) for the two communication systems.The second part of the thesis studies bandwidth-efficient LDPC coded systems that employ multiple transmit and multiple receive antennas, i.e., multiple-input multiple-output (MIMO) systems. Two scenarios of CSI availability considered are: (i) the CSI is unknown at both the transmitter and the receiver; (ii) the CSI is known at both the transmitter and the receiver. For the first scenario, LDPC coded unitary space-time modulation systems are most suitable and the ML performance bound is derived for these non-coherent systems. To derive the bound, the summation of chordal distances is obtained and used instead of the Euclidean distances. For the second case of CSI, adaptive LDPC coded MIMO modulation systems are studied, where three adaptive schemes with antenna beamforming and/or antenna selection are investigated and compared in terms of the bandwidth efficiency. For uncoded discrete-rate adaptive modulation, the computation of the bandwidth efficiency shows that the scheme with antenna selection at the transmitter and antenna combining at the receiver performs the best when the number of antennas is small. For adaptive LDPC coded MIMO modulation systems, an achievable threshold of the bandwidth efficiency is also computed from the ML bound of LDPC coded modulation derived in the first part

Engineering evaluations and studies. Volume 3: Exhibit C

High rate multiplexes asymmetry and jitter, data-dependent amplitude variations, and transition density are discussed

Design and implimentationof Multi-user MIMO precoding algorithms

The demand for high-speed communications required by cutting-edge applications has put a strain on the already saturated wireless spectrum. The incorporation of antenna arrays at both ends of the communication link has provided improved spectral efficiency and link reliability to the inherently complex wireless environment, thus allowing for the thriving of high data-rate applications without the cost of extra bandwidth consumption. As a consequence to this, multiple-input multiple-output (MIMO) systems have become the key technology for wideband communication standards both in single-user and multi-user setups. The main difficulty in single-user MIMO systems stems from the signal detection stage at the receiver, whereas multi-user downlink systems struggle with the challenge of enabling non-cooperative signal acquisition at the user terminals. In this respect, precoding techniques perform a pre-equalization stage at the base station so that the signal at each receiver can be interpreted independently and without the knowledge of the overall channel state. Vector precoding (VP) has been recently proposed for non-cooperative signal acquisition in the multi-user broadcast channel. The performance advantage with respect to the more straightforward linear precoding algorithms is the result of an added perturbation vector which enhances the properties of the precoded signal. Nevertheless, the computation of the perturbation signal entails a search for the closest point in an in nite lattice, which is known to be in the class of non-deterministic polynomial-time hard (NP-hard) problems. This thesis addresses the difficulties that stem from the perturbation process in VP systems from both theoretical and practical perspectives. On one hand, the asymptotic performance of VP is analyzed assuming optimal decoding. Since the perturbation process hinders the analytical assessment of the VP performance, lower and upper bounds on the expected data rate are reviewed and proposed. Based on these bounds, VP is compared to linear precoding with respect to the performance after a weighted sum rate optimization, the power resulting from a quality of service (QoS) formulation, and the performance when balancing the user rates. On the other hand, the intricacies of performing an efficient computation of the perturbation vector are analyzed. This study is focused on tree-search techniques that, by means of an strategic node pruning policy, reduce the complexity derived from an exhaustive search and yield a close-to-optimum performance. To that respect, three tree-search algorithms are proposed. The xed-sphere encoder (FSE) features a constant data path and a non-iterative architecture that enable the parallel processing of the set of vector hypotheses and thus, allow for high-data processing rates. The sequential best-node expansion (SBE) algorithm applies a distance control policy to reduce the amount of metric computations performed during the tree traversal. Finally, the low-complexity SBE (LC-SBE) aims at reducing the complexity and latency of the aforementioned algorithm by combining an approximate distance computation model and a novel approach of variable run-time constraints. Furthermore, the hardware implementation of non-recursive tree-search algorithms for