639 research outputs found
Relay-Aided Communication in Large Interference Limited Wireless Networks
In recent years, the number of active wireless devices increases exponentially and it is, therefore, to expect that the interference increases as well. Interference between communication links is the major performance limiting factor in today's communication networks. Hence, the handling of the overall interference in a network is one major challenge in wireless communication networks of the future. If the interference signals are weak in comparison to the useful signal, they can be simply treated as noise. If the interference signals are strong in comparison to the useful signal, they can be reliably decoded and subtracted from the received signal at the receivers. However, in multiuser communication networks, the interference and the useful signal are often of comparable signal strength. The conventional approach to handle these interference signals is to orthogonalize the useful signal and the interference signals using, e.g., time division multiple access (TDMA) or frequency division multiple access (FDMA). In the past few years, instead of orthogonalization, interference alignment (IA) has been developed as an efficient technique to handle interference signals, especially in the high signal to noise ratio (SNR) region. The basic idea of IA is to align multiple interference signals in a particular subspace of reduced dimension at each receiver. The objective is to minimize the signal dimensions occupied by interference at each receiver. In order to perform IA, the receive space is divided into two disjoint subspaces, the useful signal subspace and the interference signal subspace. Each transmitting node designs its transmit filters in such a way that at each receiving node, all interference signals are within the interference subspace and only the useful signal is in the useful subspace.
In this thesis, the focus is on large interference limited wireless communication networks. In contrast to the conventional use of relays, for extending the coverage, in this thesis, the relays are used to manipulate the effective end-to-end channel between the transmitters and receivers to perform IA in the network. Since the relays are used to assist the process of IA and not interested in the data streams transmitted by the nodes, amplify-and-forward relays are sufficient to support the process of IA. Therefore, the main focus of this thesis is on amplify-and-forward relays. Throughout this thesis, it is assumed that all nodes and relays are multi-antenna half-duplex devices. When considering large networks, the assumption that all nodes are connected to all relays does not hold due to physical propagation phenomena, e.g., high path loss and shadowing. In such large networks, the distances between different nodes may differ a lot, leading to links of considerably different signal strengths, where sufficiently weak links may be neglected. Hence, large networks are in general partially connected. In this thesis, three important interference-limited relay aided wireless network topologies are investigated, the partially connected relay aided multi-pair pair-wise communication network, the fully connected multi-group multi-way relaying network and the partially connected multi-group multi-way relaying network. For each of these topologies, new algorithms to perform IA are developed in this thesis.
First, a large partially connected relay aided pair-wise communication network is considered. The concept of an appropriate partitioning of a partially connected network into subnetworks which are themselves fully connected is introduced. Each of these subnetworks contains a single relay and all nodes being connected to this relay. Some nodes or even communication pairs may be connected to multiple relays. The bidirectional pair-wise communication between the nodes takes place via the intermediate relays, using the two-way relaying protocol. Only relays which are connected to both nodes of a communication pair can serve this pair. Hence, it is assumed that all communication pairs in the entire network are served by at least one relay. The most challenging part of such a partially connected network is the handling of nodes which are connected to multiple relays. Hence, techniques called simultaneous signal alignment (SSA) and simultaneous channel alignment (SCA), are proposed to perform signal alignment (SA) and channel alignment (CA) with multiple relays simultaneously. SA means that all nodes transmit to the relay in such a way that the signals of each communicating pair are pair-wise aligned at the relay. For CA, which is dual to SA, the receive filter of each node is designed such that the effective channels between the relay and both nodes of a communicating pair span the same subspace. A closed-form solution to perform IA in this network topology is obtained and the properness conditions for SSA and SCA are derived. It is shown that local channel state information (CSI) is sufficient to perform IA in partially connected networks, whereas in fully connected relay aided networks, global CSI is required in general. Through simulations, it is shown that the proposed closed-form solution achieves more degrees of freedom (DoF) than the reference algorithms and has better sum-rate performance, especially in the high SNR-region. Especially in large wireless networks, it may happen that not both nodes of a communication pair are connected to the same relays. If a single node of a communication pair is in addition connected to a relay which, therefore, cannot assist the communication, this node receives only interference and no useful signal from this relay. Such a node suffers from inter-subnetwork interference, due to the connection by an inter-subnetwork link to the additional relay. Hence, in this thesis, a closed form algorithm which minimizes the inter-subnetwork interference power in the whole partially connected network is proposed and the properness conditions are derived. The condition under which an interference free-communication can be achieved by the proposed inter-subnetwork interference power minimization algorithm is derived. Further, it is shown that the proposed inter-subnetwork interference power minimization algorithm achieves a higher sum rate in comparison to the considered reference algorithm.
