Near far resistant detection for CDMA personal communication systems.

The growth of Personal Communications, the keyword of the 90s, has already the signs of a technological revolution. The foundations of this revolution are currently set through the standardization of the Universal Mobile Telecommunication System (UMTS), a communication system with synergistic terrestrial and satellite segments. The main characteristic of the UMTS radio interface, is the provision of ISDN services. Services with higher than voice data rates require more spectrum, thus techniques that utilize spectrum as efficiently as possible are currently at the forefront of the research community interests. Two of the most spectrally efficient multiple access technologies, namely. Code Division Multiple Access (CDMA) and Time Division Multiple Access (TDMA) concentrate the efforts of the European telecommunity.This thesis addresses problems and. proposes solutions for CDMA systems that must comply with the UMTS requirements. Prompted by Viterbi's call for further extending the potential of CDMA through signal processing at the receiving end, we propose new Minimum Mean Square Error receiver architectures. MMSE detection schemes offer significant advantages compared to the conventional correlation based receivers as they are NEar FAr Resistant (NEFAR) over a wide range of interfering power levels. The NEFAR characteristic of these detectors reduces considerably the requirements of the power control loops currently found in commercial CDMA systems. MMSE detectors are also found, to have significant performance gains over other well established interference cancellation techniques like the decorrelating detector, especially in heavily loaded system conditions. The implementation architecture of MMSE receivers can be either Multiple-Input Multiple Output (MIMO) or Single-Input Single-Output. The later offers not only complexity that is comparable to the conventional detector, but also has the inherent advantage of employing adaptive algorithms which can be used to provide both the dispreading and the interference cancellation function, without the knowledge of the codes of interfering users. Furthermore, in multipath fading channels, adaptive MMSE detectors can exploit the multipath diversity acting as RAKE combiners. The later ability is distinctive to MMSE based receivers, and it is achieved in an autonomous fashion, without the knowledge of the multipath intensity profile. The communicator achieves its performance objectives by the synergy of the signal processor and the channel decoder. According to the propositions of this thesis, the form of the signal processor needs to be changed, in order to exploit the horizons of spread spectrum signaling. However, maximum likelihood channel decoding algorithms need not change. It is the way that these algorithms are utilized that needs to be revis ed. In this respect, we identify three major utilization scenarios and an attempt is made to quantify which of the three best matches the requirements of a UMTS oriented CDMA radio interface. Based on our findings, channel coding can be used as a mapping technique from the information bit to a more ''intelligent" chip, matching the ''intelligence" of the signal processor

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

MIMO Systems

In recent years, it was realized that the MIMO communication systems seems to be inevitable in accelerated evolution of high data rates applications due to their potential to dramatically increase the spectral efficiency and simultaneously sending individual information to the corresponding users in wireless systems. This book, intends to provide highlights of the current research topics in the field of MIMO system, to offer a snapshot of the recent advances and major issues faced today by the researchers in the MIMO related areas. The book is written by specialists working in universities and research centers all over the world to cover the fundamental principles and main advanced topics on high data rates wireless communications systems over MIMO channels. Moreover, the book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

Novel Efficient Precoding Techniques for Multiuser MIMO Systems

In Multiuser MIMO (MU-MIMO) systems, precoding is essential to eliminate or minimize the multiuser interference (MUI). However, the design of a suitable precoding algorithm with good overall performance and low computational complexity at the same time is quite challenging, especially with the increase of system dimensions. In this thesis, we explore the art of novel low-complexity high-performance precoding algorithms with both linear and non-linear processing strategies. Block diagonalization (BD)-type based precoding techniques are well-known linear precoding strategies for MU-MIMO systems. By employing BD-type precoding algorithms at the transmit side, the MU-MIMO broadcast channel is decomposed into multiple independent parallel SU-MIMO channels and achieves the maximum diversity order at high data rates. The main computational complexity of BD-type precoding algorithms comes from two singular value decomposition (SVD) operations, which depend on the number of users and the dimensions of each user's channel matrix. In this thesis, two categories of low-complexity precoding algorithms are proposed to reduce the computational complexity and improve the performance of BD-type precoding algorithms. One is based on multiple LQ decompositions and lattice reductions. The other one is based on a channel inversion technique, QR decompositions, and lattice reductions to decouple the MU-MIMO channel into equivalent SU-MIMO channels. Both of the two proposed precoding algorithms can achieve a comparable sum-rate performance as BD-type precoding algorithms, substantial bit error rate (BER) performance gains, and a simplified receiver structure, while requiring a much lower complexity. Tomlinson-Harashima precoding (THP) is a prominent nonlinear processing technique employed at the transmit side and is a dual to the successive interference cancelation (SIC) detection at the receive side. Like SIC detection, the performance of THP strongly depends on the ordering of the precoded symbols. The optimal ordering algorithm, however, is impractical for MU-MIMO systems with multiple receive antennas. We propose a multi-branch THP (MB-THP) scheme and algorithms that employ multiple transmit processing and ordering strategies along with a selection scheme to mitigate interference in MU-MIMO systems. Two types of multi-branch THP (MB-THP) structures are proposed. The first one employs a decentralized strategy with diagonal weighted filters at the receivers of the users and the second uses a diagonal weighted filter at the transmitter. The MB-MMSE-THP algorithms are also derived based on an extended system model with the aid of an LQ decomposition, which is much simpler compared to the conventional MMSE-THP algorithms. Simulation results show that a better BER performance can be achieved by the proposed MB-MMSE-THP precoder with a small computational complexity increase