Rate compatible modulation for non-orthogonal multiple access

We propose a new Non-Orthogonal Multiple Access (NOMA) coding scheme based on the use of a Rate Compatible Modulation (RCM) encoder for each user. By properly designing the encoders and taking advantage of the additive nature of the Multiple Access Channel (MAC), the joint decoder from the inputs of all the users can be represented by a bipartite graph corresponding to a standard point-topoint RCM structure with certain constraints. Decoding is performed over this bipartite graph utilizing the sum-product algorithm. The proposed scheme allows the simultaneous transmission of a large number of uncorrelated users at high rates, while the decoding complexity is the same as that of standard point-to-point RCM schemes. When Rayleigh fast fading channels are considered, the BER vs SNR performance improves as the number of simultaneous users increases, as a result of the averaging effect

Power Allocation in Uplink NOMA-Aided Massive MIMO Systems

In the development of the fifth-generation (5G) as well as the vision for the future generations of wireless communications networks, massive multiple-input multiple-output (MIMO) technology has played an increasingly important role as a key enabler to meet the growing demand for very high data throughput. By equipping base stations (BSs) with hundreds to thousands antennas, the massive MIMO technology is capable of simultaneously serving multiple users in the same time-frequency resources with simple linear signal processing in both the downlink (DL) and uplink (UL) transmissions. Thanks to the asymptotically orthogonal property of users' wireless channels, the simple linear signal processing can effectively mitigate inter-user interference and noise while boosting the desired signal's gain, and hence achieves high data throughput. In order to realize this orthogonal property in a practical system, one critical requirement in the massive MIMO technology is to have the instantaneous channel state information (CSI), which is acquired via channel estimation with pilot signaling. Unfortunately, the connection capability of a conventional massive MIMO system is strictly limited by the time resource spent for channel estimation. Attempting to serve more users beyond the limit may result in a phenomenon known as pilot contamination, which causes correlated interference, lowers signal gain and hence, severely degrades the system's performance. A natural question is ``Is it at all possible to serve more users beyond the limit of a conventional massive MIMO system?''. The main contribution of this thesis is to provide a promising solution by integrating the concept of nonorthogonal multiple access (NOMA) into a massive MIMO system. The key concept of NOMA is based on assigning each unit of orthogonal radio resources, such as frequency carriers, time slots or spreading codes, to more than one user and utilize a non-linear signal processing technique like successive interference cancellation (SIC) or dirty paper coding (DPC) to mitigate inter-user interference. In a massive MIMO system, pilot sequences are also orthogonal resources, which can be allocated with the NOMA approach. By sharing a pilot sequence to more than one user and utilizing the SIC technique, a massive MIMO system can serve more users with a fixed amount of time spent for channel estimation. However, as a consequence of pilot reuse, correlated interference becomes the main challenge that limits the spectral efficiency (SE) of a massive MIMO-NOMA system. To address this issue, this thesis focuses on how to mitigate correlated interference when combining NOMA into a massive MIMO system in order to accommodate a higher number of wireless users. In the first part, we consider the problem of SIC in a single-cell massive MIMO system in order to serve twice the number of users with the aid of time-offset pilots. With the proposed time-offset pilots, users are divided into two groups and the uplink pilots from one group are transmitted simultaneously with the uplink data of the other group, which allows the system to accommodate more users for a given number of pilots. Successive interference cancellation is developed to ease the effect of pilot contamination and enhance data detection. In the second part, the work is extended to a cell-free network, where there is no cell boundary and a user can be served by multiple base stations. The chapter focuses on the NOMA approach for sharing pilot sequences among users. Unlike the conventional cell-free massive MIMO-NOMA systems in which the UL signals from different access points are equally combined over the backhaul network, we first develop an optimal backhaul combining (OBC) method to maximize the UL signal-to-interference-plus-noise ratio (SINR). It is shown that, by using OBC, the correlated interference can be effectively mitigated if the number of users assigned to each pilot sequence is less than or equal to the number of base stations. As a result, the cell-free massive MIMO-NOMA system with OBC can enjoy unlimited performance when the number of antennas at each BS tends to infinity. Finally, we investigate the impact of imperfect SIC to a NOMA cell-free massive MIMO system. Unlike the majority of existing research works on performance evaluation of NOMA, which assume perfect channel state information and perfect data detection for SIC, we take into account the effect of practical (hence imperfect) SIC. We show that the received signal at the backhaul network of a cell-free massive MIMO-NOMA system can be effectively treated as a signal received over an additive white Gaussian noised (AWGN) channel. As a result, a discrete joint distribution between the interfering signal and its detected version can be analytically found, from which an adaptive SIC scheme is proposed to improve performance of interference cancellation