Secondly, a fully connected multi-group multi-way relaying networks is considered. In such a network, multiple nodes form a group and each node wants to share its message with all other nodes in its group via an intermediate relay. The group-wise communication between the nodes inside a group takes place via the intermediate relay, using a transmission strategy considering several multiple access (MAC) phases and several multicast (MC) phases, in general. In this thesis, a multicast IA algorithm to handle the interference in such a network is proposed. The idea of the proposed algorithm is that in each of the MC phases, a multiple input multiple output (MIMO) interference multicast channel is created by separating the antennas of the relay into as many clusters as groups in the network. Each of these clusters serves a specific group of nodes and transmits in such a way that the signals transmitted from different clusters are aligned at the receiving nodes of the non-intended multicast groups. It is shown that the minimum required number of antennas at the relay is independent of the number of nodes per group, which is an important property since the number of antennas available at the relay is limited in general. Furthermore, the properness conditions for the proposed multicast IA algorithm are derived. It is shown that the proposed multicast algorithm outperforms a reference algorithm for a broad range of SNR values, while still requiring less antennas at the relay.
Finally, a large partially connected multi-group multi-way relay network is considered. In contrast to the fully connected multi-group multi-way relaying network, multiple relays are considered in this partially connected network. Such a partially connected network can be partitioned into subnetworks that are themselves fully connected. Hence, such a partially connected network consists of multiple subnetworks, where each of these contains a single relay and all groups of nodes which are connected to this relay. Each group of nodes may be connected to one or multiple relays. This means that not all groups of nodes are connected to all relays in the network. However, any group is connected to at least one relay which serves this group of nodes. The group-wise exchange of data between the nodes inside a group is performed via the multi-way relaying protocol. The most challenging part of such a partially connected network is the handling of the nodes inside groups which are connected to multiple relays. To overcome this challenge, new techniques called simultaneous group signal alignment (SGSA) and simultaneous group channel alignment (SGCA) are introduced to perform SA and CA in partially connected multi-group multi-way relaying networks. A closed-form IA solution for this network topology is obtained and the properness conditions for the solvability of SGSA and SGCA are derived. It is shown that the proposed IA algorithm outperforms the reference algorithm in terms of sum rate and DoF
A Tutorial on Nonorthogonal Multiple Access for 5G and Beyond
Today's wireless networks allocate radio resources to users based on the
orthogonal multiple access (OMA) principle. However, as the number of users
increases, OMA based approaches may not meet the stringent emerging
requirements including very high spectral efficiency, very low latency, and
massive device connectivity. Nonorthogonal multiple access (NOMA) principle
emerges as a solution to improve the spectral efficiency while allowing some
degree of multiple access interference at receivers. In this tutorial style
paper, we target providing a unified model for NOMA, including uplink and
downlink transmissions, along with the extensions tomultiple inputmultiple
output and cooperative communication scenarios. Through numerical examples, we
compare the performances of OMA and NOMA networks. Implementation aspects and
open issues are also detailed.Comment: 25 pages, 10 figure
Advanced Signal Processing Techniques for Two-Way Relaying Networks and Full-Duplex Communication Systems
Sehr hohe Datenraten und ständig verfügbare Netzabdeckung in
zukĂĽnftigen drahtlosen Netzwerken erfordern neue Algorithmen auf der
physischen Schicht. Die Nutzung von Relais stellt ein vielversprechendes
Verfahren dar, da die Netzabdeckung gesteigert werden kann. Zusätzlich
steht hierdurch im Vergleich zu Kupfer- oder Glasfaserleitungen eine
preiswerte Lösung zur Anbindung an die Netzinfrastruktur zur Verfügung.
