Symbol-Level Precoding Through the Lens of Zero Forcing and Vector Perturbation

Symbol-level precoding (SLP) has recently emerged as a new paradigm for physical-layer transmit precoding in multiuser multi-input-multi-output (MIMO) channels. It exploits the underlying symbol constellation structure, which the conventional paradigm of linear precoding does not, to enhance symbol-level performance such as symbol error probability (SEP). It also allows the precoder to take a more general form than linear precoding. This paper aims to better understand the relationships between SLP and linear precoding, subsequent design implications, and further connections beyond the existing SLP scope. Focused on the quadrature amplitude modulation (QAM) constellations, our study is built on a basic signal observation, namely, that SLP can be equivalently represented by a zero-forcing (ZF) linear precoding scheme augmented with some appropriately chosen symbol-dependent perturbation terms, and that some extended form of SLP is equivalent to a vector perturbation (VP) nonlinear precoding scheme augmented with the above-noted perturbation terms. We examine how insights arising from this perturbed ZF and VP interpretations can be leveraged to i) substantially simplify the optimization of certain SLP design criteria, namely, total or peak power minimization subject to SEP quality guarantees; and ii) draw connections with some existing SLP designs. We also touch on the analysis side by showing that, under the total power minimization criterion, the basic ZF scheme is a near-optimal SLP scheme when the QAM order is very high -- which gives a vital implication that SLP is more useful for lower-order QAM cases. Numerical results further indicate the merits and limitations of the different SLP designs derived from the perturbed ZF and VP interpretations

FPGA Acceleration for Computationally Efficient Symbol-Level Precoding in Multi-User Multi-Antenna Communication Systems

In this paper, we demonstrate an FPGA accelerated design of the computationally efficient Symbol-Level Precoding (SLP) for high-throughput communication systems. The SLP technique recalculates optimal beam-forming vectors by solving a non-negative least squares (NNLS) problem per every set of transmitted symbols. It exploits the advantages of constructive inter-user interference to minimize the total transmitted power and increase service availability. The benefits of using SLP come with a substantially increased computational load at a gateway. The FPGA design enables the SLP technique to perform in realtime operation mode and provide a high symbol throughput for multiple receive terminals. We define the SLP technique in a closed-form algorithmic expression and translate it to Hardware Description Language (HDL) and build an optimized HDL core for an FPGA. We evaluate the FPGA resource occupation, which is required for high throughput multiple-input-multiple-output (MIMO) systems with sizeable dimensions. We describe the algorithmic code, the I/O ports mapping and the functional behavior of the HDL core. We deploy the IP core to an actual FPGA unit and benchmark the energy efficiency performance of SLP. The synthetic tests demonstrate a fair energy efficiency improvement of the proposed closed-form algorithm, also compared to the best results obtained through MATLAB numerical simulations

SYMBOL LEVEL PRECODING TECHNIQUES FOR HARDWARE AND POWER EFFICIENT WIRELESS TRANSCEIVERS

Large-scale antennas are crucial for next generation wireless communication systems as they improve spectral efficiency, reliability and coverage compared to the traditional ones that are employing antenna arrays of few elements. However, the large number of antenna elements leads to a big increase in power consumption of conventional fully digital transceivers due to the one Radio Frequency (RF) chain / per antenna element requirement. The RF chains include a number of different components among which are the Digital-to-Analog Converters (DACs)/Analog-to-Digital Converters (ADCs) that their power consumption increases exponential with the resolution they support. Motivated by this, in this thesis, a number of different architectures are proposed with the view to reduce the power consumption and the hardware complexity of the transceiver. In order to optimize the transmission of data through them, corresponding symbol level precoding (SLP) techniques were developed for the proposed architectures. SLP is a technique that mitigates multi-user interference (MUI) by designing the transmitted signals using the Channel State Information and the information-bearing symbols. The cases of both frequency flat and frequency selective channels were considered. First, three different power efficient transmitter designs for transmission over frequency flat channels and their respective SLP schemes are considered. The considered systems tackle the high hardware complexity and power consumption of existing SLP techniques by reducing or completely eliminating fully digital RF chains. The precoding design is formulated as a constrained least squares problem and efficient algorithmic solutions are developed via the Coordinate Descent method. Next, the case of frequency selective channels is considered. To this end, Constant Envelope precoding in a Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing system (CE MIMO-OFDM) is considered. In CE MIMO-OFDM the transmitted signals for each antenna are designed to have constant amplitude regardless of the channel realization and the information symbols that must be conveyed to the users. This facilitates the use of power-efficient components, such as phase shifters and non-linear power amplifiers. The precoding problem is firstly formulated as a least-squares problem with a unit-modulus constraint and solved using an algorithm based on the coordinate descent (CCD) optimization framework and then, after reformulating the problem into an unconstrained non-linear least squares problem, a more computationally efficient solution using the Gauss-Newton algorithm is presented. Then, CE MIMO-OFDM is considered for a system with low resolution DACs. The precoding design problem is formulated as a mixed discrete- continuous least-squares optimization one which is NP-hard. An efficient low complexity solution is developed based also on the CCD optimization framework. Finally, a precoding scheme is presented for OFDM transmission in MIMO systems based on one-bit DACs and ADCs at the transmitter’s and the receiver’s end, respectively, as a way to reduce the total power consumption. The objective of the precoding design is to mitigate the effects of one-bit quantization and the problem is formulated and then is split into two NP hard least squares optimization problems. Algorithmic solutions are developed for the solution of the latter problems, based on the CCD framework