Joint Communication and Positioning based on Channel Estimation

Mobile wireless communication systems have rapidly and globally become an integral part of everyday life and have brought forth the internet of things. With the evolution of mobile wireless communication systems, joint communication and positioning becomes increasingly important and enables a growing range of new applications. Humanity has already grown used to having access to multimedia data everywhere at every time and thereby employing all sorts of location-based services. Global navigation satellite systems can provide highly accurate positioning results whenever a line-of-sight path is available. Unfortunately, harsh physical environments are known to degrade the performance of existing systems. Therefore, ground-based systems can assist the existing position estimation gained by satellite systems. Determining positioning-relevant information from a unified signal structure designed for a ground-based joint communication and positioning system can either complement existing systems or substitute them. Such a system framework promises to enhance the existing systems by enabling a highly accurate and reliable positioning performance and increased coverage. Furthermore, the unified signal structure yields synergetic effects. In this thesis, I propose a channel estimation-based joint communication and positioning system that employs a virtual training matrix. This matrix consists of a relatively small training percentage, plus the detected communication data itself. Via a core semi- blind estimation approach, this iteratively includes the already detected data to accurately determine the positioning-relevant parameter, by mutually exchanging information between the communication part and the positioning part of the receiver. Synergy is created. I propose a generalized system framework, suitable to be used in conjunction with various communication system techniques. The most critical positioning-relevant parameter, the time-of-arrival, is part of a physical multipath parameter vector. Estimating the time-of-arrival, therefore, means solving a global, non-linear, multi-dimensional optimization problem. More precisely, it means solving the so-called inverse problem. I thoroughly assess various problem formulations and variations thereof, including several different measurements and estimation algorithms. A significant challenge, when it comes to solving the inverse problem to determine the positioning-relevant path parameters, is imposed by realistic multipath channels. Most parameter estimation algorithms have proven to perform well in moderate multipath environments. It is mathematically straightforward to optimize this performance in the sense that the number of observations has to exceed the number of parameters to be estimated. The typical parameter estimation problem, on the other hand, is based on channel estimates, and it assumes that so-called snapshot measurements are available. In the case of realistic channel models, however, the number of observations does not necessarily exceed the number of unknowns. In this thesis, I overcome this problem, proposing a method to reduce the problem dimensionality via joint model order selection and parameter estimation. Employing the approximated and estimated parameter covariance matrix inherently constrains the estimation problem’s model order selection to result in optimal parameter estimation performance and hence optimal positioning performance. To compare these results with the optimally achievable solution, I introduce a focused order-related lower bound in this thesis. Additionally, I use soft information as a weighting matrix to enhance the positioning algorithm positioning performance. For demonstrating the feasibility and the interplay of the proposed system components, I utilize a prototype system, based on multi-layer interleave division multiple access. This proposed system framework and the investigated techniques can be employed for multiple existing systems or build the basis for future joint communication and positioning systems. The assessed estimation algorithms are transferrable to all kinds of joint communication and positioning system designs. This thesis demonstrates their capability to, in principle, successfully cope with challenging estimation problems stemming from harsh physical environments

