30 research outputs found
On Linear Transmission Systems
This thesis is divided into two parts. Part I analyzes the information rate of single antenna, single carrier linear modulation systems. The information rate of a system is the maximum number of bits that can be transmitted during a channel usage, and is achieved by Gaussian symbols. It depends on the underlying pulse shape in a linear modulated signal and also the signaling rate, the rate at which the Gaussian symbols are transmitted. The object in Part I is to study the impact of both the signaling rate and the pulse shape on the information rate. Part II of the thesis is devoted to multiple antenna systems (MIMO), and more specifically to linear precoders for MIMO channels. Linear precoding is a practical scheme for improving the performance of a MIMO system, and has been studied intensively during the last four decades. In practical applications, the symbols to be transmitted are taken from a discrete alphabet, such as quadrature amplitude modulation (QAM), and it is of interest to find the optimal linear precoder for a certain performance measure of the MIMO channel. The design problem depends on the particular performance measure and the receiver structure. The main difficulty in finding the optimal precoders is the discrete nature of the problem, and mostly suboptimal solutions are proposed. The problem has been well investigated when linear receivers are employed, for which optimal precoders were found for many different performance measures. However, in the case of the optimal maximum likelihood (ML) receiver, only suboptimal constructions have been possible so far. Part II starts by proposing new novel, low complexity, suboptimal precoders, which provide a low bit error rate (BER) at the receiver. Later, an iterative optimization method is developed, which produces precoders improving upon the best known ones in the literature. The resulting precoders turn out to exhibit a certain structure, which is then analyzed and proved to be optimal for large alphabets
Constant Envelope Precoding for Large Antenna Arrays
5G, the new generation of mobile communications, is expected to provide huge improvements in spectral efficiency and energy efficiency. Specifically, it has been proven that the adoption of large antenna arrays is an efficient means to improve the system performance in both of these efficiency measures. For these reasons, the deployment of base stations with large amount of antennas has attracted a substantial amount of research interest over the recent years. However, when pure digital beamforming is pursued in large array system context, a large number of transmitter and receiver chains must also be implemented, increasing the complexity and costs of the deployment.
In general, power consumption of the cellular network is recognized as a major concern. Radio transmitters tend to be really power hungry, especially because of the potential energy inefficiency of their power amplifiers. Due to the characteristics of the current and future waveforms utilized in wireless communications, power amplifiers need to work in a relatively linear regime in order not to distort the signal, making the energy efficiency of such highly linear amplifiers to be rather low. If power amplifiers were capable of working in the nonlinear regime without degrading system performance, their energy efficiency could be notably increased, resulting in considerable savings in energy, costs and system complexity.
In this Thesis, the development and evaluation of a constant envelope spatial precoder is being addressed. The precoder is capable of generating a symbol-rate constant envelope signal, which despite pulse-shape filtering yields substantial robustness against the nonlinearities of power amplifiers. This facilitates pushing power amplifiers into heavily nonlinear regime, with the consequent increase in their energy efficiency. At the same time, the precoder is able to perform spatial beamforming processing in order to mitigate the multi-user interference due to spatial multiplexing. It is assumed that the number of antennas in the base station is much larger than the number of simultaneously scheduled users, implying that large-scale MU-MIMO scenarios are considered, which allows us to exploit the additional degrees of freedom to perform waveform shaping. For the sake of evaluating the proposed precoder performance, different metrics such as PAPR, BER, multi-user interference and beamforming gain are compared to those of currently used precoding techniques.