Traditionelle Einwege-Relais-Techniken (One-Way Relaying [OWR]) nutzen
Halbduplex-Verfahren (HD-Verfahren), welche das Ăśbertragungssystem
ausbremst und zu spektralen Verlusten fĂĽhrt. Einerseits erlauben es
Zweiwege-Relais-Techniken (Two-Way Relaying [TWR]), simultan sowohl an das
Relais zu senden als auch von diesem zu empfangen, wodurch im Vergleich zu
OWR das Spektrum effizienter genutzt wird. Aus diesem Grunde untersuchen
wir Zweiwege-Relais und im Speziellen TWR-Systeme fĂĽr den
Mehrpaar-/Mehrnutzer-Betrieb unter Nutzung von Amplify-and-forward-Relais
(AF-Relais). Derartige Szenarien leiden unter Interferenzen zwischen Paaren
bzw. zwischen Nutzern. Um diesen Interferenzen Herr zu werden, werden
hochentwickelte Signalverarbeitungsalgorithmen – oder in anderen Worten
räumliche Mehrfachzugriffsverfahren (Spatial Division Multiple Access
[SDMA]) – benötigt. Andererseits kann der spektrale Verlust durch den
HD-Betrieb auch kompensiert werden, wenn das Relais im Vollduplexbetrieb
arbeitet. Nichtsdestotrotz ist ein FD-Gerät in der Praxis aufgrund starker
interner Selbstinterferenz (SI) und begrenztem Dynamikumfang des
Tranceivers schwer zu realisieren. Aus diesem Grunde sollten
fortschrittliche Verfahren zur SI-ĂśnterdrĂĽckung entwickelt werden. Diese
Dissertation trägt diesen beiden Zielen Rechnung, indem optimale und/oder
effiziente algebraische Lösungen entwickelt werden, welche verschiedenen
Nutzenfunktionen, wie Summenrate und minimale Sendeleistung, maximieren.Im
ersten Teil studieren wir zunächst Mehrpaar-TWR-Netzwerke mit einem
einzelnen Mehrantennen-AF-Relais. Dieser Anwendungsfall kann auch so
betrachtet werden, dass sich mehrere verschiedene Dienstoperatoren Relais
und Spektrum teilen, wobei verschiedene Nutzerpaare zu verschiedenen
Dienstoperatoren gehören. Aktuelle Ansätzen zielen auf
InterferenzunterdrĂĽckung ab. Wir schlagen ein auf Projektion basiertes
Verfahren zur Trennung mehrerer Dienstoperatoren (projection based
separation of multiple operators [ProBaSeMO]) vor. ProBaSeMO ist leicht
anpassbar fĂĽr den Fall, dass jeder Nutzer mehrere Antennen besitzt oder
unterschiedliche Systemdesignkriterien angewendet werden mĂĽssen. Als
BewertungsmaĂźstab fĂĽr ProBaSeMO entwickeln wir optimale Algorithmen zur
Maximierung der Summenrate, zur Minimierung der Sendeleistung am Relais
oder zur Maximierung des minimalen
Signal-zu-Interferenz-und-Rausch-Verhältnisses (Signal to Interference and
Noise Ratio [SINR]) am Nutzer. Zur Maximierung der Summenrate wurden
spezifische gradientenbasierte Methoden entwickelt, die unabhängig davon
sind, ob ein Nutzer mit einer oder mehr Antennen ausgestattet ist. Um im
Falle eines „Worst-Case“ immer noch eine polynomielle Laufzeit zu
garantieren, entwickelten wir einen Algorithmus mit polynomieller Laufzeit.