The Interplay between Computation and Communication

In this thesis, a comprehensive exploration into the integration of communication and learning within the massive Internet of Things (mIoT) is undertaken. Addressing one of the fundamental challenges of mIoT, where traditional channel estimation methods prove inefficient due to high device density and short packets; initially, a novel approach leveraging unsupervised machine learning for joint channel estimation and signal detection is proposed. This technique utilizes the Gaussian mixture model (GMM) clustering of received signals, thereby reducing the necessity for exhaustive channel estimation, decreasing the number of required pilot symbols, and enhancing symbol error rate (SER) performance. Building on this foundation, an innovative method is proposed that eliminates the need for pilot symbols entirely. By coupling GMM clustering with rotational invariant (RI) coding, the model maintains robust performance against the effects of channel rotation, thereby improving the efficiency of mIoT systems. This research delves further into integrating communication and learning in mIoT, specifically focusing on federated learning (FL) convergence under error-prone conditions. It carefully analyzes the impact of factors like block length, coding rate, and signal-to-noise ratio on FL's accuracy and convergence. A novel approach is proposed to address communication error challenges, where the base station (BS) uses memory to cache key parameters. Closing the thesis, an extensive simulation of a real-world mIoT system, integrating previously developed techniques, such as the innovative channel estimation method, RI coding, and the introduced FL model. It notably demonstrates that optimal learning outcomes can be achieved even without stringent communication reliability. Thus, this work not only achieves comparable or superior performance to traditional methods with fewer pilot symbols but also provides valuable insights for optimizing mIoT systems within the FL framework

Multiuser non coherent massive MIMO schemes based on DPSK for future communication systems