Symbol-Level Noise-Guessing Decoding with Antenna Sorting for URLLC Massive MIMO

Supporting ultra-reliable and low-latency communication (URLLC) is a challenge in current wireless systems. Channel codes that generate large codewords improve reliability but necessitate the use of interleavers, which introduce undesirable latency. Only short codewords can eliminate the requirement for interleaving and reduce decoding latency. This paper suggests a coding and decoding method which, when combined with the high spectral efficiency of spatial multiplexing, can provide URLLC over a fading channel. Random linear coding and high-order modulation are used to transmit information over a massive multiple-input multiple-output (mMIMO) channel, followed by zero-forcing detection and guessing random additive noise decoding (GRAND) at a receiver. A variant of GRAND, called symbol-level GRAND, originally proposed for single-antenna systems that employ high-order modulation schemes, is generalized to spatial multiplexing. The paper studies the impact of the orthogonality defect of the underlying mMIMO lattice on symbol-level GRAND, and proposes to leverage side-information that comes from the mMIMO channel-state information and relates to the reliability of each receive antenna. This induces an antenna sorting step, which further reduces decoding complexity by over 80\% when compared to bit-level GRAND

Trellis coding with Continuous Phase Modulation (CPM) for satellite-based land-mobile communications

This volume of the final report summarizes the results of our studies on the satellite-based mobile communications project. It includes: a detailed analysis, design, and simulations of trellis coded, full/partial response CPM signals with/without interleaving over various Rician fading channels; analysis and simulation of computational cutoff rates for coherent, noncoherent, and differential detection of CPM signals; optimization of the complete transmission system; analysis and simulation of power spectrum of the CPM signals; design and development of a class of Doppler frequency shift estimators; design and development of a symbol timing recovery circuit; and breadboard implementation of the transmission system. Studies prove the suitability of the CPM system for mobile communications

Clustering techniques for base station coordination in a wireless cellular system

A lo largo de este Proyecto Fin de Carrera, propondremos mejoras para futuros sistemas de comunicaciones móviles mediante un estudio detallado de la coordinación entre estaciones base en sistemas celulares basados en MIMO. Este proyecto se compone de dos partes fundamentales. Por un lado, nos centraremos en técnicas de procesado de señal para MIMO como filtrado y precodificación lineales en el dominio espacial. Partiendo de los últimos desarrollos en dicho ámbito, se han desarrollado precodificadores de mínimo error cuadrático medio que incluyen restricciones de máxima potencia transmitida por celda. Además, se ha propuesto un concepto novedoso consistente en la introducción de una nueva formulación que, además de minimizar el error cuadrático medio en el interior de cada agrupación de celdas (cluster ), trata de mantener la interferencia entre clusters en niveles suficientemente bajos. Durante la segunda parte, analizaremos el impacto que la agrupación de celdas en clusters, que define qué estaciones base pueden ser coordinadas entre sí , tiene en el rendimiento global del sistema. Se ha estudiado la aplicabilidad de técnicas de agrupamiento dentro del aprendizaje máquina, dando como resultado un conjunto de nuevos algoritmos que han sido desarrollados adaptando algoritmos de agrupamiento de propósito general ya existentes al problema de crear una partición del conjunto de celdas de acuerdo a las condiciones de propagación de señal existentes en el sistema en un determinado instante. Todas nuestras contribuciones se han verificado mediante la simulación de un sistema de comunicaciones móviles basado en modelos de propagación de señal del 3GPP para LTE. De acuerdo a los resultados obtenidos, las técnicas propuestas a lo largo de este proyecto proporcionan un aumento considerable de la media y la mediana de las tasas por usuario respecto a soluciones ya existentes. La idea de introducir la reducción de interferencia entre clusters en la formulación de los precodifiadores MMSE mejora dramáticamente el rendimiento en sistemas celulares MIMO al ser comparados con precodifiadores de Wiener tradicionales. Por otro lado, nuestros algoritmos de agrupamiento dinámico de estaciones base exhiben un notable aumento de las tasas por usuario a la vez que emplean clusters de menor tamaño con respecto a soluciones existentes basadas en particiones estáticas del conjunto de celdas en el sistema. _______________________________________________________________________________________________________________________________In this project, we attempt to provide enhancements for future mobile communications systems by carrying out a throughout study of base-station coordination in cellular MIMO systems. Our work can be divided in two main blocks. During the first part, we focus our attention on linear MIMO signal processing techniques such as linear spatial precoding and linear spatial ltering. Starting from the state-of-the-art in that area of knowledge, we have developed novel MMSE precoders which include per-cell power constraints and a new formulation which, apart from minimizing the intra-cluster MSE, tries to keep inter-cluster interference at low levels. In the second part, we focus on the study of the impact the particular mapping of cells to clusters in the cellular system has on the overall performance of the mobile communication radio access network. The applicability of existing clustering algorithms in the fi eld of machine learning has been studied, resulting in a set of novel algorithms that we developed by adapting existing general-purpose clustering solutions for the problem of dynamically partitioning a set of cells according to the instantaneous signal propagation conditions. All our contributions have been exhaustively tested by simulation of a cellular mobile communication system based on 3GPP signal propagation models for LTE. According to the results obtained, the techniques proposed along this project provide a remarkable increase of both the average and median user rates in the system with respect to previous existing solutions. The inter-cluster interference-awareness we introduced in the formulation of MMSE precoders dramatically increases the performance in cellular coordinated MIMO when comparing it with traditional Wiener precoders. On the other hand, our dynamic base-station clustering has been shown to signi catively enhance the user rates while using smaller clusters that existing solutions based on static partitions of the base-station deployment.Ingeniería de Telecomunicació

