Joint precoding and antenna selection in massive mimo systems

This thesis presents an overview of massive multiple-input multiple-output (MIMO) systems and proposes new algorithms to jointly precode and select the antennas. Massive MIMO is a new technology, which is candidate for comprising the fifth-generation (5G) of mobile cellular systems. This technology employs a huge amount of antennas at the base station and can reach high data rates under favorable, or asymptotically favorable, propagation conditions, while using simple linear processing. However, massive MIMO systems have some drawbacks, such as the high cost related to the base stations. A way to deal with this issue is to employ antenna selection algorithms at the base stations. These algorithms reduce the number of active antennas, decreasing the deployment and maintenance costs related to the base stations. Moreover, this thesis also describes a class of nonlinear precoders that are rarely addressed in the literature; these techniques are able to generate precoded sparse signals in order to achieve joint precoding and antenna selection. This thesis proposes two precoders belonging to this class, where the number of selected antennas is controlled by a design parameter. Simulation results show that the proposed precoders reach a lower bit-error rate than the classical antenna selection algorithms. Furthermore, simulation results show that the proposed precoders present a linear relation between the aforementioned design parameter that controls the signals’ sparsity and the number of selected antennas. Such relation is invariant to the number of base station’s antennas and the number of terminals served by this base station.Esta dissertação apresenta uma visão geral sobre MIMO (do termo em inglês, multiple-input multiple-output) massivo e propõe novos algoritmos que permitem a pré-codificacão de sinais e a seleção de antenas de forma simultânea. MIMO massivo é uma nova tecnologia candidata para compor a quinta geração (5G) dos sistemas celulares. Essa tecnologia utiliza uma quantidade muito grande de antenas na estação-base e, sob condições de propagação favorável ou assintoticamente favorável, pode alcançar taxas de transmissão elevadas, ainda que utilizando um simples processamento linear. Entretanto, os sistemas MIMO massivo apresentam algumas desvantagens, como por exemplo, o alto custo de implementação das estações-bases. Uma maneira de lidar com esse problema é utilizar algoritmos de seleção de antenas na estação-base. Com esses algoritmos é possível reduzir o número de antenas ativas e consequentemente reduzir o custo nas estações-bases. Essa dissertação também apresenta uma classe pouco estudada de pré-codificadores não-lineares que buscam sinais pré-codificados esparsos para realizar a seleção de antenas conjuntamente com a pré-codificação. Além disso, este trabalho propõem dois novos pré-codificadores pertencentes a essa classe, para os quais o número de antenas selecionadas é controlado por um parâmetro de projeto. Resultados de simulações mostram que os pré-codificadores propostos conseguem uma BER (do termo em inglês, bit-error rate) menor que os algoritmos clássicos usados para selecionar antenas. Além disso, resultados de simulações mostram que os pré-codificadores propostos apresentam uma relação linear com o parâmetro de projeto que controla a quantidade de antenas selecionadas; tal relação independe do número de antenas na estação-base e do número de terminais servidos por essa estação

Mathematical optimization and signal processing techniques for cooperative wireless networks