The explosive usage of rich multimedia content in wireless devices has overloaded the communication networks. Moreover, the fifth generation (5G) of wireless communications involves new requirements in the radio access network (RAN) which require higher network capacities and new capabilities such as ultra-reliable and low-latency communication (URLLC), vehicular communications or augmented reality. All this has encouraged a remarkable spectrum crisis in the RF bands. A need for searching alternative techniques with more spectral efficiency to accommodate the needs of future emerging wireless communications is emerging. In this context, massive MIMO (m-MIMO) systems have been proposed as a promising solution for providing a substantial increase in the network capacity, becoming one of the key enabling technologies for 5G and beyond. m-MIMO provides high spectral- and energy-efficiency thanks to the deployment of a large number of antennas at the BS. However, we have to take into account that the current communication technologies are based on coherent transmission techniques so far, which require the transmission of a huge amount of signaling. This drawback is escalating with the excessive available number of antennas in m-MIMO. Therefore, the differential encoding and non coherent (NC) detection are an alternative solution to circumvent the drawbacks of m-MIMO in coherent systems. This Ph.D. Thesis is focused on signal processing techniques for NC detection in conjunction with m-MIMO, proposing new constellation designs and NC detection algorithms, where the information is transmitted in the signal differential phase. First, we design new constellation schemes for an uplink multiuser NC m-MIMO system in Rayleigh fading channels. These designs allow us to separate the users' signals at the receiver thanks to a one-to-one correspondence between the constellation for each user and the received joint constellation. Two approaches are considered in terms of BER: each user achieves a different performance and, on the other hand, the same performance is provided for all users. We analyze the number of antennas needed for those designs and compare to the required number by other designs in the literature. It is shown that our designs based on DPSK require a lower number of antennas than that required by their counterpart schemes based on energy. In addition, we compare the performance to their coherent counterpart systems, resulting NC-m-MIMO based on DPSK capable of outperforming the coherent systems with the suitable designs. Second, in order to reduce the number of antennas required for a target performance we propose a multi-user bit interleaved coded modulation - iterative decoding (BICM-ID) scheme as channel coding for a NC-m-MIMO system based on DPSK. We propose a novel NC approach for calculating EXIT curves based on the number of antennas. Then using the EXIT chart we find the best channel coding scheme for our NC-m-MIMO proposal. We show that the number of users served by the BS can be increased with a 70% reduction in the number of antennas with respect to the case without channel coding. In particular, we show that with 100 antennas for error protection equal design for all users and a coding rate of 1/2 we achieve the minimum probability of error. Third, we consider that current scenarios such as backhaul wireless systems, rural or suburban environments, and even new device-to-device (D2D) communications or the communications in higher frequencies (millimeter and the emerging ones in terahertz frequencies) can have a predominant line-of-sight (LOS) component, modeled by Rician fading. For all these new possible scenarios in 5G, we analyze the behavior of the NC m-MIMO systems when we have a Rician fading. We present a new constellation design to overcome the problem of the LOS channel component, as well as an associated detection algorithm to separate each user in reception taking into account the characterization of the constellation. In addition, for contemplating a more realistic scenario, we propose grouping users which experience a Rayleigh fading with those with Rician fading, analyzing the SINR and the performance of such combination in a multi-user NC m-MIMO system based on M-DPSK. The adequate user grouping allows unifying the constellation for both groups of users and the detection algorithm, reducing the complexity of the receiver. Also, the number of users that may be multiplexed may be further increased thanks to the improved performance. In the fourth part of this Thesis, we analyse the performance of multi-user NC m- MIMO based on DPSK in real environments and practical channels defined for the current standards such as LTE, the future technologies such as 5G and even for communications in the terahertz band. For this purpose, we use a metric to model the time-varying characteristics of the practical channels. We employ again the EXIT charts tool for analyzing and designing iteratively decoded systems. This analysis allows us to obtain an estimate of the degradation of the system's performance imposed by realistic channels. Hence, we show that our proposed system is robust to temporal variations, thus it is more recommendable the employment of NC-m-MIMO-DPSK in the future communication standards such as 5G. In order to reduce he number of hardware resources required in terms of RF chains, facilitating its implementation in a real system, we propose incorporating differential spatial modulation (DSM). We present and analyze a novel multiuser scheme for NC-m-MIMO combined with DSM with which we can see that the number of antennas is not a affected by the incorporation of DSM, even we have an improvement on the performance with respect to the coherent case. Finally, we study the viability of multiplexing users by constellation schemes against classical multiplexing techniques such as time division multiple access (TDMA). In order to fully characterize the system performance we analyze the block error rate (BLER) and the throughput of a NC-m-MIMO system. The results show a significant advantage regarding the number of antennas for multiplexing in the constellation against TDMA. However, in some cases, the demodulation of multiple users in constellation could require an excessively large number of antennas compared to TDMA. Therefore, it is necessary to properly manage the tradeoff between throughout and the number of antennas, to reach an optimal operational point, as shown in this Thesis.El inmenso uso de contenido multimedia en los dispositivos inalámbricos ha sobrecargado las redes de comunicaciones. Además, la quinta generación (5G) de sistemas de comunicaciones demanda nuevos requisitos para la red de acceso radio, la cual requiere ofrecer capacidades de red mayores y nuevas funcionalidades como comunicaciones ultra fiables y con muy poca letancia (URLLC), comunicaciones vehiculares o aplicaciones como la realidad aumentada. Todo esto