Lattice-Based Precoding And Decoding in MIMO Fading Systems

In this thesis, different aspects of lattice-based precoding and decoding for the transmission of digital and analog data over MIMO fading channels are investigated: 1) Lattice-based precoding in MIMO broadcast systems: A new viewpoint for adopting the lattice reduction in communication over MIMO broadcast channels is introduced. Lattice basis reduction helps us to reduce the average transmitted energy by modifying the region which includes the constellation points. The new viewpoint helps us to generalize the idea of lattice-reduction-aided precoding for the case of unequal-rate transmission, and obtain analytic results for the asymptotic behavior of the symbol-error-rate for the lattice-reduction-aided precoding and the perturbation technique. Also, the outage probability for both cases of fixed-rate users and fixed sum-rate is analyzed. It is shown that the lattice-reduction-aided method, using LLL algorithm, achieves the optimum asymptotic slope of symbol-error-rate (called the precoding diversity). 2) Lattice-based decoding in MIMO multiaccess systems and MIMO point-to-point systems: Diversity order and diversity-multiplexing tradeoff are two important measures for the performance of communication systems over MIMO fading channels. For the case of MIMO multiaccess systems (with single-antenna transmitters) or MIMO point-to-point systems with V-BLAST transmission scheme, it is proved that lattice-reduction-aided decoding achieves the maximum receive diversity (which is equal to the number of receive antennas). Also, it is proved that the naive lattice decoding (which discards the out-of-region decoded points) achieves the maximum diversity in V-BLAST systems. On the other hand, the inherent drawbacks of the naive lattice decoding for general MIMO fading systems is investigated. It is shown that using the naive lattice decoding for MIMO systems has considerable deficiencies in terms of the diversity-multiplexing tradeoff. Unlike the case of maximum-likelihood decoding, in this case, even the perfect lattice space-time codes which have the non-vanishing determinant property can not achieve the optimal diversity-multiplexing tradeoff. 3) Lattice-based analog transmission over MIMO fading channels: The problem of finding a delay-limited schemes for sending an analog source over MIMO fading channels is investigated in this part. First, the problem of robust joint source-channel coding over an additive white Gaussian noise channel is investigated. A new scheme is proposed which achieves the optimal slope for the signal-to-distortion-ratio (SDR) curve (unlike the previous known coding schemes). Then, this idea is extended to MIMO channels to construct lattice-based codes for joint source-channel coding over MIMO channels. Also, similar to the diversity-multiplexing tradeoff, the asymptotic performance of MIMO joint source-channel coding schemes is characterized, and a concept called diversity-fidelity tradeoff is introduced in this thesis

Feedback of channel state information in multi-antenna systems based on quantization of channel Gram matrices