The rapid growth of mobile users and emergence of high data rate multimedia and interactive services have resulted in a shortage of the radio spectrum. Novel solutions are therefore required for future generations of wireless networks to enhance capacity and coverage. This thesis aims at addressing this issue through the design and analysis of signal processing algorithms. In particular various resource allocation and spatial diversity techniques have been proposed within the context of wireless peer-to-peer relays and coordinated base station (BS) processing. In order to enhance coverage while providing improvement in capacity, peer-to-peer relays that share the same frequency band have been considered and various techniques for designing relay coefficients and allocating powers optimally are proposed. Both one-way and two-way amplify and forward (AF) relays have been investigated. In order to maintain fairness, a signal-to-interference plus noise ratio (SINR) balancing criterion has been adopted. In order to improve the spectrum utilization further, the relays within the context of cognitive radio network are also considered. In this case, a cognitive peer-to-peer relay network is required to achieve SINR balancing while maintaining the interference leakage to primary receiver below a certain threshold. As the spatial diversity techniques in the form of multiple-input-multipleoutput (MIMO) systems have the potential to enhance capacity significantly, the above work has been extended to peer-to-peer MIMO relay networks. Transceiver and relay beamforming design based on minimum mean-square error (MSE) criterion has been proposed. Establishing uplink downlink MSE duality, an alternating algorithm has been developed. A scenario where multiple users are served by both the BS and a MIMO relay is considered and a joint beamforming technique for the BS and the MIMO relay is proposed. With the motivation of optimising the transmission power at both the BS and the relay, an interference precoding design is presented that takes into account the knowledge of the interference caused by the relay to the users served by the BS. Recognizing joint beamformer design for multiple BSs has the ability to reduce interference in the network significantly, cooperative multi-cell beamforming design is proposed. The aim is to design multi-cell beamformers to maximize the minimum SINR of users subject to individual BS power constraints. In contrast to all works available in the literature that aimed at balancing SINR of all users in all cells to the same level, the SINRs of users in each cell is balanced and maximized at different values. This new technique takes advantage of the fact that BSs may have different available transmission powers and/or channel conditions for their users

Quality of service optimization in the Broadcast Channel with Imperfect transmit channel state information