Cooperative Radio Communications for Green Smart Environments

The demand for mobile connectivity is continuously increasing, and by 2020 Mobile and Wireless Communications will serve not only very dense populations of mobile phones and nomadic computers, but also the expected multiplicity of devices and sensors located in machines, vehicles, health systems and city infrastructures. Future Mobile Networks are then faced with many new scenarios and use cases, which will load the networks with different data traffic patterns, in new or shared spectrum bands, creating new specific requirements. This book addresses both the techniques to model, analyse and optimise the radio links and transmission systems in such scenarios, together with the most advanced radio access, resource management and mobile networking technologies. This text summarises the work performed by more than 500 researchers from more than 120 institutions in Europe, America and Asia, from both academia and industries, within the framework of the COST IC1004 Action on "Cooperative Radio Communications for Green and Smart Environments". The book will have appeal to graduates and researchers in the Radio Communications area, and also to engineers working in the Wireless industry. Topics discussed in this book include: • Radio waves propagation phenomena in diverse urban, indoor, vehicular and body environments• Measurements, characterization, and modelling of radio channels beyond 4G networks• Key issues in Vehicle (V2X) communication• Wireless Body Area Networks, including specific Radio Channel Models for WBANs• Energy efficiency and resource management enhancements in Radio Access Networks• Definitions and models for the virtualised and cloud RAN architectures• Advances on feasible indoor localization and tracking techniques• Recent findings and innovations in antenna systems for communications• Physical Layer Network Coding for next generation wireless systems• Methods and techniques for MIMO Over the Air (OTA) testin

Cooperative Radio Communications for Green Smart Environments

The demand for mobile connectivity is continuously increasing, and by 2020 Mobile and Wireless Communications will serve not only very dense populations of mobile phones and nomadic computers, but also the expected multiplicity of devices and sensors located in machines, vehicles, health systems and city infrastructures. Future Mobile Networks are then faced with many new scenarios and use cases, which will load the networks with different data traffic patterns, in new or shared spectrum bands, creating new specific requirements. This book addresses both the techniques to model, analyse and optimise the radio links and transmission systems in such scenarios, together with the most advanced radio access, resource management and mobile networking technologies. This text summarises the work performed by more than 500 researchers from more than 120 institutions in Europe, America and Asia, from both academia and industries, within the framework of the COST IC1004 Action on "Cooperative Radio Communications for Green and Smart Environments". The book will have appeal to graduates and researchers in the Radio Communications area, and also to engineers working in the Wireless industry. Topics discussed in this book include: • Radio waves propagation phenomena in diverse urban, indoor, vehicular and body environments• Measurements, characterization, and modelling of radio channels beyond 4G networks• Key issues in Vehicle (V2X) communication• Wireless Body Area Networks, including specific Radio Channel Models for WBANs• Energy efficiency and resource management enhancements in Radio Access Networks• Definitions and models for the virtualised and cloud RAN architectures• Advances on feasible indoor localization and tracking techniques• Recent findings and innovations in antenna systems for communications• Physical Layer Network Coding for next generation wireless systems• Methods and techniques for MIMO Over the Air (OTA) testin