This dissertation deals with the proper design of efficient feedback strategies for Multiple-Input Multiple-Output (MIMO) communication systems. MIMO systems outperform single antenna systems in terms of achievable throughput and are more resilient to noise and interference, which are becoming the limiting factors in the current and future communications. Apart from the clear performance advantages, MIMO systems introduce an additional complexity factor, since they require knowledge of the propagation channel in order to be able to adapt the transmission to the propagation channel’s characteristics and achieve optimum performance. This channel knowledge, also known as Channel State Information (CSI), is estimated at the receiver and sent to the transmitter through a limited feedback link. In this dissertation, first, the minimum channel information necessary at the transmitter for the optimum precoding design is identified. This minimum information for the optimum design of the system corresponds to the channel Gram matrix. It is essential for the design of optimized systems to avoid the transmission of redundant feedback information. Following this idea, a quantization algorithm that exploits the differential geometry of the set of Gram matrices and the correlation in time present in most propagation channels is developed in order to greatly improve the feedback performance. This scheme is applied first to single-user MIMO communications, then to some particular multiuser scenarios, and finally it is extended to general multiuser broadcast communications. To conclude, the feedback link sizing is studied. An analysis of the tradeoff between size of the forward link and size of the feedback link isformulated and the radio resource allocation problem, in terms of transmission energy, time, and bandwidth of the forward and feedback links is presented.En un mundo cada vez más interconectado, donde hay una clara tendencia hacia un mayor número de comunicaciones inalámbricas simultáneas (comunicaciones M2M: Machine to Machine, redes de sensores, etc.) y en el que las necesidades de capacidad de transmisión de los enlaces de comunicaciones aumentan de manera vertiginosa (audio, video, contenidos multimedia, alta definición, etc.) el problema de la interferencia se convierte en uno de los factores limitadores de los enlaces junto con los desvanecimientos del nivel de señal y las pérdidas de propagación. Por este motivo los sistemas que emplean múltiples antenas tanto en la transmisión como en la recepción (los llamados sistemas MIMO: Multiple-Input Multiple-Output) se presentan como una de las soluciones más interesantes para satisfacer los crecientes requisitos de capacidad y comportamiento relativo a interferencias. Los sistemas MIMO permiten obtener un mejor rendimiento en términos de tasa de transmisión de información y a su vez son más robustos frente a ruido e interferencias en el canal. Esto significa que pueden usarse para aumentar la capacidad de los enlaces de comunicaciones actuales o para reducir drásticamente el consumo energético manteniendo las mismas prestaciones. Por otro lado, además de estas claras ventajas, los sistemas MIMO introducen un punto de complejidad adicional puesto que para aprovechar al máximo las posibilidades de estos sistemas es necesario tener conocimiento de la información de estado del canal (CSI: Channel State Information) tanto en el transmisor como en el receptor. Esta CSI se obtiene mediante estimación de canal en el receptor y posteriormente se envía al transmisor a través de un canal de realimentación. Esta tesis trata sobre el diseño del canal de realimentación para la transmisión de CSI, que es un elemento fundamental de los sistemas de comunicaciones del presente y del futuro. Las técnicas de transmisión que consideran activamente el efecto de la interferencia y el ruido requieren adaptarse al canal y, para ello, la realimentación de CSI es necesaria. En esta tesis se identifica, en primer lugar, la mínima información sobre el estado del canal necesaria para implementar un diseño óptimo en el transmisor, con el fin de evitar transmitir información redundante y obtener así un sistema más eficiente. Esta información es la matriz de Gram del canal MIMO. Seguidamente, se desarrolla un algoritmo de cuantificación adaptado a la geometría diferencial del conjunto que contiene la información a cuantificar y que además aprovecha la correlación temporal existente en los canales de propagación inalámbricos. Este algoritmo se implementa y evalúa primero en comunicaciones MIMO punto a punto entre dos usuarios, después se implementa para algunos casos particulares con múltiples usuarios, y finalmente se amplía para el caso general de sistemas broadcast multi-usuario. Adicionalmente, esta tesis también estudia y optimiza el dimensionamiento del canal de realimentación en función de la cantidad de recursos radio disponibles, en términos de ancho de banda, tiempo y potencia de transmisión. Para ello presenta el problema de la distribución óptima de dichos recursos radio entre el enlace de transmisión de datos y el enlace de realimentación para transmisión de información sobre estado del canal como un problema de optimización

Transmission strategies for broadband wireless systems with MMSE turbo equalization

