Massive MIMO without CSI: When Non-Coherent Communication Meets Many Antennas

Under high-mobility scenarios, the traditional coherent demodulation schemes (CDS) have limited performance, because reference signals cannot effectively track the channel variations with an affordable overhead. As an alternative solution, non-coherent demodulation schemes (NCDS) based on differential modulation have been proposed. Even in the absence of reference signals, they are capable of outperforming the CDS with a reduced complexity. The literature on NCDS laid the theoretical foundations for simplified channel and signal models, often single-carrier and spatially uncorrelated flat-fading channels. This chapter explains the most recent results assuming orthogonal frequency division multiplexing (OFDM) signaling and realistic channel models

Analysis and Design of Algorithms for the Improvement of Non-coherent Massive MIMO based on DMPSK for beyond 5G systems

Mención Internacional en el título de doctorNowadays, it is nearly impossible to think of a service that does not rely on wireless communications. By the end of 2022, mobile internet represented a 60% of the total global online traffic. There is an increasing trend both in the number of subscribers and in the traffic handled by each subscriber. Larger data rates, smaller extreme-to-extreme (E2E) delays and greater number of devices are current interests for the development of mobile communications. Furthermore, it is foreseen that these demands should also be fulfilled in scenarios with stringent conditions, such as very fast varying wireless communications channels (either in time or frequency) or scenarios with power constraints, mainly found when the equipment is battery powered. Since most of the wireless communications techniques and standards rely on the fact that the wireless channel is somehow characterized or estimated to be pre or post-compensated in transmission (TX) or reception (RX), there is a clear problem when the channels vary rapidly or the available power is constrained. To estimate the wireless channel and obtain the so-called channel state information (CSI), some of the available resources (either in time, frequency or any other dimension), are utilized by including known signals in the TX and RX typically known as pilots, thus avoiding their use for data transmission. If the channels vary rapidly, they must be estimated many times, which results in a very low data efficiency of the communications link. Also, in case the power is limited or the wireless link distance is large, the resulting signal-tointerference- plus-noise ratio (SINR) will be low, which is a parameter that is directly related to the quality of the channel estimation and the performance of the data reception. This problem is aggravated in massive multiple-input multiple-output (massive MIMO), which is a promising technique for future wireless communications since it can increase the data rates, increase the reliability and cope with a larger number of simultaneous devices. In massive MIMO, the base station (BS) is typically equipped with a large number of antennas that are coordinated. In these scenarios, the channels must be estimated for each antenna (or at least for each user), and thus, the aforementioned problem of channel estimation aggravates. In this context, algorithms and techniques for massive MIMO without CSI are of interest. This thesis main topic is non-coherent massive multiple-input multiple-output (NC-mMIMO) which relies on the use of differential M-ary phase shift keying (DMPSK) and the spatial diversity of the antenna arrays to be able to detect the useful transmitted data without CSI knowledge. On the one hand, hybrid schemes that combine the coherent and non-coherent schemes allowing to get the best of both worlds are proposed. These schemes are based on distributing the resources between non-coherent (NC) and coherent data, utilizing the NC data to estimate the channel without using pilots and use the estimated channel for the coherent data. On the other hand, new constellations and user allocation strategies for the multi-user scenario of NC-mMIMO are proposed. The new constellations are better than the ones in the literature and obtained using artificial intelligence techniques, more concretely evolutionary computation.This work has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie ETN TeamUp5G, grant agreement No. 813391. The PhD student was the Early Stage Researcher (ESR) number 2 of the project. This work has also received funding from the Spanish National Project IRENE-EARTH (PID2020-115323RB-C33) (MINECO/AEI/FEDER, UE), which funded the work of some coauthors.Programa de Doctorado en Multimedia y Comunicaciones por la Universidad Carlos III de Madrid y la Universidad Rey Juan CarlosPresidente: Luis Castedo Ribas.- Secretario: Matilde Pilar Sánchez Fernández.- Vocal: Eva Lagunas Targaron

Design of terahertz transceiver schemes for ultrahigh-speed wireless communications