the precoding scenario is also addressed in this thesis. More specifically, the hardware architecture design and resource occupation of the FSE and K-Best xed-complexity treesearch techniques are presented. The determination of the ordered sequence of complexvalued nodes, also known as the Schnorr-Euchner enumeration, is required in order to select the nodes to be evaluated during the tree traversal. With the aim of minimizing the hardware resource demand of such a computationally-expensive task, a novel non-sequential and lowcomplexity enumeration algorithm is presented, which enables the independent selection of the nodes within the ordered sequence. The incorporation of the proposed enumeration technique along with a fully-pipelined architecture of the FSE and K-Best approaches, allow for data processing throughputs of up to 5 Gbps in a 4x4 antenna setup.Aplikazio abangoardistek beharrezko duten abiadura handiko komunikazioen eskaerak presio handia ezarri du dagoeneko saturatuta dagoen haririk gabeko espektruan. Komunikazio loturaren bi muturretan antena array-en erabilerak eraginkortasun espektral eta dagarritasun handiagoez hornitu du berez konplexua den haririk gabeko ingurunea, modu honetan banda zabalera gehigarririk gabeko abiadura handiko aplikazioen garapena ahalbidetuz. Honen ondorioz, multiple-input multiple output (MIMO) sistemak banda zabaleko komunikazio estandarren funtsezko teknologia bihurtu dira, erabiltzaile bakarreko ezarpenetan hala nola erabiltzaile anitzeko inguruneetan. Erabiltzaile bakarreko MIMO sistemen zailtasun garrantzitsuena hartzailean ematen den seinalearen detekzio fasean datza. Erabiltzaile anitzeko sistemetan, aldiz, erronka nagusiena datu jasotze ez kooperatiboa bermatzea da. Prekodi kazio teknikek hartzaile bakoitzaren seinalea kanalaren egoera orokorraren ezagutzarik gabe eta modu independiente baten interpretatzea ahalbidetzen dute estazio nagusian seinalearen pre-ekualizazio fase bat inposatuz. Azken aldian, prekodi kazio bektoriala (VP, ingelesez vector precoding) proposatu da erabiltzaile anitzeko igorpen kanalean seinalearen eskuratze ez kooperatiboa ahalbidetzeko. Perturbazio seinale baten erabilerak, prekodi katutako seinalearen ezaugarriak hobetzeaz gain, errendimenduaren hobekuntza nabarmen bat lortzen du prekodi kazio linearreko teknikekiko. Hala ere, perturbazio seinalearen kalkuluak sare in nitu baten puntu hurbilenaren bilaketa suposatzen du. Problema honen ebazpenaren konplexutasuna denbora polinomialean ez deterministikoa dela jakina da. Doktoretza tesi honen helburu nagusia VP sistemetan perturbazio prozesuaren ondorioz ematen diren zailtasun teoriko eta praktikoei irtenbide egoki bat ematea da. Alde batetik, seinale/zarata ratio handiko ingurunetan VP sistemen errendimendua aztertzen da, beti ere deskodetze optimoa ematen dela suposatuz. Perturbazio prozesuak VP sistemen errendimenduaren azterketa analitikoa oztopatzen duenez, data transmisio tasaren hainbat goi eta behe borne proposatu eta berrikusi dira. Borne hauetan oinarrituz, VP eta prekodi kazio linealaren arteko errendimendu desberdintasuna neurtu da hainbat aplikazio ezberdinen eremuan. Konkretuki, kanalaren ahalmen ponderatua, zerbitzu kalitatearen formulazio baten ondorioz esleitzen den seinale potentzia eta erabiltzaileen datu transmisio tasa orekatzean lortzen den errendimenduaren azterketa burutu dira. Beste alde batetik, perturbazio bektorearen kalkulu eraginkorra lortzeko metodoak ere aztertu dira. Analisi hau zuhaitz-bilaketa tekniketan oinarritzen da, non egitura sinple baten bitartez errendimendu ia optimoa lortzen den. Ildo horretan, hiru zuhaitz-bilaketa algoritmo proposatu dira. Alde batetik, Fixed-sphere encoder-aren (FSE) konplexutasun konstateak eta arkitektura ez errekurtsiboak datu prozesaketa abiadura handiak lortzea ahalbidetzen dute. Sequential best-node expansion (SBE) delako algoritmo iteratiboak ordea, distantzia kontrol politika baten bitartez metrika kalkuluen kopurua murriztea lortzen du. Azkenik, low-complexity SBE (LC-SBE) algoritmoak SBE metodoaren latentzia eta konplexutasuna murriztea lortzen du ordezko distantzien kalkuluari eta exekuzio iraupenean ezarritako muga aldakorreko metodo berri bati esker. Honetaz gain, prekodi kazio sistementzako zuhaitz-bilaketa algoritmo ez errekurtsiboen hardware inplementazioa garatu da. Zehazki, konplexutasun nkoko FSE eta K-Best algoritmoen arkitektura diseinua eta hardware baliabideen erabilera landu dira. Balio konplexuko nodoen sekuentzia ordenatua, Schnorr-Euchner zerrendapena bezala ezagutua, funtsezkoa da zuhaitz bilaketan erabiliko diren nodoen aukeraketa egiteko. Prozesu honek beharrezkoak dituen hardware baliabideen eskaera murrizteko, konplexutasun bajuko algoritmo ez sekuentzial bat proposatzen da. Metodo honen bitartez, sekuentzia ordenatuko edozein nodoren aukeraketa independenteki egin ahal da. Proposatutako