[Resumen]Este trabajo considera un sistema Broadcast Channel (BC) que consiste en un transmisor equipado con múltiples antenas y varios usuarios con una o más antenas. Dependiendo del número de antenas en el lado receptor, tales sistemas son conocidos como Multiple-User Multiple-Input Single-Output (MU-MISO), para usuarios con una única antena, o Multiple-User Multiple-Input Multiple-Output (MU-MIMO), para usuarios con varias antenas. Este modelo es adecuado para sistemas actuales de comunicaciones inalámbricas. Respecto a la dirección del flujo de datos, diferenciamos entre el canal downlink o BC, y canal uplink o Multiple Access Channel (MAC). En el BC las señales se envían desde la estación base a los usuarios, mientras que la información perteneciente a los usuarios es transmitida a la estación base en el MAC. En este trabajo nos centramos en el BC donde la estación base aplica precodificación lineal aprovechando las múltiples antenas. La información sobre el estado del canal se asume perfecta en todos los usuarios. Sin embargo, los usuarios no cooperan, y la estación base solo tiene información de canal parcial obtenida a través de un canal de realimentación en los sistemas Frequency-Division Duplex (FDD), que tiene un ancho de banda limitado. Esta limitación fuerza a los usuarios a aplicar algunos métodos, como quantización, para reducir la cantidad de datos a enviar a la estación base. La combinación de la información proporcionada por los usuarios es interpretada en la estación base como información de canal estocástica, y constituye un factor crítico en el diseño de los precodificadores. En la literatura se han considerado varios métodos para evaluar el rendimiento del BC, a saber, Signal to Interference-plus-Noise Ratio (SINR), Minimum Mean Square Error (MMSE), y tasa. Algunos trabajos calculan las medidas correspondientes para cada usuario mientras que otros consideran la suma de todos ellos como la métrica de interés. En nuestro caso, nos centramos en la tasa como figura de mérito. En particular, estamos interesados en garantizar ciertas tasas por usuario. De esta manera, evitamos situaciones injustas que surgen de utilizar la tasa suma como criterio, en las que a los usuarios con canales pobres se les asignan tasas bajas, o incluso cero. Además, reducir la cantidad de potencia necesaria para satisfacer las restricciones de calidad de servicio mencionadas es una característica deseable en los sistemas de comunicaciones inalámbricas. Así, abordamos el problema de optimización consistente en minimizar la potencia total en el transmisor empleada para cumplir un conjunto de restricciones de calidad de servicio, expresadas como tasas por usuario. Durante los últimos años el problema de minimización de potencia ha sido estudiado ampliamente para información tanto perfecta como imperfecta de canal, en los escenarios BC. Asumir conocimiento de canal perfecto es poco realista y, por tanto, consideramos que los usuarios env´ıan la información de canal a la estación base por medio de un canal de realimentación, normalmente disponible en los est´andares de comunicación recientes. Aunque algunos autores han empleado modelos de incertidumbre limitada para el conocimiento de canal tales como rectangular, elipsoidal, o esférico, y han aprovechado esa asunción para resolver el problema de minimización de potencia, no asumimos una forma particular para esa incertidumbre sino un modelo de error estocástico. En el modelo de sistema considerado, MU-MIMO, el número de antenas en la estación base es mayor que el número de antenas en cada usuario, e.g. MU-MISO. Además, los usuarios no cooperan para separar las señales recibidas. Debido a ésto y a la falta de grados de libertad en los usuarios, es necesario el uso de filtros transmisores, también llamados precodificadores, para eliminar las interferencias entre usuarios. De este modo, en este trabajo diseñamos conjuntamente los precodificadores lineales y los filtros receptores minimizando la potencia total en el transmisor sujeta a restricciones de tasa por usuario. Esta formulación del problema no es convexa y, por tanto, es complicada de manejar. Por este motivo, aplicamos la desigualdad de Jensen a las restricciones de tasa para obtener otras basadas en el MMSE. Como consecuencia, nuestro objetivo es diseñar los precodificadores y filtros que minimizan el MMSE para todos los usuarios. Para ello, distintos tipos de dualidades basadas en SINR,Mean Square Error (MSE), o tasa, han sido empleadas para el diseño de los filtros como fórmulas para intercambiar entre el BC y el MAC por conveniencia. En particular, empleamos la dualidad de MSE con conocimiento de canal imperfecto. Además, para la distribución de potencias, explotamos el marco teórico de las standard Interference Function, planteado para resolver el algoritmo de control de potencia. De esta manera, proponemos un algoritmo para solucionar el problema de minimización de potencia en el BC. Para comprobar la factibilidad de las restricciones de calidad de servicio, proponemos un test que permite determinar si el algoritmo converge o no. Además, el algoritmo propuesto permite resolver el problema dual, ésto es, encontrar los objetivos de tasa balanceados correspondientes a una potencia total en el transmisor. Finalmente, algunas aplicaciones de la minimización de potencia surgen de diferentes escenarios y se resuelven por medio del algoritmo propuesto. Usando el lenguaje de programación MATLAB se simulan experimentos con el objetivo de mostrar el rendimiento de los métodos propuestos.