Future ultra-high-speed wireless communication systems face difficult challenges due to the fundamental limitations of current technologies operating at microwave frequencies. Supporting high transmission rates will require the use of more spectral resources that are only available at higher frequencies. Within this context, terahertz (THz) communications have been attracting more and more attention, being considered by the research community as one of the most promising research fields on the topic due to the availability of extensive unused bandwidth segments. However, its widespread use is not yet possible due to some obstacles, such as the high propagation losses that occur in this band and the difficulty in designing devices that can effectively perform both transmission and detection tasks. The purpose of this dissertation is to contribute for the solution of both of the aforementioned problems and to propose novel THz transceiver schemes for ultra-high-speed wireless communications. Three main research areas were addressed: device modelling for the THz; index modulation (IM) based schemes for Beyond 5G (B5G) networks and hybrid precoding designs for THz ultra massive (UM) – multiple input multiple output (MIMO) systems. The main contributions of this work include the creation of a new design for a reconfigurable THz filter; the proposal of a precoded generalized spatial modulation scheme for downlink MIMO transmissions in B5G networks; the creation of a low-complexity hybrid design algorithm with a near fully-digital performance for multiuser (MU) mmWave/THz ultra massive MIMO systems that can incorporate different analog architectures; and the system-level assessment of cloud radio access network (C-RAN) deployments based on low-complexity hybrid precoding designs for massive MIMO downlink transmissions in B5G networks. The first contribution is especially suited for the implementation of reconfigurable THz filters and optical modulators, since it is based on a simple design, which transits from situations in which it presents a full transparency to situations where it achieves full opacity. Moreover, this approach can also be used for the implementation of simultaneously transmitting and reflecting (STAR) reconfigurable intelligent surfaces (RIS) which are important for enabling flexible system designs in RIS-assisted networks. The second contribution showed that the implementation of precoding schemes based on generalised spatial modulations is a solution with a considerable potential for future B5G systems, since it can provide larger throughputs when compared to conventional MU-MIMO schemes with identical spectral efficiencies.The last two contributions showed that through the proposed hybrid design algorithm it becomes possible to replace a fully digital precoder/combiner by a fully-connected or even by a partially-connected architecture (array of subarrays and dynamic array of subarrays), while achieving good tradeoffs between spectral efficiency, power consumption and implementation complexity. These proposals are particularly relevant for the support of UM-MIMO in severely hardware constrained THz systems. Moreover, the capability of achieving significant improvements in terms of throughput performance and coverage over typical cellular networks, when considering hybrid precoding‐based C-RAN deployments in two indoor office scenarios at the THz band, was demonstrated.Os futuros sistemas de comunicação sem fios de velocidade ultra-elevada enfrentam desafios difíceis devido às limitações fundamentais das tecnologias atuais que funcionam a frequências de microondas. O suporte de taxas de transmissão altas exigirá a utilização de mais recursos espectrais que só estão disponíveis em frequências mais elevadas. A banda Terahertz (THz) é uma das soluções mais promissoras devido às suas enormes larguras de banda disponíveis no espectro eletromagnético. No entanto, a sua utilização generalizada ainda não é possível devido a alguns obstáculos, tais como as elevadas perdas de propagação que se verificam nesta banda e a dificuldade em conceber dispositivos que possam desempenhar eficazmente as tarefas de transmissão e deteção. O objetivo desta tese de doutoramento, é contribuir para ambos os problemas mencionados anteriormente e propor novos esquemas de transcetores THz para comunicações sem fios de velocidade ultra-elevada. Três grandes áreas de investigação foram endereçadas, contribuindo individualmente para um todo: a modelação do dispositivo para o THz; esquemas baseados em modulações de índice (IM) para redes pós-5G (B5G) e desenhos de pré-codificadores híbridos para sistemas THz MIMO ultra-massivos. As principais contribuições deste trabalho incluem a criação de um novo design para um filtro THz reconfigurável; a proposta de uma nova tipologia de modulação espacial generalizada pré-codificada para transmissões MIMO de ligação descendente para redes B5G; a criação de um algoritmo de design híbrido de baixa complexidade com desempenho quase totalmente digital para sistemas MIMO multi-utilizador (MU) mmWave/THz ultra massivos que podem incorporar diferentes arquiteturas analógicas e a avaliação das implementações da rede de acesso de rádio na nuvem (C-RAN) com base em designs de pré-codificação híbridos de baixa complexidade para transmissões MIMO de ligação descendente massivas em redes B5G. A primeira contribuição é especialmente adequada para a implementação de filtros THz reconfiguráveis e moduladores óticos, uma vez que se baseia numa concepção mais simples, que transita de situações em que apresenta uma transparência total para situações em que atinge uma opacidade total. Para além disso, esta abordagem também pode ser utilizada para a implementação de superfícies inteligentes reconfiguráveis (RIS) de transmissão e reflexão simultânea (STAR). A segunda contribuição mostrou que a implementação de esquemas de pré-codificação baseados em modulações espaciais generalizadas é uma solução com um potencial considerável para futuros sistemas B5G, uma vez que permite alcançar maiores ganhos em termos de débito binário quando comparado com esquemas convencionais MU-MIMO com eficiências espectrais idênticas. As duas últimas contribuições mostraram que através do algoritmo proposto torna-se possível substituir a utilização de uma arquitectura totalmente digital por uma arquitetura totalmente conectada ou mesmo por uma arquitetura parcialmente conectada (arrays de subarrays e arrays dinâmicos de subarrays), conseguindo-se bons tradeoffs entre eficiência espectral, consumo de energia e complexidade de implementação. Estas propostas são particularmente relevantes para dar suporte a sistemas THz UM-MIMO com restrições severas ao nível de hardware. Demonstrou-se também a capacidade de se alcançar melhorias significativas em termos de débito binário e cobertura em relação a redes celulares típicas, considerando dois cenários na banda THz