This monograph details efficient transmission strategies for single-carrier wireless broadband communication systems employing iterative (turbo) equalization. In particular, the first part focuses on the design and analysis of low complexity and robust MMSE-based turbo equalizers operating in the frequency domain. Accordingly, several novel receiver schemes are presented which improve the convergence properties and error performance over the existing turbo equalizers. The second part discusses concepts and algorithms that aim to increase the power and spectral efficiency of the communication system by efficiently exploiting the available resources at the transmitter side based upon the channel conditions. The challenging issue encountered in this context is how the transmission rate and power can be optimized, while a specific convergence constraint of the turbo equalizer is guaranteed.Die vorliegende Arbeit beschäftigt sich mit dem Entwurf und der Analyse von effizienten Übertragungs-konzepten für drahtlose, breitbandige Einträger-Kommunikationssysteme mit iterativer (Turbo-) Entzerrung und Kanaldekodierung. Dies beinhaltet einerseits die Entwicklung von empfängerseitigen Frequenzbereichs-entzerrern mit geringer Komplexität basierend auf dem Prinzip der Soft Interference Cancellation Minimum-Mean Squared-Error (SC-MMSE) Filterung und andererseits den Entwurf von senderseitigen Algorithmen, die durch Ausnutzung von Kanalzustandsinformationen die Bandbreiten- und Leistungseffizienz in Ein- und Mehrnutzersystemen mit Mehrfachantennen (sog. Multiple-Input Multiple-Output (MIMO)) verbessern. Im ersten Teil dieser Arbeit wird ein allgemeiner Ansatz für Verfahren zur Turbo-Entzerrung nach dem Prinzip der linearen MMSE-Schätzung, der nichtlinearen MMSE-Schätzung sowie der kombinierten MMSE- und Maximum-a-Posteriori (MAP)-Schätzung vorgestellt. In diesem Zusammenhang werden zwei neue Empfängerkonzepte, die eine Steigerung der Leistungsfähigkeit und Verbesserung der Konvergenz in Bezug auf existierende SC-MMSE Turbo-Entzerrer in verschiedenen Kanalumgebungen erzielen, eingeführt. Der erste Empfänger - PDA SC-MMSE - stellt eine Kombination aus dem Probabilistic-Data-Association (PDA) Ansatz und dem bekannten SC-MMSE Entzerrer dar. Im Gegensatz zum SC-MMSE nutzt der PDA SC-MMSE eine interne Entscheidungsrückführung, so dass zur Unterdrückung von Interferenzen neben den a priori Informationen der Kanaldekodierung auch weiche Entscheidungen der vorherigen Detektions-schritte berücksichtigt werden. Durch die zusätzlich interne Entscheidungsrückführung erzielt der PDA SC-MMSE einen wesentlichen Gewinn an Performance in räumlich unkorrelierten MIMO-Kanälen gegenüber dem SC-MMSE, ohne dabei die Komplexität des Entzerrers wesentlich zu erhöhen. Der zweite Empfänger - hybrid SC-MMSE - bildet eine Verknüpfung von gruppenbasierter SC-MMSE Frequenzbereichsfilterung und MAP-Detektion. Dieser Empfänger besitzt eine skalierbare Berechnungskomplexität und weist eine hohe Robustheit gegenüber räumlichen Korrelationen in MIMO-Kanälen auf. Die numerischen Ergebnisse von Simulationen basierend auf Messungen mit einem Channel-Sounder in Mehrnutzerkanälen mit starken räumlichen Korrelationen zeigen eindrucksvoll die Überlegenheit des hybriden SC-MMSE-Ansatzes gegenüber dem konventionellen SC-MMSE-basiertem Empfänger. Im zweiten Teil wird der Einfluss von System- und Kanalmodellparametern auf die Konvergenzeigenschaften der vorgestellten iterativen Empfänger mit Hilfe sogenannter Korrelationsdiagramme untersucht. Durch semi-analytische Berechnungen der Entzerrer- und Kanaldecoder-Korrelationsfunktionen wird eine einfache Berechnungsvorschrift zur Vorhersage der Bitfehlerwahrscheinlichkeit von SC-MMSE und PDA SC-MMSE Turbo Entzerrern für MIMO-Fadingkanäle entwickelt. Des Weiteren werden zwei Fehlerschranken für die Ausfallwahrscheinlichkeit der Empfänger vorgestellt. Die semi-analytische Methode und die abgeleiteten Fehlerschranken ermöglichen eine aufwandsgeringe Abschätzung sowie Optimierung der Leistungsfähigkeit des iterativen Systems. Im dritten und abschließenden Teil werden Strategien zur Raten- und Leistungszuweisung in Kommunikationssystemen mit konventionellen iterativen SC-MMSE Empfängern untersucht. Zunächst wird das Problem der Maximierung der instantanen Summendatenrate unter der Berücksichtigung der Konvergenz des iterativen Empfängers für einen Zweinutzerkanal mit fester Leistungsallokation betrachtet. Mit Hilfe des Flächentheorems von Extrinsic-Information-Transfer (EXIT)-Funktionen wird eine obere Schranke für die erreichbare Ratenregion hergeleitet. Auf Grundlage dieser Schranke wird ein einfacher Algorithmus entwickelt, der für jeden Nutzer aus einer Menge von vorgegebenen Kanalcodes mit verschiedenen Codierraten denjenigen auswählt, der den instantanen Datendurchsatz des Mehrnutzersystems verbessert. Neben der instantanen Ratenzuweisung wird auch ein ausfallbasierter Ansatz zur Ratenzuweisung entwickelt. Hierbei erfolgt die Auswahl der Kanalcodes für die Nutzer unter Berücksichtigung der Einhaltung einer bestimmten Ausfallwahrscheinlichkeit (outage probability) des iterativen Empfängers. Des Weiteren wird ein neues Entwurfskriterium für irreguläre Faltungscodes hergeleitet, das die Ausfallwahrscheinlichkeit von Turbo SC-MMSE Systemen verringert und somit die Zuverlässigkeit der Datenübertragung erhöht. Eine Reihe von Simulationsergebnissen von Kapazitäts- und Durchsatzberechnungen werden vorgestellt, die die Wirksamkeit der vorgeschlagenen Algorithmen und Optimierungsverfahren in Mehrnutzerkanälen belegen. Abschließend werden außerdem verschiedene Maßnahmen zur Minimierung der Sendeleistung in Einnutzersystemen mit senderseitiger Singular-Value-Decomposition (SVD)-basierter Vorcodierung untersucht. Es wird gezeigt, dass eine Methode, welche die Leistungspegel des Senders hinsichtlich der Bitfehlerrate des iterativen Empfängers optimiert, den konventionellen Verfahren zur Leistungszuweisung überlegen ist