zerrendapen metodoa eta estruktura fully-pipeline baten bitartez, 5 Gbps-ko datu prozesaketa abiadura lortu daiteke FSE eta K-Best delako algoritmoen inplementazioan.La demanda de comunicaciones de alta velocidad requeridas por las aplicaciones más vanguardistas ha impuesto una presión sobre el actualmente saturado espectro inalámbrico. La incorporación de arrays de antenas en ambos extremos del enlace de comunicación ha proporcionado una mayor e ciencia espectral y abilidad al inherentemente complejo entorno inalámbrico, permitiendo así el desarrollo de aplicaciones de alta velocidad de transmisión sin un consumo adicional de ancho de banda. Consecuentemente, los sistemas multiple-input multiple output (MIMO) se han convertido en la tecnología clave para los estándares de comunicación de banda ancha, tanto en las con guraciones de usuario único como en los entornos multiusuario. La principal di cultad presente en los sistemas MIMO de usuario único reside en la etapa de detección de la señal en el extremo receptor, mientras que los sistemas multiusuario en el canal de bajada se enfrentan al reto de habilitar la adquisición de datos no cooperativa en los terminales receptores. A tal efecto, las técnicas de precodi cación realizan una etapa de pre-ecualización en la estación base de tal manera que la señal en cada receptor se pueda interpretar independientemente y sin el conocimiento del estado general del canal. La precodifi cación vectorial (VP, del inglés vector precoding) se ha propuesto recientemente para la adquisición no cooperativa de la señal en el canal de difusión multiusuario. La principal ventaja de la incorporación de un vector de perturbación es una considerable mejora en el rendimiento con respecto a los métodos de precodi cación lineales. Sin embargo, la adquisición de la señal de perturbación implica la búsqueda del punto más cercano en un reticulado in nito. Este problema se considera de complejidad no determinística en tiempo polinomial o NP-complejo. Esta tesis aborda las di cultades que se derivan del proceso de perturbación en sistemas VP desde una perspectiva tanto teórica como práctica. Por un lado, se analiza el rendimiento de VP asumiendo una decodi cación óptima en escenarios de alta relación señal a ruido. Debido a que el proceso de perturbación di culta la evaluación analítica del rendimiento de los sistemas de VP, se proponen y revisan diversas cotas superiores e inferiores en la tasa esperada de transmisión de estos sistemas. En base a estas cotas, se realiza una comparación de VP con respecto a la precodi cación lineal en el ámbito de la capacidad suma ponderada, la potencia resultante de una formulación de calidad de servicio y el rendimiento obtenido al equilibrar las tasas de transmisión de los usuarios. Por otro lado, se han propuesto nuevos procedimientos para un cómputo e ciente del vector de perturbación. Estos métodos se basan en técnicas de búsqueda en árbol que, por medio de diferentes políticas de podado, reducen la complejidad derivada de una búsqueda exhaustiva y obtienen un rendimiento cercano al óptimo. A este respecto, se proponen tres algoritmos de búsqueda en árbol. El xed-sphere encoder (FSE) cuenta con una complejidad constante y una arquitectura no iterativa, lo que permite el procesamiento paralelo de varios vectores candidatos, lo que a su vez deriva en grandes velocidades de procesamiento de datos. El algoritmo iterativo denominado sequential best-node expansion (SBE) aplica una política de control de distancias para reducir la cantidad de cómputo de métricas realizadas durante la búsqueda en árbol. Por último, el low-complexity SBE (LC-SBE) tiene por objetivo reducir la complejidad y latencia del algoritmo anterior mediante la combinación de un modelo de cálculo aproximado de distancias y una estrategia novedosa de restricción variable del tiempo de ejecución. Adicionalmente, se analiza la implementación en hardware de algoritmos de búsqueda en árbol no iterativos para los escenarios de precodi cación. Más especí camente, se presentan el diseño de la arquitectura y la ocupación de recursos de hardware de las técnicas de complejidad ja FSE y K-Best. La determinación de la secuencia ordenada de nodos de naturaleza compleja, también conocida como la enumeración de Schnorr-Euchner, es vital para seleccionar los nodos evaluados durante la búsqueda en árbol. Con la intención de reducir al mínimo la demanda de recursos de hardware de esta tarea de alta carga computacional, se presenta un novedoso algoritmo no secuencial de baja complejidad que permite la selección independiente de los nodos dentro de la secuencia ordenada. La incorporación de la técnica de enumeración no secuencial junto con la arquitectura fully-pipeline de los algoritmos FSE y K-Best, permite alcanzar velocidades de procesamiento de datos de hasta 5 Gbps para un sistema de 4 antenas receptoras