Dieser ist inspiriert von der „Polynomial Time Difference of Convex
Functions“-Methode (POTDC-Methode). Bezüglich der Summenrate des Systems
untersuchen wir zuletzt, welche Bedingungen erfĂĽllt sein mĂĽssen, um einen
Gewinn durch gemeinsames Nutzen zu erhalten. Hiernach untersuchen wir die
Maximierung der Summenrate eines Mehrpaar-TWR-Netzwerkes mit mehreren
Einantennen-AF-Relais und Einantennen-Nutzern. Das daraus resultierende
Problem der Summenraten-Maximierung, gebunden an eine bestimmte
Gesamtsendeleistung aller Relais im Netzwerk, ist ähnlich dem des
vorangegangenen Szenarios. Dementsprechend kann eine optimale Lösung für
das eine Szenario auch fĂĽr das jeweils andere Szenario genutzt werden.
Weiterhin werden basierend auf dem Polynomialzeitalgorithmus global
optimale Lösungen entwickelt. Diese Lösungen sind entweder an eine
maximale Gesamtsendeleistung aller Relais oder an eine maximale
Sendeleistung jedes einzelnen Relais gebunden. Zusätzlich entwickeln wir
suboptimale Lösungen, die effizient in ihrer Laufzeit sind und eine
Approximation der optimalen Lösung darstellen. Hiernach verlegen wir unser
Augenmerk auf ein Mehrpaar-TWR-Netzwerk mit mehreren Mehrantennen-AF-Relais
und mehreren Repeatern. Solch ein Szenario ist allgemeiner, da die
vorherigen beiden Szenarien als spezielle Realisierungen dieses Szenarios
aufgefasst werden können. Das Interferenz-Management in diesem Szenario
ist herausfordernder aufgrund der vorhandenen Repeater.
Interferenzneutralisierung (IN) stellt eine Lösung dar, um diese Art
Interferenz zu handhaben. Im Zuge dessen werden notwendige und ausreichende
Bedingungen zur Aufhebung der Interferenz hergeleitet. Weiterhin wird ein
Framework entwickelt, dass verschiedene Systemnutzenfunktionen optimiert,
wobei IN im jeweiligen Netzwerk vorhanden sein kann oder auch nicht. Dies
ist unabhängig davon, ob die Relais einer maximalen Gesamtsendeleistung
oder einer individuellen maximalen Sendeleistung unterliegen. Letztendlich
entwickeln wir ein Ăśbertragungsverfahren sowie ein Vorkodier- und
Dekodierverfahren fĂĽr Basisstationen (BS) in einem TWR-assistierten
Mehrbenutzer-MIMO-Downlink-Kanal. Im Vergleich mit dem
Mehrpaar-TWR-Netzwerk leidet dieses Szenario unter Interferenzen zwischen
den Kanälen. Wir entwickeln drei suboptimale Algorithmen, welche auf
Kanalinversion basieren. ProBaSeMO und „Zero-Forcing Dirty Paper
Coding“ (ZFDPC), welche eine geringe Zeitkomplexität aufweisen, schaffen
eine Balance zwischen Leistungsfähigkeit und Komplexität. Zusätzlich
gibt es jeweils nur geringe EinbrĂĽche in stark beanspruchten
Kommunikationssystemen.Im zweiten Teil untersuchen wir Techniken zur
SI-UnterdrĂĽckung, um den FD-Gewinn in einem Punkt-zu-Punkt-System
auszunutzen. Zunächst entwickeln wir ein Übertragungsverfahren, dass auf
SI RĂĽcksicht nimmt und die SI-UnterdrĂĽckung gegen den Multiplexgewinn
abwägt. Die besten Ergebnisse werden durch die perfekte Kenntnis des
Kanals erzielt, was praktisch nicht genau der Fall ist. Aus diesem Grund
werden Übertragungstechniken für den „Worst Case“ entwickelt, die den
Kanalschätzfehlern Rechnung tragen. Diese Fehler werden deterministisch
modelliert und durch Ellipsoide beschränkt. In praktischen Szenarien ist
der HF-Schaltkreise nicht perfekt. Dies hat Einfluss auf die Verfahren zur
SI-UnterdrĂĽckung und fĂĽhrt zu einer Restselbstinterferenz. Wir entwickeln
effiziente Ăśbertragungstechniken mittels Beamforming, welche auf dem
Signal-zu-Verlust-und-Rausch-Verhältnis (signal to leakage plus noise
ratio [SLNR]) aufbauen, um Unvollkommenheiten der HF-Schaltkreise
auszugleichen. Zusätzlich können alle Designkonzepte auf FD-OWR-Systeme
erweitert werden.To enable ultra-high data rate and ubiquitous coverage in future wireless
networks, new physical layer techniques are desired. Relaying is a
promising technique for future wireless networks since it can boost the
coverage and can provide low cost wireless backhauling solutions, as
compared to traditional wired backhauling solutions via fiber and copper.
