Técnicas de pré-codificação para sistemas multicelulares coordenados

Doutoramento em TelecomunicaçõesCoordenação Multicélula é um tópico de investigação em rápido crescimento e uma solução promissora para controlar a interferência entre células em sistemas celulares, melhorando a equidade do sistema e aumentando a sua capacidade. Esta tecnologia já está em estudo no LTEAdvanced sob o conceito de coordenação multiponto (COMP). Existem várias abordagens sobre coordenação multicélula, dependendo da quantidade e do tipo de informação partilhada pelas estações base, através da rede de suporte (backhaul network), e do local onde essa informação é processada, i.e., numa unidade de processamento central ou de uma forma distribuída em cada estação base. Nesta tese, são propostas técnicas de pré-codificação e alocação de potência considerando várias estratégias: centralizada, todo o processamento é feito na unidade de processamento central; semidistribuída, neste caso apenas parte do processamento é executado na unidade de processamento central, nomeadamente a potência alocada a cada utilizador servido por cada estação base; e distribuída em que o processamento é feito localmente em cada estação base. Os esquemas propostos são projectados em duas fases: primeiro são propostas soluções de pré-codificação para mitigar ou eliminar a interferência entre células, de seguida o sistema é melhorado através do desenvolvimento de vários esquemas de alocação de potência. São propostas três esquemas de alocação de potência centralizada condicionada a cada estação base e com diferentes relações entre desempenho e complexidade. São também derivados esquemas de alocação distribuídos, assumindo que um sistema multicelular pode ser visto como a sobreposição de vários sistemas com uma única célula. Com base neste conceito foi definido uma taxa de erro média virtual para cada um desses sistemas de célula única que compõem o sistema multicelular, permitindo assim projectar esquemas de alocação de potência completamente distribuídos. Todos os esquemas propostos foram avaliados em cenários realistas, bastante próximos dos considerados no LTE. Os resultados mostram que os esquemas propostos são eficientes a remover a interferência entre células e que o desempenho das técnicas de alocação de potência propostas é claramente superior ao caso de não alocação de potência. O desempenho dos sistemas completamente distribuídos é inferior aos baseados num processamento centralizado, mas em contrapartida podem ser usados em sistemas em que a rede de suporte não permita a troca de grandes quantidades de informação.Multicell coordination is a promising solution for cellular wireless systems to mitigate inter-cell interference, improving system fairness and increasing capacity and thus is already under study in LTE-A under the coordinated multipoint (CoMP) concept. There are several coordinated transmission approaches depending on the amount of information shared by the transmitters through the backhaul network and where the processing takes place i.e. in a central processing unit or in a distributed way on each base station. In this thesis, we propose joint precoding and power allocation techniques considering different strategies: Full-centralized, where all the processing takes place at the central unit; Semi-distributed, in this case only some process related with power allocation is done at the central unit; and Fulldistributed, where all the processing is done locally at each base station. The methods are designed in two phases: first the inter-cell interference is removed by applying a set of centralized or distributed precoding vectors; then the system is further optimized by centralized or distributed power allocation schemes. Three centralized power allocation algorithms with per-BS power constraint and different complexity tradeoffs are proposed. Also distributed power allocation schemes are proposed by considering the multicell system as superposition of single cell systems, where we define the average virtual bit error rate (BER) of interference-free single cell system, allowing us to compute the power allocation coefficients in a distributed manner at each BS. All proposed schemes are evaluated in realistic scenarios considering LTE specifications. The numerical evaluations show that the proposed schemes are efficient in removing inter-cell interference and improve system performance comparing to equal power allocation. Furthermore, fulldistributed schemes can be used when the amounts of information to be exchanged over the backhaul is restricted, although system performance is slightly degraded from semi-distributed and full-centralized schemes, but the complexity is considerably lower. Besides that for high degrees of freedom distributed schemes show similar behaviour to centralized ones