D11.2 Consolidated results on the performance limits of wireless communications

Deliverable D11.2 del projecte europeu NEWCOM#The report presents the Intermediate Results of N# JRAs on Performance Limits of Wireless Communications and highlights the fundamental issues that have been investigated by the WP1.1. The report illustrates the Joint Research Activities (JRAs) already identified during the first year of the project which are currently ongoing. For each activity there is a description, an illustration of the adherence and relevance with the identified fundamental open issues, a short presentation of the preliminary results, and a roadmap for the joint research work in the next year. Appendices for each JRA give technical details on the scientific activity in each JRA.Peer ReviewedPreprin

Optimization Algorithms in Wireless and Quantum Communications

Since the first communication systems were developed, the scientific community has been witnessing attempts to increase the amount of information that can be transmitted. In the last 10--15 years there has been a tremendous amount of research towards developing multi-antenna systems which would hopefully provide high-data-rate transmissions. However, increasing the overall amount of transmitted information increases the complexity of the necessary signal processing. A large portion of this thesis deals with several important issues in signal processing of multi-antenna systems. In almost every particular case the goal is to develop a technique/algorithm so that the overall complexity of the signal processing is significantly decreased. In the first part of the thesis a very important problem of signal detection in MIMO (multiple-input multiple-output) systems is considered. The problem is analyzed in two different scenarios: when the transmission medium (channel) 1) is known and 2) is unknown at the receiver. The former case is often called coherent and the later non-coherent MIMO detection. Both cases usually amount to solving highly complex NP-hard combinatorial optimization problems. For the coherent case we develop a significant improvement of the traditional sphere decoder algorithm commonly used for this type of detection. An interesting connection between the new improved algorithm and the H-infinity estimation theory is established, and the performance improvement over the standard sphere decoder is demonstrated. For the non-coherent case we develop a counterpart to the standard sphere decoder, the so-called out-sphere decoder. The complexity of the algorithm is viewed as a random variable; its expected value is analyzed and shown to be significantly smaller than the one of the overall exhaustive search. In the non-coherent case, in addition to the complexity analysis of the exact out-sphere decoder, we analyze the performance loss of a suboptimal technique. We show that only a moderate loss of a few dbs in power required at the transmitter will occur if a polynomial algorithm based on the semi-definite relaxation is used in place of any exact technique (which of course is not known to be polynomial). In the second part of the thesis we consider a few problems that arise in wireless broadcast channels. Namely, we consider the problem of the information symbol vector design at the transmitter. A polynomial linear precoding technique is constructed. It enables achieving data rates very close to the ones achieved with DPC (dirty paper coding) technique. Additionally, for another suboptimal polynomial scheme (the so-called nulling and cancelling), we show that it asymptotically achieves the same data rate as the optimal, exponentially complex, DPC. In the last part of the thesis we consider a quantum counterpart of the signal detection from classical communication. In quantum systems the signals are quantum states and the quantum detection problem amounts to designing measurement operators which have to satisfy certain quantum mechanics laws. A specific type of quantum detection called unambiguous detection, which has numerous applications including quantum filtering, has recently attracted a lot of attention in the research community. We develop a general framework for numerically solving this problem using the tools from the convex optimization theory. Furthermore, in the special case where the two quantum states are of rank 2, we construct an explicit analytical solution for the measurement operators. At the end we would like to emphasize that the contribution of this thesis goes beyond the specific problems mentioned here. Most algorithmic optimization techniques developed in this paper are generally applicable. While it is a fact that our results were originally motivated by wireless and quantum communications applications, we believe that the developed techniques will find applications in many different areas where similar optimization problems appear.</p