[Resumo]Este traballo considera un sistema Broadcast Channel (BC) que consiste nun transmisor equipado con múltiples antenas e varios usuarios cunha ou máis antenas. Dependendo do número de antenas no lado receptor, tales sistemas son coñecidos como Multiple-User Multiple-Input Single-Output (MU-MISO), para usuarios cunha única antena, ou Multiple-User Multiple-Input Multiple-Output (MU-MIMO), para usuarios con varias antenas. Este modelo é adecuado para sistemas actuais de comunicacións sen fíos. Respecto á dirección do fluxo de datos, diferenciamos entre a canle downlink ou BC, e a canle uplink ou Multiple Access Channel (MAC). No BC os sinais env´ıanse dende a estación base aos usuarios, mentres que a información pertencente aos usuarios é transmitida á estación base no MAC. Neste traballo centrámonos no BC onde a estación base aplica precodificación lineal aproveitando as múltiples antenas. A información sobre o estado da canle asúmese perfecta en todos os usuarios. Por contra, os usuarios non cooperan e a estación base só ten información da canle parcial obtida a través dunha canle de realimentación nos sistemas Frequency-Division Duplex (FDD), que ten un ancho de banda limitado. Esta limitación forza aos usuarios a aplicar algúns métodos, como quantización, para reducir a cantidade de datos que se envían á estación base. A combinación da información proporcionada polos usuarios é interpretada na estación base como información da canle estocástica, e constitúe un factor crítico no deseño dos precodificadores. Na literatura consider´aronse varios métodos para avaliar o rendemento do BC, a saber, Signal to Interference-plus-Noise Ratio (SINR), Minimum Mean Square Error (MMSE), e taxa. Algúns traballos calculan as medidas correspondentes para cada usuario mentres que outros consideran a suma de todos eles como a métrica de interese. No noso caso, centrámonos na taxa como figura de mérito. En particular, estamos interesados en garantir certas taxas por usuario. Deste xeito evitamos situación inxustas que xurdan de utilizar a taxa suma como criterio, nas que aos usuarios con canles pobres se lles asignan tasas baixas, ou incluso cero. Ademais, reducir a cantidade de potencia necesaria para satisfacer as restricci ´ons de calidade de servizo mencionadas ´e unha característica desexable nos sistemas de comunicacións se fíos. Así, acometemos o problema de optimización consistente en minimizar a potencia total no transmisor empregada para cumprir un conxunto de restricións de calidade de servizo, expresadas como taxas por usuario. Durante os últimos anos o problema de minimización de potencia foi estudado amplamente para información tanto perfecta como imperfecta de canle, nos escenarios BC. Asumir coñecemento perfecto de canle é pouco realista e, por tanto, consideramos que os usuarios envían a información de canle á estación base por medio dunha canle de realimentación, normalmente dispoñible nos estándares de comunicación recentes. Aínda que algúns autores empregaron modelos de incerteza limitada para o coñecemento de canle tales como rectangular, elipsoidal, ou esférico, e aproveitaron esa asunción para solucionar o problema de minimización de potencia, non asumimos unha forma particular para esa incerteza sen´on un modelo de error estocástico. No modelo de sistema considerado, MU-MIMO, o número de antenas na estación base é maior que o número de antenas en cada usuario, e.g. MU-MISO. Ademais, os usuarios non cooperan para separar os sinais recibidos. Debido a isto e á falta de graos de liberdade nos usuarios, é preciso o uso de filtros transmisores, tamén chamados precodificadores, para eliminar as interferencias entre usuarios. Deste xeito, neste traballo deseñamos conxuntamente os precodificadores lineais e os filtros receptores minimizando a potencia total no transmisor suxeita a restriccións de taxa por usuario. Esta formulación do problema non é convexa e, por tanto, é complicada de manexar. Por este motivo, aplicamos a desigualdade de Jensen ´as restriccións de taxa para obter outras baseadas no MMSE. Como consecuencia, o noso obxectivo é deseñar os precodificadores e filtros que minimizan o MMSE para todos os usuarios. Para iso, distintos tipos de dualidades baseadas en SINR, Mean Square Error (MSE), ou taxa, foron empregadas para o deseño dos filtros coma fórmulas para intercambiar entre o BC e o MAC por conveniencia. En particular, empregamos a dualidade de MSE con coñecemento de canal imperfecto. Ademais, para a distribución de potencias, explotamos o marco teórico das standard Interference Function, formulado para resolver o algoritmo de control de potencia. Desta maneira, propomos un algoritmo para resolver o problema de minimización de potencia no BC. Para comprobar a factibilidade das restricci óns de calidade de servizo, propomos un test que permite determinar se o algoritmo converxe ou non. Ademais, o algoritmo proposto permite resolver o problema dual, ´ısto é, atopar os obxectivos de taxa balanceados correspondentes a unha potencia total no transmisor. Finalmente, algunhas aplicacións da minimización de potencia xorden de diferentes escenarios e resólvense por medio do algoritmo proposto. Usando a linguaxe de programación MATLAB simúlanse experimentos co obxectivo de mostrar o rendemento dos métodos propostos.