Physical Layer Techniques for High Frequency Wireline Broadband Systems

This thesis collects contributions to wireline and wireless communication systems with an emphasis on multiuser and multicarrier physical layer technology. To deliver increased capacity, modern wireline access systems such as G.fast extend the signal bandwidth up from tens to hundreds of MHz. This ambitious development revealed a number of unforeseen hurdles such as the impact of impedance changes in various forms. Impedance changes have a strong effect on the performance of multi-user crosstalk mitigation techniques such as vectoring. The first part of the thesis presents papers covering the identification of one of these problems, a model describing why it occurs and a method to mitigate its effects, improving line stability for G.fast systems.A second part of the thesis deals with the effects of temperature changes on wireline channels. When a vectored (MIMO) wireline system is initialized, channel estimates need to be obtained. This thesis presents contributions on the feasibility of re-using channel coefficients to speed up the vectoring startup procedures, even after the correct coefficients have changed, e.g., due to temperature changes. We also present extensive measurement results showing the effects of temperature changes on copper channels using a temperature chamber and British cables. The last part of the thesis presents three papers on the convergence of physical layer technologies, more specifically the deployment of OFDM-based radio systems using twisted pairs in different ways. In one proposed scenario, the idea of using the access copper lines to deploy small cells inside users' homes is explored. The feasibility of the concept, the design of radio-heads and a practical scheme for crosstalk mitigation are presented in three contributions

Analysis and Mitigation of Channel Non-Reciprocity in TDD MIMO Systems

The ever-growing demands for higher number of connected devices as well as higher data rates and more energy efficient wireless communications have necessitated the use of new technical solutions. One of the main enablers in this respect is Multiple-Input Multiple-Output (MIMO) systems in which transmitting and receiving sides are equipped with multiple antennas. Such systems need precise information of the MIMO radio channel available at the transmitter side to reach their full potential. Owing to the reciprocity of uplink and downlink channels in Time Division Duplexing (TDD) systems, Base Stations (BSs) may acquire the required channel state information for downlink transmission by processing the received uplink pilots. However, such reciprocity only applies to the physical propagation channels and does not take into consideration the so-called observable or effective uplink and downlink channels which also include the possible non-reciprocal behavior of the involved transceiver circuits and antenna systems. This thesis focuses on the channel non-reciprocity problem in TDD MIMO systems due to mismatches in Frequency Response (FR) and mutual coupling of transmitting and receiving chains of transceivers and associated antenna systems. The emphasis in the work and developments is placed on multi-user MIMO precoded downlink transmission. In this respect, the harmful impacts of channel non-reciprocity on the performance of such downlink transmission are analyzed. Additionally, non-reciprocity mitigation methods are developed seeking to reclaim TDD reciprocity and thus to avoid the involved performance degradations. Firstly, the focus is on the small-scale MIMO systems where BSs are equipped with relatively limited number of antennas, say in the order of 4 to 8. The provided analysis on Zero-Forcing (ZF) and eigen-based precoding schemes in single-cell scenario shows that both schemes experience considerable performance degradations in the presence of FR and mutual coupling mismatches. Whereas, in general, the system performance is more sensitive to i) non-reciprocity sources in the BS transceiver; and ii) mutual coupling mismatches. Then, assuming reasonably good antenna isolation, an Over-The-Air (OTA) pilot-based algorithm is proposed to efficiently mitigate the BS transceiver non-reciprocity. The numerical results indicate high accuracy in estimating the BS transceiver non- reciprocity parameters as well as considerable improvement in the performance of the system. In multi-cell scenario, both centralized and decentralized precoding approaches are covered while the focus is on the impacts of FR mismatches of UE transceivers. The how that there is severe degradation in the performance of decentralized precoding while centralized precoding is immune to such channel non-reciprocity impacts. Secondly, the so-called massive MIMO systems are considered in which the number of antennas in the BS side is increased with an order of magnitude or more. Based on the detailed developed signal models, closed-form analytical expressions are first provided for effective signal-to-interference-plus-noise ratios of both ZF and maximum ratio transmission precoding schemes. The analysis covers the joint impacts of channel non-reciprocity and imperfect uplink channel estimation and shows that while both precoding schemes suffer from channel non-reciprocity impacts, ZF is more sensitive to such non-idealities. Next, a concept and an algorithm are proposed, involving UE side measurements and processing, to be deployed in the UE side to efficiently estimate the level of BS transceiver non-reciprocity. This enables the UEs to inform the BS about the optimum time to perform channel non-reciprocity mitigation round and thus improves the spectral efficiency. Finally, in order to mitigate channel non-reciprocity in massive MIMO systems, an efficient iterative OTA pilot-based algorithm is proposed which estimates and mitigates transceiver non-reciprocity impacts in both BS and UE sides. Compared to the state-of-the-art methods, the simulation results indicate substantial improvements in system spectral efficiency when the proposed method is being used. Overall, the analyses provided in this thesis can be used as valuable tools to better understand practical TDD MIMO systems which can be very helpful in designing such systems. Furthermore, the channel non-reciprocity mitigation methods proposed in this thesis can be deployed in practical TDD MIMO syst channel reciprocity and thus significantly increase the spectral efficiency

Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays

Massive MIMO (multiple-input multiple-output) is no longer a "wild" or "promising" concept for future cellular networks - in 2018 it became a reality. Base stations (BSs) with 64 fully digital transceiver chains were commercially deployed in several countries, the key ingredients of Massive MIMO have made it into the 5G standard, the signal processing methods required to achieve unprecedented spectral efficiency have been developed, and the limitation due to pilot contamination has been resolved. Even the development of fully digital Massive MIMO arrays for mmWave frequencies - once viewed prohibitively complicated and costly - is well underway. In a few years, Massive MIMO with fully digital transceivers will be a mainstream feature at both sub-6 GHz and mmWave frequencies. In this paper, we explain how the first chapter of the Massive MIMO research saga has come to an end, while the story has just begun. The coming wide-scale deployment of BSs with massive antenna arrays opens the door to a brand new world where spatial processing capabilities are omnipresent. In addition to mobile broadband services, the antennas can be used for other communication applications, such as low-power machine-type or ultra-reliable communications, as well as non-communication applications such as radar, sensing and positioning. We outline five new Massive MIMO related research directions: Extremely large aperture arrays, Holographic Massive MIMO, Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin

Massive MIMO is a reality - What is next? Five promising research directions for antenna arrays

Massive MIMO (multiple-input multiple-output) is no longer a “wild” or “promising” concept for future cellular networks—in 2018 it became a reality. Base stations (BSs) with 64 fully digital transceiver chains were commercially deployed in several countries, the key ingredients of Massive MIMO have made it into the 5G standard, the signal processing methods required to achieve unprecedented spectral efficiency have been developed, and the limitation due to pilot contamination has been resolved. Even the development of fully digital Massive MIMO arrays for mmWave frequencies—once viewed prohibitively complicated and costly—is well underway. In a few years, Massive MIMO with fully digital transceivers will be a mainstream feature at both sub-6 GHz and mmWave frequencies. In this paper, we explain how the first chapter of the Massive MIMO research saga has come to an end, while the story has just begun. The coming wide-scale deployment of BSs with massive antenna arrays opens the door to a brand new world where spatial processing capabilities are omnipresent. In addition to mobile broadband services, the antennas can be used for other communication applications, such as low-power machine-type or ultra-reliable communications, as well as non-communication applications such as radar, sensing and positioning. We outline five new Massive MIMO related research directions: Extremely large aperture arrays, Holographic Massive MIMO, Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive MIMO

Array Architectures and Physical Layer Design for Millimeter-Wave Communications Beyond 5G

Ever increasing demands in mobile data rates have resulted in exploration of millimeter-wave (mmW) frequencies for the next generation (5G) wireless networks. Communications at mmW frequencies is presented with two keys challenges. Firstly, high propagation loss requires base stations (BSs) and user equipment (UEs) to use a large number of antennas and narrow beams to close the link with sufficient received signal power. Consequently, communications using narrow beams create a new challenge in channel estimation and link establishment based on fine angular probing. Current mmW system use analog phased arrays that can probe only one angle at the time which results in high latency during link establishment and channel tracking. It is desirable to design low latency beam training by exploring both physical layer designs and array architectures that could replace current 5G approaches and pave the way to the communications for frequency bands in higher mmW band and sub-THz region where larger antenna arrays and communications bandwidth can be exploited. To this end, we propose a novel signal processing techniques exploiting unique properties of mmW channel, and show both theoretically, in simulation and experiments its advantages over conventional approaches. Secondly, we explore different array architecture design and analyze their trade-offs between spectral efficiency and power consumption and area. For comprehensive comparison, we have developed a methodology for optimal design of system parameters for different array architecture candidates based on the spectral efficiency target, and use these parameters to estimate the array area and power consumption based on the circuits reported in the literature. We show that the hybrid analog and digital architectures have severe scalability concerns in radio frequency signal distribution with increased array size and spatial multiplexing levels, while the fully-digital array architectures have the best performance and power/area trade-offs.The developed approaches are based on a cross-disciplinary research that combines innovation in model based signal processing, machine learning, and radio hardware. This work is the first to apply compressive sensing (CS), a signal processing tool that exploits sparsity of mmW channel model, to accelerate beam training of mmW cellular system. The algorithm is designed to address practical issues including the requirement of cell discovery and synchronization that involves estimation of angular channel together with carrier frequency offset and timing offsets. We have analyzed the algorithm performance in the 5G compliant simulation and showed that an order of magnitude saving is achieved in initial access latency for the desired channel estimation accuracy. Moreover, we are the first to develop and implement a neural network assisted compressive beam alignment to deal with hardware impairments in mmW radios. We have used 60GHz mmW testbed to perform experiments and show that neural networks approach enhances alignment rate compared to CS. To further accelerate beam training, we proposed a novel frequency selective probing beams using the true-time-delay (TTD) analog array architecture. Our approach utilizes different subcarriers to scan different directions, and achieves a single-shot beam alignment, the fastest approach reported to date. Our comprehensive analysis of different array architectures and exploration of emerging architectures enabled us to develop an order of magnitude faster and energy efficient approaches for initial access and channel estimation in mmW systems