Advanced optimization algorithms for sensor arrays and multi-antenna communications

Optimization problems arise frequently in sensor array and multi-channel signal processing applications. Often, optimization needs to be performed subject to a matrix constraint. In particular, unitary matrices play a crucial role in communications and sensor array signal processing. They are involved in almost all modern multi-antenna transceiver techniques, as well as sensor array applications in biomedicine, machine learning and vision, astronomy and radars. In this thesis, algorithms for optimization under unitary matrix constraint stemming from Riemannian geometry are developed. Steepest descent (SD) and conjugate gradient (CG) algorithms operating on the Lie group of unitary matrices are derived. They have the ability to find the optimal solution in a numerically efficient manner and satisfy the constraint accurately. Novel line search methods specially tailored for this type of optimization are also introduced. The proposed approaches exploit the geometrical properties of the constraint space in order to reduce the computational complexity. Array and multi-channel signal processing techniques are key technologies in wireless communication systems. High capacity and link reliability may be achieved by using multiple transmit and receive antennas. Combining multi-antenna techniques with multicarrier transmission leads to high the spectral efficiency and helps to cope with severe multipath propagation. The problem of channel equalization in MIMO-OFDM systems is also addressed in this thesis. A blind algorithm that optimizes of a combined criterion in order to be cancel both inter-symbol and co-channel interference is proposed. The algorithm local converge properties are established as well

A comparative study of STBC transmissions at 2.4 GHz over indoor channels using a 2 × 2 MIMO testbed

In this paper we employ a 2×2 Multiple-Input Multiple-Output (MIMO) hardware platform to evaluate, in realistic indoor scenarios, the performance of different space-time block coded (STBC) transmissions at 2.4GHz. In particular, we focus on the Alamouti orthogonal scheme considering two types of channel state information (CSI) estimation: a conventional pilot-aided supervised technique and a recently proposed blind method based on second-order statistics (SOS). For comparison purposes, we also evaluate the performance of a Differential (non-coherent) space-time block coding (DSTBC). DSTBC schemes have the advantage of not requiring CSI estimation but they incur in a 3dB loss in performance. The hardware MIMO platform is based on high-performance signal acquisition and generation boards, each one equipped with a 1GB memory module that allows the transmission of extremely large data frames. Upconversion to RF is performed by two RF vector signal generators whereas downconversion is carried out with two custom circuits designed from commercial components. All the baseband signal processing is implemented off-line in MATLAB®, making the MIMO testbed very flexible and easily reconfigurable. Using this platform we compare the performance of the described methods in line-of-sight (LOS) and non-line-of-sight (NLOS) indoor scenarios.This work has been supported by Ministerio de Educación y Ciencia of Spain, Xunta de Galicia and FEDER funds of the European Union under grant numbers TEC2004-06451-C05-02, TEC2004-06451-C05-01, PGIDT05PXIC10502PN, and FPU grants AP2004-5127 and AP2006-2965

Superimposed RIS-phase Modulation for MIMO Communications: A Novel Paradigm of Information Transfer

Reconfigurable intelligent surface (RIS) is regarded as an important enabling technology for the sixth-generation (6G) network. Recently, modulating information in reflection patterns of RIS, referred to as reflection modulation (RM), has been proven in theory to have the potential of achieving higher transmission rate than existing passive beamforming (PBF) schemes of RIS. To fully unlock this potential of RM, we propose a novel superimposed RIS-phase modulation (SRPM) scheme for multiple-input multiple-output (MIMO) systems, where tunable phase offsets are superimposed onto predetermined RIS phases to bear extra information messages. The proposed SRPM establishes a universal framework for RM, which retrieves various existing RM-based schemes as special cases. Moreover, the advantages and applicability of the SRPM in practice is also validated in theory by analytical characterization of its performance in terms of average bit error rate (ABER) and ergodic capacity. To maximize the performance gain, we formulate a general precoding optimization at the base station (BS) for a single-stream case with uncorrelated channels and obtain the optimal SRPM design via the semidefinite relaxation (SDR) technique. Furthermore, to avoid extremely high complexity in maximum likelihood (ML) detection for the SRPM, we propose a sphere decoding (SD)-based layered detection method with near-ML performance and much lower complexity. Numerical results demonstrate the effectiveness of SRPM, precoding optimization, and detection design. It is verified that the proposed SRPM achieves a higher diversity order than that of existing RM-based schemes and outperforms PBF significantly especially when the transmitter is equipped with limited radio-frequency (RF) chains.Comment: Submitted to IEEE for possible publicatio