Traditional one-way relaying (OWR) techniques suffer from the spectral loss
due to the half-duplex (HD) operation at the relay. On one hand, two-way
relaying (TWR) allows the communication partners to transmit to and/or
receive from the relay simultaneously and thus uses the spectrum more
efficiently than OWR. Therefore, we study two-way relays and more
specifically multi-pair/multi-user TWR systems with amplify-and-forward
(AF) relays. These scenarios suffer from inter-pair or inter-user
interference. To deal with the interference, advanced signal processing
algorithms, in other words, spatial division multiple access (SDMA)
techniques, are desired. On the other hand, if the relay is a full-duplex
(FD) relay, the spectral loss due to a HD operation can also be
compensated. However, in practice, a FD device is hard to realize due to
the strong loop-back self-interference and the limited dynamic range at the
transceiver. Thus, advanced self-interference suppression techniques should
be developed. This thesis contributes to the two goals by developing
optimal and/or efficient algebraic solutions for different scenarios
subject to different utility functions of the system, e.g., sum rate
maximization and transmit power minimization. In the first part of this
thesis, we first study a multi-pair TWR network with a multi-antenna AF
relay. This scenario can be also treated as the sharing of the relay and
the spectrum among multiple operators assuming that different pairs of
users belong to different operators. Existing approaches focus on
interference suppression. We propose a projection based separation of
multiple operators (ProBaSeMO) scheme, which can be easily extended when
each user has multiple antennas or when different system design criteria
are applied. To benchmark the ProBaSeMO scheme, we develop optimal relay
transmit strategies to maximize the system sum rate, minimize the required
transmit power at the relay, or maximize the minimum signal to interference
plus noise ratio (SINR) of the users. Specifically for the sum rate
maximization problem, gradient based methods are developed regardless
whether each user has a single antenna or multiple antennas. To guarantee a
worst-case polynomial time solution, we also develop a polynomial time
algorithm which has been inspired by the polynomial time difference of
convex functions (POTDC) method. Finally, we analyze the conditions for
obtaining the sharing gain in terms of the sum rate. Then we study the sum
rate maximization problem of a multi-pair TWR network with multiple single
antenna AF relays and single antenna users. The resulting sum rate
maximization problem, subject to a total transmit power constraint of the
relays in the network, yields a similar problem structure as in the
previous scenario. Therefore the optimal solution for one scenario can be
used for the other. Moreover, a global optimal solution, which is based on
the polyblock approach, and several suboptimal solutions, which are more
computationally efficient and approximate the optimal solution, are
developed when there is a total transmit power constraint of the relays in
the network or each relay has its own transmit power constraint. We then
shift our focus to a multi-pair TWR network with multiple multi-antenna AF
relays and multiple dumb repeaters. This scenario is more general because
the previous two scenarios can be seen as special realizations of this
scenario. The interference management in this scenario is more challenging
due to the existence of the repeaters. Interference neutralization (IN) is
a solution for dealing with this kind of interference. Thereby, necessary
and sufficient conditions for neutralizing the interference are derived.