Resource allocation for 5G technologies under statistical queueing constraints

As the launch of fifth generation (5G) wireless networks is approaching, recent years have witnessed comprehensive discussions about a possible 5G standard. Many transmission scenarios and technologies have been proposed and initial over-the-air experimental trials have been conducted. Most of the existing literature studies on 5G technologies have mainly focused on the physical layer parameters and quality of service (QoS) requirements, e.g., achievable data rates. However, the demand for delay-sensitive data traffic over wireless networks has increased exponentially in the recent years, and is expected to further increase by the time of 5G. Therefore, other constraints at the data-link layer concerning the buffer overflow and delay violation probabilities should also be regarded. It follows that evaluating the performance of the 5G technologies when such constraints are considered is a timely task. Motivated by this fact, in this thesis we explore the performance of three promising 5G technologies when operating under certain QoS at the data-link layer. We follow a cross-layer approach to examine the interplay between the physical and data-link layers when statistical QoS constraints are inflicted in the form of limits on the delay violation and buffer overflow probabilities. Noting that wireless systems, generally, have limited physical resources, in this thesis we mainly target designing adaptive resource allocation schemes to maximize the system performance under such QoS constraints. We initially investigate the throughput and energy efficiency of a general class of multiple-input multiple-output (MIMO) systems with arbitrary inputs. As a cross-layer evaluation tool, we employ the effective capacity as the main performance metric, which is the maximum constant data arrival rate at a buffer that can be sustained by the channel service process under specified QoS constraints. We obtain the optimal input covariance matrix that maximizes the effective capacity under a short-term average power budget. Then, we perform an asymptotic analysis of the effective capacity in the low signal-to-noise ratio and large-scale antenna (massive MIMO) regimes. Such analysis has a practical importance for 5G scenarios that necessitate low latency, low power consumption, and/or ability to simultaneously support massive number of users. Non-orthogonal multiple access (NOMA) has attracted significant attention in the recent years as a promising multiple access technology for 5G. In this thesis, we consider a two-user power-domain NOMA scheme in which both transmitters employ superposition coding and the receiver applies successive interference cancellation (SIC) with a certain order. For practical concerns, we consider limited transmission power budgets at the transmitters, and assume that both transmitters have arbitrarily distributed input signals. We again exploit the effective capacity as the main cross-layer performance measure. We provide a resource management scheme that can jointly obtain the optimal power allocation policies at the transmitters and the optimal decoding order at the receiver, with the goal of maximizing the effective capacity region that provides the maximum allowable sustainable arrival rate region at the transmitters' buffers under QoS guarantees. In the recent years, visible light communication (VLC) has emerged as a potential transmission technology that can utilize the visible light spectrum for data transmission along with illumination. Different from the existing literature studies on VLC, in this thesis we consider a VLC system in which the access point (AP) is unaware of the channel conditions, thus the AP sends the data at a fixed rate. Under this assumption, and considering an ON-OFF data source, we provide a cross-layer study when the system is subject to statistical buffering constraints. To this end, we employ the maximum average data arrival rate at the AP buffer and the non-asymptotic bounds on buffering delay as the main performance measures. To facilitate our analysis, we adopt a two-state Markov process to model the fixed-rate transmission strategy, and we then formulate the steady-state probabilities of the channel being in the ON and OFF states. The coexistence of radio frequency (RF) and VLC systems in typical indoor environments can be leveraged to support vast user QoS needs. In