[Abstract]This work considers a Broadcast Channel (BC) system, where the transmitter is equipped with multiple antennas and each user at the receiver side could have one or more antennas. Depending on the number of antennas at the receiver side, such a system is known as Multiple-User Multiple-Input Single-Output (MU-MISO), for single antenna users, orMultiple-UserMultiple-InputMultiple-Output (MU-MIMO), for several antenna users. This model is suitable for current wireless communication systems. Regarding the direction of the data flow, we differentiate between downlink channel or BC, and uplink channel or Multiple Access Channel (MAC). In the BC the signals are sent from the Base Station (BS) to the users, whereas the information from the users is sent to the BS in the MAC. In this work we focus on the BC where the BS applies linear precoding taking advantage of multiple antennas. The Channel State Information (CSI) is assumed to be perfectly known at each user. However, the users do not cooperate, and the BS only has partial CSI obtained via a feedback link in Frequency-Division Duplex (FDD) systems, which is bandwidth limited. This limitation forces the users to apply some methods, like quantization, to reduce the amount of data to be sent to the BS. The combination of the information provided by the users is interpreted as stochastic CSI at the BS, so that the partial CSI is critical for the design of the precoders. Several criteria have been considered to evaluate the BC performance in the literature, namely, Signal to Interference-plus-Noise Ratio (SINR), Minimum Mean Square Error (MMSE), and rate. While some works compute the corresponding metric for each of the users, others consider the sum of all of them as the value of interest. In our case, we concentrate on rate as figure of merit. In particular, we are interested in guarantying certain per-user rates. That way, we avoid unfair situations of the sum rate criterion arising when the channels for some of the users are poor with assigned low, even zero, rates. Moreover, reducing the amount of power required to fulfill the mentioned Qualityof- Service (QoS) restrictions is a desirable feature for a wireless communication system. Thus, we address the optimization problem consisting on minimizing the total transmit power employed at the BS to fulfill a set of given QoS constraints, expressed as per-user rates. The power minimization problem has been widely studied during the last years for both perfect and imperfect CSI at the BS scenarios. The assumption of perfect CSI is rather unrealistic so that, as we mentioned previously, we consider that the users send the channel information to the BS by means of the feedback channel, usually available in recent wireless communication standards. Although some authors have employed XIV bounded uncertainty models for the CSI such as rectangular, ellipsoidal, or spherical, and have taken advantage of that assumption to solve the power minimization problem, we do not assume a particular shape for that uncertainty, but is modeled as a stochastic error. In the considered MU-MIMO system model the number of antennas at the BS is larger than the number of antennas at each user, e.g. MU-MISO. Moreover, the users do not cooperate to separate the received signals. Due to that and to the lack of degrees of freedom at the users, it makes necessary the use of transmit filters, also denoted as precoders, to remove inter-user interference. Thus, in this work we jointly design the linear precoders and receive filters minimizing the total transmit power subject to per-user rate constraints. This problem formulation is non-convex. As a consequence, it is difficult to deal with. For such a reason, we apply the Jensen’s inequality to the rate constraints to obtain a MMSE based restrictions. Consequently, our aim is to find the precoders and the filters that minimize the MMSE for all the users. To that end, several types of dualities based on SINR, Mean Square Error (MSE), or rate have been employed for the design of the filters as conversion formulas that allow to switch between the BC and the MAC for convenience. We employ the MSE BC/MAC duality for imperfect Channel State Information at the Transmitter (CSIT). Furthermore, for the power allocation design, we take advantage of the standard Interference Function (IF) framework, proposed to solve the power control algorithm. In such a way, an algorithm is proposed to solve the power minimization problem in the BC. To check the feasibility of the QoS constraints, we propose a test that allows to determine the convergence of the algorithm. Additionally, the proposed algorithm can be employed to solve the dual problem, i.e., find the balanced targets for given total transmit power. Finally, some applications of the power minimization problem arising from different scenarios are studied and solved by means of the proposed algorithm. Simulation experiments are carried out using the technical programming language MATLAB in order to show the performance of the proposed methods