Moreover, a general framework to optimize different system utility
functions in this network with or without IN is developed regardless
whether the AF relays in the network have a total transmit power limit or
individual transmit power limits. Finally, we develop the relay transmit
strategy as well as base station (BS) precoding and decoding schemes for a
TWR assisted multi-user MIMO (MU-MIMO) downlink channel. Compared to the
multi-pair TWR network, this scenario suffers from the co-channel
interference. We develop three suboptimal algorithms which are based on
channel inversion, ProBaSeMO and zero-forcing dirty paper coding (ZFDPC),
which has a low computational complexity, provides a balance between the
performance and the complexity, and suffers only a little when the system
is heavily loaded, respectively.In the second part of this thesis, we
investigate self-interference (SI) suppression techniques to exploit the FD
gain for a point-to-point MIMO system. We first develop SI aware transmit
strategies, which provide a balance between the SI suppression and the
multiplexing gain of the system. To get the best performance, perfect
channel state information (CSI) is needed, which is imperfect in practice.
Thus, worst case transmit strategies to combat the imperfect CSI are
developed, where the CSI errors are modeled deterministically and bounded
by ellipsoids. In real word applications, the RF chain is imperfect. This
affects the performance of the SI suppression techniques and thus results
in residual SI. We develop efficient transmit beamforming techniques, which
are based on the signal to leakage plus noise ratio (SLNR) criterion, to
deal with the imperfections in the RF chain. All the proposed design
concepts can be extended to FD OWR systems
Energy efficiency and interference management in long term evolution-advanced networks.
Doctoral Degree. University of KwaZulu-Natal, Durban.Cellular networks are continuously undergoing fast extraordinary evolution to overcome
technological challenges. The fourth generation (4G) or Long Term Evolution-Advanced
(LTE-Advanced) networks offer improvements in performance through increase in network density,
while allowing self-organisation and self-healing. The LTE-Advanced architecture is heterogeneous,
consisting of different radio access technologies (RATs), such as macrocell, smallcells, cooperative
relay nodes (RNs), having various capabilities, and coexisting in the same geographical coverage
area. These network improvements come with different challenges that affect users’ quality of
service (QoS) and network performance. These challenges include; interference management, high
energy consumption and poor coverage of marginal users. Hence, developing mitigation schemes for
these identified challenges is the focus of this thesis.
The exponential growth of mobile broadband data usage and poor networks’ performance along
the cell edges, result in a large increase of the energy consumption for both base stations (BSs) and
users. This due to improper RN placement or deployment that creates severe inter-cell and intracell
interferences in the networks. It is therefore, necessary to investigate appropriate RN placement
techniques which offer efficient coverage extension while reducing energy consumption and mitigating
interference in LTE-Advanced femtocell networks. This work proposes energy efficient and optimal
RN placement (EEORNP) algorithm based on greedy algorithm to assure improved and effective
coverage extension. The performance of the proposed algorithm is investigated in terms of coverage
percentage and number of RN needed to cover marginalised users and found to outperform other RN
placement schemes.
Transceiver design has gained importance as one of the effective tools of interference
management. Centralised transceiver design techniques have been used to improve network
performance for LTE-Advanced networks in terms of mean square error (MSE), bit error rate (BER)
and sum-rate. The centralised transceiver design techniques are not effective and computationally
feasible for distributed cooperative heterogeneous networks, the systems considered in this thesis.
This work proposes decentralised transceivers design based on the least-square (LS) and minimum MSE (MMSE) pilot-aided channel estimations for interference management in uplink
LTE-Advanced femtocell networks. The decentralised transceiver algorithms are designed for the
femtocells, the macrocell user equipments (MUEs), RNs and the cell edge macrocell UEs (CUEs) in
the half-duplex cooperative relaying systems. The BER performances of the proposed algorithms
with the effect of channel estimation are investigated.