Beyond Massive MIMO : Trade-offs and Opportunities with Large Multi-Antenna Systems

After the commercial emergence of 5G, the research community is already putting its focus on proposing innovative solutions to enable the upcoming 6G. One important lesson put forth by 5G research was that scaling up the conventional multiple-input-multiple-output (MIMO) technology by increasing the number of antennas could be extremely beneficial for effectively multiplexing data streams in the spatial domain. This idea was embodied in massive MIMO, which constitutes one of the major technical advancements included in 5G. Consequently, 6G research efforts have been largely directed towards studying ways to further scale up wireless systems, as can be seen in some of the proposed 6G enabling technologies like large intelligent surface (LIS), cell-free massive MIMO, or even reconfigurable intelligent surface (RIS). This thesis studies the possibilities offered by some of these technologies, as well as the trade-offs that may naturally arise when scaling up such wireless systems.An important part of this thesis deals with decentralized solutions for base station (BS) technologies including a large number of antennas. Already in the initial massive MIMO prototypes, the increased number of BS antennas led to scalability issues due to the high interconnection bandwidths required to send the received signals---as well as the channel state information (CSI)---to a central processing unit (CPU) in charge of the data processing. These issues can only be exacerbated if we consider novel system proposals like LIS, where the number of BS antennas may be increased by an order of magnitude with respect to massive MIMO, or cell-free massive MIMO, where the BS antennas may be located far from each other. We provide a number of decentralized schemes to process the received data while restricting the information that has to be shared with a CPU. We also provide a framework to study architectures with an arbitrary level of decentralization, showing that there exists a direct trade-off between the interconnection bandwidth to a CPU and the complexity of the decentralized processing required for fixed user rates.Another part of this thesis studies RIS-based solutions to enhance the multiplexing performance of wireless communication systems. RIS constitutes one of the most attractive 6G enabling technologies since it provides a cost- and energy-efficient solution to improve the wireless propagation links by generating favorable reflections. We extend the concept of RIS by considering reconfigurable surfaces (RSs) with different processing capabilities, and we show how these surfaces may be employed for achieving perfect spatial multiplexing at reduced processing complexity in general multi-antenna communication settings. We also show that these surfaces can exploit the available degrees of freedom---e.g., due to excess of BS antennas---to embed their own data into the enhanced channel