ha propiciado una crisis notable en el espectro electromagnético, lo que ha llevado a una necesidad por buscar técnicas alternativas con más eficiencia espectral para acomodar todos los requisitos de las tecnologías de comunicaciones emergentes y futuras. En este contexto, los sistemas multi antena masivos, conocidos como massive MIMO, m-MIMO, han sido propuestos como una solución prometedora que proporciona un incremento substancial de la capacidad de red, convirtiéndose en una de las tecnologías claves para el 5G. Los sistemas m-MIMO elevan enormemente el número de antenas en la estación base, lo que les permite ofrecer alta eficiencia espectral y energética. No obstante, tenemos que tener en cuenta que las actuales tecnologías de comunicaciones emplean técnicas coherentes, las cuales requieren de información del estado del canal y por ello la transmisión de una enorme cantidad de información de señalización. Este inconveniente se ve agravado en el caso del m-MIMO debido al enorme número de antenas. Por ello, la codificación diferencial y la detección no coherente (NC) son una solución alternativa para solventar el problema de m-MIMO en los sistemas coherentes. Esta Tesis se centra en las técnicas de procesado de señal para detección NC junto con m-MIMO, proponiendo nuevos esquemas de constelación y algoritmos de detección NC, donde la información sea transmitida en la diferencia de fase de la señal. Primero, diseñamos nuevas constelaciones para un sistema multi usuario NC en m- MIMO en enlace ascendente (uplink) en canales con desvanecimiento tipo Rayleigh. Estos diseños nos permiten separar las señales de los usuarios en el receptor gracias a la correspondencia unívoca entre la constelación de cada usuario individual y la constelación conjunta recibida en la estación base. Hemos considerado dos enfoques para el diseño en términos de probabilidad de error: cada usuario consigue un rendimiento distinto, mientras que por otro lado, todos los usuarios son capaces de recibir las mismas prestaciones de probabilidad de error. Analizamos el número de antenas necesario para estos diseños y comparamos con el número requerido por otros diseños propuestos en la literatura. Nuestro diseño basado en DPSK requiere un número menor de antenas comparado con los sistemas basados en detección de energía. También comparamos con su homólogo coherente, resultando que NC-m-MIMO basado en DPSK es capaz de superar a los sistemas coherentes con los diseños adecuados. En segundo lugar, para reducir el número de antenas requerido para un rendimiento dado, proponemos incluir un esquema de codificación de canal. Hemos optado por un esquema de modulación codificado por bit entrelazado y decodificación iterativa (BICMID). Hemos empleado la herramienta EXIT chart para el diseño de la codificación de canal, proponiendo un nuevo enfoque para calcular las curvas EXIT de forma NC y basadas en el número de antenas. Los resultados muestran que el número de usuarios servidos por la estación base puede ser incrementado reduciendo un 70% el número de antenas con respecto al caso sin codificación de canal. En particular, para un array de 100 antenas y un diseño que ofrezca iguales prestaciones a todos los usuarios, con un código de tasa 1=2, podemos conseguir la mínima probabilidad de error. En tercer lugar, consideramos escenarios donde el canal tenga una componente predominante de visión directa (LOS) con la estación base modelada mediante un desvanecimiento tipo Rician. Por ejemplo, sistemas inalámbricos de backhaul, entornos rurales o sub urbanos, comunicaciones entre dispositivos (D2D), también cuando nos movemos hacia frecuencias superiores como son en la banda de milimétricas o más recientemente, la banda de terahercios para buscar mayores anchos de banda. Todos estos escenarios están contemplados en el futuro 5G. Los diseños presentados para canales Rayleigh ya no son válidos debido a la componente LOS del canal, por ello presentamos un nuevo diseño de constelación que resuelve el problema de la componente LOS, así como una guía para diseñar nuevas constelaciones. También proponemos un algoritmo asociado al diseñno de la constelación para poder separar a los usuarios en recepción. Además, para contemplar un escenario más realista donde podamos encontrar tanto desvanecimiento Rayleigh como Rice, proponemos agrupar usuarios de ambos grupos, analizando su rendimiento y relación señal a interferencia en la combinación. El adecuado agrupamiento permite unificar el diseño de la constelación para ambos desvanecimientos y por tanto reducir la complejidad en el receptor. También, el número de usuarios multiplicados en la constelación podría ser incrementado, gracias a la mejora en el rendimiento. El cuarto módulo de esta tesis es dedicado a analizar el rendimiento de los diseños propuestos en presencia de canales reales, donde disponemos de variabilidad temporal y en frecuencia. Proponemos usar una métrica que modela las características de la variabilidad temporal y, usando de nuevo la herramienta EXIT, analizamos los sistemas decodificados iterativamente considerando ahora los parámetros prácticos del canal. Este análisis nos permite obtener una estimación de la degradación que sufre el rendimiento del sistema impuesto por canales reales. Los resultados muestran que los sistemas NC-m-MIMO basados en DPSK son muy robustos a la variabilidad temporal por lo que son recomendables para los nuevos escenarios propuestos por el 5G, donde el canal cambia rápidamente. Otra consideración para introducir los sistemas NC con m-MIMO es la problemática de necesitar muchas cadenas de radio frecuencia que llevarían a tamaños de dispositivos enormes. Para reducir este número se propone la modulación espacial. En esta Tesis, estudiamos su uso con los sistemas NC, proponiendo una solución de modulación espacial diferencial para esquemas con múltiples usuarios combinado con NC-m-MIMO. Finalmente, estudiamos la viabilidad de multiplexar usuarios en la constelación frente a usar técnicas clásicas de multiplexación como TDMA. Para caracterizar completamente el rendimiento del sistema, analizamos la tasa de error de bloque (BLER) y el throughput de un sistema NC-m-MIMO. Los resultados muestran una ventaja significativa en cuanto al número de antennas para multiplexar usuarios en la constelación frente al requerido por TDMA. No obstante, en algunos casos, la demodulación de múltiples usuarios en la constelación podría requerir un número de antennas excesivamente grande comparado con la multiplexación en el tiempo. Por ello, es necesario gestionar adecuadamente un balance entre el throughput y el número de antenas para alcanzar un punto operacional óptimo, como se muestra en esta Tesis.Programa Oficial de Doctorado en Multimedia y Comunicaciones por la Universidad Carlos III de Madrid y la Universidad Rey Juan CarlosPresidente: Ana Isabel Pérez Neira.- Secretario: Máximo Morales Céspedes.- Vocal: María del Carmen Aguayo Torre