D 3. 3 Final performance results and consolidated view on the most promising multi -node/multi -antenna transmission technologies

This document provides the most recent updates on the technical contributions and research challenges focused in WP3. Each Technology Component (TeC) has been evaluated under possible uniform assessment framework of WP3 which is based on the simulation guidelines of WP6. The performance assessment is supported by the simulation results which are in their mature and stable state. An update on the Most Promising Technology Approaches (MPTAs) and their associated TeCs is the main focus of this document. Based on the input of all the TeCs in WP3, a consolidated view of WP3 on the role of multinode/multi-antenna transmission technologies in 5G systems has also been provided. This consolidated view is further supported in this document by the presentation of the impact of MPTAs on METIS scenarios and the addressed METIS goals.Aziz, D.; Baracca, P.; De Carvalho, E.; Fantini, R.; Rajatheva, N.; Popovski, P.; Sørensen, JH.... (2015). D 3. 3 Final performance results and consolidated view on the most promising multi -node/multi -antenna transmission technologies. http://hdl.handle.net/10251/7675

Hardware-Conscious Wireless Communication System Design

The work at hand is a selection of topics in efficient wireless communication system design, with topics logically divided into two groups.One group can be described as hardware designs conscious of their possibilities and limitations. In other words, it is about hardware that chooses its configuration and properties depending on the performance that needs to be delivered and the influence of external factors, with the goal of keeping the energy consumption as low as possible. Design parameters that trade off power with complexity are identified for analog, mixed signal and digital circuits, and implications of these tradeoffs are analyzed in detail. An analog front end and an LDPC channel decoder that adapt their parameters to the environment (e.g. fluctuating power level due to fading) are proposed, and it is analyzed how much power/energy these environment-adaptive structures save compared to non-adaptive designs made for the worst-case scenario. Additionally, the impact of ADC bit resolution on the energy efficiency of a massive MIMO system is examined in detail, with the goal of finding bit resolutions that maximize the energy efficiency under various system setups.In another group of themes, one can recognize systems where the system architect was conscious of fundamental limitations stemming from hardware.Put in another way, in these designs there is no attempt of tweaking or tuning the hardware. On the contrary, system design is performed so as to work around an existing and unchangeable hardware limitation. As a workaround for the problematic centralized topology, a massive MIMO base station based on the daisy chain topology is proposed and a method for signal processing tailored to the daisy chain setup is designed. In another example, a large group of cooperating relays is split into several smaller groups, each cooperatively performing relaying independently of the others. As cooperation consumes resources (such as bandwidth), splitting the system into smaller, independent cooperative parts helps save resources and is again an example of a workaround for an inherent limitation.From the analyses performed in this thesis, promising observations about hardware consciousness can be made. Adapting the structure of a hardware block to the environment can bring massive savings in energy, and simple workarounds prove to perform almost as good as the inherently limited designs, but with the limitation being successfully bypassed. As a general observation, it can be concluded that hardware consciousness pays off

Power efficient designs for 5G wireless networks

In this dissertation, to step forward towards green communication, we study power efficient solutions in three potential 5G wireless networks, namely an asynchronous multicarrier two-way Amplify-and-Forward (AF) relay network, a multi-carrier two-way Filter-and-Forward (FF) network, and a massive Multiple Input Multiple Output (MIMO) network using the Non-Orthogonal Multiple Access (NOMA) scheme. In the first network, two transceivers using the Orthogonal Frequency Division Multiplexing (OFDM) scheme communicate through multiple relays in an asynchronous manner. As an attempt to design a simple solution, we assume the AF protocol at the relays. We jointly design the power allocation and distributed beamforming coefficients to minimize the total transmission power subject to sum-rate constraints. We propose an optimal semi-closed form solution to this problem and we show that at the optimum, the end-to-end channel has only one non-zero tap. To extend the first work to high data-rate scenarios, we consider a second relaying-based network which consists of two OFDM-based transceivers and multiple FF relays. We propose two approaches to tackle a total transmission power minimization problem: a gradient steepest descent-based technique, and a low-complexity method enforcing a frequency-flat Channel Impulse Response (CIR) response at the optimum. As the last network, we consider a massive MIMO-NOMA network with both co-located and distributed structures. We study the joint problem of power allocation and user clustering to minimize the total transmit power subject to QoS constraints. We propose a novel clustering algorithm which groups the correlated users into the same cluster and has an unique ability to automatically switch between using the spatial-domain-MIMO and the power-domain-NOMA. We show that our proposed method can substantially improve the feasibility probability and power consumption performance compared to existing methods

On the feasibility and applications of in-band full-duplex radios for future wireless networks