Mixed-numerology for radio access network slicing

Network slicing is a sustainable solution to support the various service types in future networks. In general, network slicing is composed of core network slicing and radio access network (RAN) slicing. The former can be realized by allocating dedicated virtualized core network functionalities to specific slices. Similarly, RAN slicing includes the virtualization and allocation of the limited RAN resources. From the physical layer perspective, supporting RAN slicing implies the need of unique radio-frequency (RF) and baseband (BB) configurations, i.e., numerology, for each slice to fulfil its quality of service requirements. To support such a heterogeneous mixed-numerology (MN) system, the transceiver architecture and widely used signal processing algorithms in the traditional single-service system need to be significantly changed. A clear understanding of mixed-numerology signals multiplexing and isolation is of importance to enable spectrum and computation efficient RAN slicing. Meanwhile, an effective channel estimation is the guarantee of performing almost all receiver signal processing. Fundamental channel estimation investigations also constitute a crucial piece of MN study. This thesis aims to systematically investigate the OFDM-based MN wireless communication systems in terms of system modeling, channel equalization/ estimation, and power allocation. First, a comprehensive mixed-numerology framework with two numerologies is proposed and characterized by physical layer parameters. According to the BB and RF configurations imparities among numerologies, four scenarios are categorized and elaborated on the configuration relationships of different numerologies. System models considering the most generic scenario are established for both uplink and downlink transmissions. Two theorems are proposed as the basis of MN algorithms design, which generalize the original circular convolution property of the discrete Fourier transform. The proposed theorems verifies the feasibility of the one-tap channel equalization in MN systems. However, they also indicate that both BB and RF configuration differences result in inter-numerology-interference (INI). Besides, severe signal distortion may occur when the transmitter and receiver numerologies are different. Therefore, a pre-coding algorithm is designed by utilizing the theorems to compensate the system degradation resulting from the signal distortion. INI cancellation algorithms are proposed based on collaboration detection scheme and joint numerologies signal models for downlink and uplink, respectively. Numerical results shows that the proposed algorithms are able to significantly improve the system performance. Another objective of this thesis is to verify the effectiveness of the existing channel estimation algorithms and to develop new ones in the presence of MN. To achieve these goals, three channel estimation methods, i.e., least-square linear interpolation, least-square ‘sinc’ interpolation, and minimum mean square error ‘sinc’ interpolation are implemented and theoretically analyzed in both single-user and multi-user scenarios. The analysis reveals that the pilot signal to noise ratio, pilot distance, and position of pilot signals jointly affect the channel estimation. In particular, a signal distortion factor caused by the RF configuration difference is spotted to seriously affect the channel estimation performance, whose values are mainly decided by the degree of configuration mismatch. On the other hand, INI also degrades the channel estimation in the MN system. The existence of interference-free subcarriers is demonstrated based on the derived closed-form expression of the INI. Pilot design principles in terms of pilot signal placement are developed according to the analyses. Numerical results shows that minimum mean square error based channel estimation has the best performance and robustness to the configuration mismatch. In addition, the proposed pilot design principles could produce comparable channel estimation results with the legacy OFDM systems where no INI and signal distortion exist. The two problems associated with the MN system, i.e., signal distortion and INI, could negatively affect the power distribution of the received MN signals, and the system performance in terms of spectrum efficiency may be seriously degraded. Consequently, it becomes outstandingly important to introduce an efficient subcarrier-level power allocation scheme in such kinds of systems to counter the performance degradation caused by the configuration mismatch. As such, this thesis makes the attempt to extend the two-numerology model to contain ‘M’ different numerologies. Based on the model, closed-form expressions of desired signal, interference, and noise are derived. The derivation shows that interference generated from different numeroloies are linearly superimposed in the frequency domain. The distribution of signal-to-interference-plus-noiseratio (SINR) is analyzed theoretically. An iterative convex approximation power allocation algorithm is proposed by applying the derived SINR. Results show that the power allocation algorithm contributes to remarkable spectrum efficiency improvement compare to the other schemes, and an extra subband filtering process could bring about even higher performance. The work presented in this thesis provides guidance for multi-numerology system design in terms of parameter selection, and the frame structure and algorithms design. Moreover, it presents a solution as to how the radio access network slicing can be underpinned in the physical layer in a spectrum efficient way

Topological Interference Management With Transmitter Cooperation

Interference networks with no channel state information at the transmitter except for the knowledge of the connectivity graph have been recently studied under the topological interference management framework. In this paper, we consider a similar problem with topological knowledge but in a distributed broadcast channel setting, i.e., a network where transmitter cooperation is enabled. We show that the topological information can also be exploited in this case to strictly improve the degrees of freedom (DoF) as long as the network is not fully connected, which is a reasonable assumption in practice. Achievability schemes from graph theoretic and interference alignment perspectives are proposed. Together with outer bounds built upon generator sequence, the concept of compound channel settings, and the relation to index coding, we characterize the symmetric DoF for the so-called regular networks with constant number of interfering links, and identify the sufficient and/or necessary conditions for the arbitrary network topologies to achieve a certain amount of symmetric DoF