this thesis, we examine the benefits of employing both technologies when operating under statistical buffering limitations. Particularly, we consider a multi-mechanism scenario that utilizes RF and VLC links for data transmission in an indoor environment. As the transmission technology is the main physical resource to be concerned in this part, we propose a link selection process through which the transmitter sends data over the link that sustains the desired QoS guarantees the most. Considering an ON-OFF data source, we employ the maximum average data arrival rate at the transmitter buffer and the non-asymptotic bounds on data buffering delay as the main performance measures. We formulate the performance measures under the assumption that both links are subject to average and peak power constraints

Distributed detection, localization, and estimation in time-critical wireless sensor networks

In this thesis the problem of distributed detection, localization, and estimation (DDLE) of a stationary target in a fusion center (FC) based wireless sensor network (WSN) is considered. The communication process is subject to time-critical operation, restricted power and bandwidth (BW) resources operating over a shared communication channel Buffering from Rayleigh fading and phase noise. A novel algorithm is proposed to solve the DDLE problem consisting of two dependent stages: distributed detection and distributed estimation. The WSN performs distributed detection first and based on the global detection decision the distributed estimation stage is performed. The communication between the SNs and the FC occurs over a shared channel via a slotted Aloha MAC protocol to conserve BW. In distributed detection, hard decision fusion is adopted, using the counting rule (CR), and sensor censoring in order to save power and BW. The effect of Rayleigh fading on distributed detection is also considered and accounted for by using distributed diversity combining techniques where the diversity combining is among the sensor nodes (SNs) in lieu of having the processing done at the FC. Two distributed techniques are proposed: the distributed maximum ratio combining (dMRC) and the distributed Equal Gain Combining (dEGC). Both techniques show superior detection performance when compared to conventional diversity combining procedures that take place at the FC. In distributed estimation, the segmented distributed localization and estimation (SDLE) framework is proposed. The SDLE enables efficient power and BW processing. The SOLE hinges on the idea of introducing intermediate parameters that are estimated locally by the SNs and transmitted to the FC instead of the actual measurements. This concept decouples the main problem into a simpler set of local estimation problems solved at the SNs and a global estimation problem solved at the FC. Two algorithms are proposed for solving the local problem: a nonlinear least squares (NLS) algorithm using the variable projection (VP) method and a simpler gird search (GS) method. Also, Four algorithms are proposed to solve the global problem: NLS, GS, hyperspherical intersection method (HSI), and robust hyperspherical intersection (RHSI) method. Thus, the SDLE can be solved through local and global algorithm combinations. Five combinations are tied: NLS2 (NLS-NLS), NLS-HSI, NLS-RHSI, GS2, and GS-N LS. It turns out that the last algorithm combination delivers the best localization and estimation performance. In fact , the target can be localized with less than one meter error. The SNs send their local estimates to the FC over a shared channel using the slotted-Aloha MAC protocol, which suits WSNs since it requires only one channel. However, Aloha is known for its relatively high medium access or contention delay given the medium access probability is poorly chosen. This fact significantly hinders the time-critical operation of the system. Hence, multi-packet reception (MPR) is used with slotted Aloha protocol, in which several channels are used for contention. The contention delay is analyzed for slotted Aloha with and without MPR. More specifically, the mean and variance have been analytically computed and the contention delay distribution is approximated. Having theoretical expressions for the contention delay statistics enables optimizing both the medium access probability and the number of MPR channels in order to strike a trade-off between delay performance and complexity