Due to the continuous increase of the demands for the wireless network’s capacity, in-band full-duplex (IBFD) has recently become a key research topic due to its potential to double spectral efficiency, reduce latency, enhance emerging applications, etc., by transmitting and receiving simultaneously over the same channel. Meanwhile, many studies in the literature experimentally demonstrated the feasibility of IBFD radios, which leads to the belief that it is possible to introduce IBFD in the standard of the next-generation networks. Therefore, in this thesis, we timely study the feasibility of IBFD and investigate its advantages for emerging applications in future networks. In the first part, we investigate the interference suppression methods to maximize the IBFD gain by minimizing the effects of self-interference (SI) and co-channel interference (CCI). To this end, we first study a 3-step self-interference cancellation (SIC) scheme. We focus on the time domain-based analog canceller and nonlinear digital canceller, explaining their rationale, demonstrating their effectiveness, and finding the optimal design by minimizing the residual effects. To break the limitation of conventional electrical radio frequency (RF) cancellers, we study the photonic-assisted canceller (PAC) and propose a new design, namely a fiber array-based canceller. We propose a new low-complexity tuning algorithm for the PAC. The effectiveness of the proposed fiber array canceller is demonstrated via simulations. Furthermore, we construct a prototype of the fiber array canceller with two taps and carry out experiments in real-world environments. Results show that the 3-step cancellation scheme can bring the SI close to the receiver's noise floor. Then, we consider the multiple-input multiple-output (MIMO) scenarios, proposing to employ hybrid RF-digital beamforming to reduce the implementation cost and studying its effects on the SIC design. Additionally, we propose a user allocation algorithm to reduce the CCI from the physical layer. A heterogeneous industrial Internet of Things (IIoT) scenario is considered, while the proposed algorithm can be generalized by modifying the parameters to fit any other network. In the second part, we study the beamforming schemes for IBFD multi-cell multi-user (IBFD-MCMU) networks. The transceiver hardware impairments (HWIs) and channel uncertainty are considered for robustness. We first enhance zero-forcing (ZF) and maximum ratio transmission and combining (MRTC) beamforming to be compatible with IBFD-MCMU networks in the presence of multi-antenna users. Then, we study beamforming for SIC, which is challenging for MCMU networks due to the limited antennas but complex interference. We propose a minimum mean-squared error (MMSE)-based scheme to enhance the SIC performance while minimizing its effects on the sum rate. Furthermore, we investigate a robust joint power allocation and beamforming (JPABF) scheme, which approaches the performance of existing optimal designs with reduced complexity. Their performance is evaluated and compared through 3GPP-based simulations. In the third part, we investigate the advantages of applying IBFD radios for physical layer security (PLS). We focus on a channel frequency response (CFR)-based secret key generation (SKG) scheme in MIMO systems. We formulate the intrinsic imperfections of IBFD radios (e.g., SIC overheads and noise due to imperfect SIC) and derive their effects on the probing errors. Then we derive closed-form expressions for the secret key capacity (SKC) of the SKG scheme in the presence of a passive eavesdropper. We analyze the asymptotic behavior of the SKC in the high-SNR regime and reveal the fundamental limits for IBFD and half-duplex (HD) radios. Based on the asymptotic SKC, numerical results illustrate that effective analog self-interference cancellation (ASIC) is the basis for IBFD to gain benefits over HD. Additionally, we investigate essential processing for the CFR-based SKG scheme and verify its effectiveness via simulations and the National Institute of Standards and Technology (NIST) test. In the fourth part, we consider a typical application of IBFD radios: integrated sensing and communication (ISAC). To provide reliable services in high-mobility scenarios, we introduce orthogonal time frequency space (OTFS) modulation and develop a novel framework for OTFS-ISAC. We give the channel representation in different domains and reveal the limitations and disadvantages of existing ISAC frameworks for OTFS waveforms and propose a novel radar sensing method, including a conventional MUSIC algorithm for angle estimation and a delay-time domain-based range and velocity estimator. Additionally, we study the communication design based on the estimated radar sensing parameters. To enable reliable IBFD radios in high-mobility scenarios, a SIC scheme compatible with OTFS and rapidly-changing channels is proposed, which is lacking in the literature. Numerical results demonstrate that the proposed ISAC waveform and associated estimation algorithm can provide both reliable communications and accurate radar sensing with reduced latency, improved spectral efficiency, etc