Finally, the EE optimisation is investigated in half-duplex multi-user multiple-input
multiple-output (MU-MIMO) relay systems. The EE optimisation is divided into sub-optimal EE
problems due to the distributed architecture of the MU-MIMO relay systems. The decentralised
approach is employed to design the transceivers such as MUEs, CUEs, RN and femtocells for the
different sub-optimal EE problems. The EE objective functions are formulated as convex
optimisation problems subject to the QoS and transmit powers constraints in case of perfect channel
state information (CSI). The non-convexity of the formulated EE optimisation problems is
surmounted by introducing the EE parameter substractive function into each proposed algorithms.
These EE parameters are updated using the Dinkelbach’s algorithm. The EE optimisation of the
proposed algorithms is achieved after finding the optimal transceivers where the unknown
interference terms in the transmit signals are designed with the zero-forcing (ZF) assumption and
estimation errors are added to improve the EE performances. With the aid of simulation results, the
performance of the proposed decentralised schemes are derived in terms of average EE evaluation
and found to be better than existing algorithms
A lunar base reference mission for the phased implementation of bioregenerative life support system components
Previous design efforts of a cost effective and reliable regenerative life support system (RLSS) provided the foundation for the characterization of organisms or 'biological processors' in engineering terms and a methodology was developed for their integration into an engineered ecological LSS in order to minimize the mass flow imbalances between consumers and producers. These techniques for the design and the evaluation of bioregenerative LSS have now been integrated into a lunar base reference mission, emphasizing the phased implementation of components of such a BLSS. In parallel, a designers handbook was compiled from knowledge and experience gained during past design projects to aid in the design and planning of future space missions requiring advanced RLSS technologies. The lunar base reference mission addresses in particular the phased implementation and integration of BLS parts and includes the resulting infrastructure burdens and needs such as mass, power, volume, and structural requirements of the LSS. Also, operational aspects such as manpower requirements and the possible need and application of 'robotics' were addressed
Multi-Antenna Techniques for Next Generation Cellular Communications
Future cellular communications are expected to offer substantial improvements for the pre- existing mobile services with higher data rates and lower latency as well as pioneer new types of applications that must comply with strict demands from a wider range of user types. All of these tasks require utmost efficiency in the use of spectral resources. Deploying multiple antennas introduces an additional signal dimension to wireless data transmissions, which provides a significant alternative solution against the plateauing capacity issue of the limited available spectrum. Multi-antenna techniques and the associated key enabling technologies possess unquestionable potential to play a key role in the evolution of next generation cellular systems.
Spectral efficiency can be improved on downlink by concurrently serving multiple users with high-rate data connections on shared resources. In this thesis optimized multi-user multi-input multi-output (MIMO) transmissions are investigated on downlink from both filter design and resource allocation/assignment points of view. Regarding filter design, a joint baseband processing method is proposed specifically for high signal-to-noise ratio (SNR) conditions, where the necessary signaling overhead can be compensated for. Regarding resource scheduling, greedy- and genetic-based algorithms are proposed that demand lower complexity with large number of resource blocks relative to prior implementations.
Channel estimation techniques are investigated for massive MIMO technology. In case of channel reciprocity, this thesis proposes an overhead reduction scheme for the signaling of user channel state information (CSI) feedback during a relative antenna calibration. In addition, a multi-cell coordination method is proposed for subspace-based blind estimators on uplink, which can be implicitly translated to downlink CSI in the presence of ideal reciprocity. Regarding non-reciprocal channels, a novel estimation technique is proposed based on reconstructing full downlink CSI from a select number of dominant propagation paths. The proposed method offers drastic compressions in user feedback reports and requires much simpler downlink training processes.
Full-duplex technology can provide up to twice the spectral efficiency of conventional resource divisions. This thesis considers a full-duplex two-hop link with a MIMO relay and investigates mitigation techniques against the inherent loop-interference. Spatial-domain suppression schemes are developed for the optimization of full-duplex MIMO relaying in a coverage extension scenario on downlink. The proposed methods are demonstrated to generate data rates that closely approximate their global bounds
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