Interference management techniques in large-scale wireless networks

In this thesis, advanced interference management techniques are designed and evaluated for large-scale wireless networks with realistic assumptions, such as signal propagation loss, random node distribution and non-instantaneous channel state information at the transmitter (CSIT). In the first part of the thesis, the Maddah-Ali and Tse (MAT) scheme for the 2-user and 2-antenna base station (BS) broadcast channel (BC) is generalised and optimised using the probabilistic-constrained optimisation approach. With consideration of the unknown channel entries, the proposed optimisation approach guarantees a high probability that the interference leakage power is below a certain threshold in the presence of minimum interference leakage receivers. The desired signal detectability is maximised at the same time and the closed-form solution for the receiving matrices is provided. Afterwards, the proposed optimisation approach is extended to the 3-user BC with 2-antenna BS. Simulation results show substantial sum rate gain over the MAT scheme, especially with a large spatial correlation at the receiver side. In the second part, the MAT scheme is extended to the time-correlated channels in three scenarios, in which degrees of freedom (DoF) regions as well as achievability schemes are studied: 1) 2-user interference channel (IC) using imperfect current and imperfect delayed CSIT; 2) K-user BC with K-antenna BS using imperfect current and perfect delayed CSIT; 3) 3-user BC with 2-antenna BS using imperfect current and perfect delayed CSIT. Notably, the consistency of the proposed DoF regions with the MAT scheme and the ZF beamforming schemes using perfect current CSIT consents to the optimality of the proposed achievability schemes. In the third part, the performance of the ZF receiver is evaluated in Poisson distributed wireless networks. Simple static networks as well as dynamic networks are studied. For the static network, transmission capacity is derived whereby the receiver can eliminate interference from nearby transmitters. It is shown that more spatial receive degrees of freedom (SRDoF) should be allocated to decode the desired symbol in the presence of low transmitter intensity. For the dynamic network, in which the data traffic is modelled by queueing theory, interference alignment (IA) beamforming is considered and implemented sequentially. Interestingly, transmitting one data stream achieves the highest area spectrum efficiency. Finally, a distance-dependent IA beamforming scheme is designed for a generic 2-tier heterogeneous wireless network. Second-tier transmitters partially align their interferences to the dominant cross-tier interference overheard by the receivers in the same cluster. Essentially, the proposed IA scheme compromises between enhancing the signal-to-interference ratio and increasing the multiplexing gain. It is shown that acquiring accurate distance knowledge brings insignificant throughput gain compared to statistical distance knowledge. Simulation results validate the derived expressions of success probabilities as well as throughput, and show that the distance-dependent IA scheme significantly outperforms the traditional IA scheme in the presence of path-loss effect