The obtained results indicate that the studied constant-envelope precoder can facilitate running the PA units of the large-array system in heavily nonlinear region, without inducing substantial nonlinear distortion, while also simultaneously providing good spatial multiplexing and beamforming characteristics. These, in turn, then facilitate larger received SINRs for the scheduled users, and therefore larger system throughputs and a more efficient utilization of the power amplifiers
Downlink Training Sequence Design Based on Achievable Sum Rate Maximisation in FDD Massive MIMO Systems
This thesis addresses the key technical challenges related to the design of the downlink (DL) training sequence for the channel state information (CSI) estimation in frequency division duplex (FDD) massive multiple-input multiple-output (massive MIMO) systems with single- stage precoding and limited coherence time. To this end, a computationally feasible solutions for designing the DL training sequences are proposed and novel closed-form solutions for the optimum pilot length that maximises the sum rate with single-stage precoding and limited coherence time are derived. The results in this thesis show that for practical base station (BS) array sizes of N 50 the diversity of spatial correlations between multiple users achieved more than 40 bits/s/Hz improvement in the sum rate of the regularised zero forcing (RZF) precoder in comparison to uncorrelated channels with identical channel covariance matrices. Finally, the analyses of the complexity results in this thesis show that more than four orders-of-magnitude reduction in the computational complexity is achieved using the superposition design, which signifies the feasibility of this approach for practical implementations compared with state-of-the-art training designs. An asymptotic random matrix theory along with the P-degrees of freedom (P-DoF) channel model are adopted in this thesis to develop an analytical closed-form solution for the sum rate of the beamforming (BF) and RZF precoders, with perfect and imperfect CSI estimation. Excellent agreement between the numerical, analytical and simulated results are obtained, which underpins the contributions of this research. Overall, the proposed approaches open up the possibility for FDD massive MIMO systems operating in a general scenario of single-stage precoding and more realistic channel conditions, particularly channel correlation and limited coherence time
Linear system design for compression and fusion
2013 Fall.Includes bibliographical references.This is a study of measurement compression and fusion design. The idea common to both problems is that measurements can often be linearly compressed into lower-dimensional spaces without introducing too much excess mean-squared error or excess volume in a concentration ellipse. The question is how to design the compression to minimize the excesses at any given dimension. The first part of this work is motivated by sensing and wireless communication, where data compression or dimension reduction may be used to reduce the required communication bandwidth. The high-dimensional measurements are converted into low-dimensional representations through linear compression. Our aim is to compress a noisy measurement, allowing for the fact that the compressed measurement will be transmitted over a noisy channel. We review optimal compression with no transmission noise and show its connection with canonical coordinates. When the compressed measurement is transmitted with noise, we give the closed-form expression for the optimal compression matrix with respect to the trace and determinant of the error covariance matrix. We show that the solutions are canonical coordinate solutions, scaled by coefficients which account for canonical correlations and transmission noise variance, followed by a coordinate transformation into the sub-dominant invariant subspace of the channel noise. The second part of this work is a problem of integrating multiple sources of measurements. We consider two multiple-input-multiple-output channels, a primary channel and a secondary channel, with dependent input signals. The primary channel carries the signal of interest, and the secondary channel carries a signal that shares a joint distribution with the primary signal. The problem of particular interest is designing the secondary channel, with a fixed primary channel. We formulate the problem as an optimization problem, in which the optimal secondary channel maximizes an information-based criterion. An analytic solution is provided in a special case. Two fast-to-compute algorithms, one extrinsic and the other intrinsic, are proposed to approximate the optimal solutions in general cases. In particular, the intrinsic algorithm exploits the geometry of the unit sphere, a manifold embedded in Euclidean space. The performances of the proposed algorithms are examined through a simulation study. A discussion of the choice of dimension for the secondary channel is given, leading to rules for dimension reduction
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
Resource allocation and feedback in wireless multiuser networks
This thesis focuses on the design of algorithms for resource allocation and feedback in wireless multiuser and heterogeneous networks. In particular, three key design challenges expected to have a major impact on future wireless networks are considered: cross-layer scheduling; structured quantization codebook design for MU-MIMO networks with limited feedback; and resource allocation to provide physical layer security. The first design challenge is cross-layer scheduling, where policies are proposed for two network architectures: user scheduling in single-cell multiuser networks aided by a relay; and base station (BS) scheduling in CoMP. These scheduling policies are then analyzed to guarantee satisfaction of three performance metrics: SEP; packet delay; and packet loss probability (PLP) due to buffer overflow. The concept of the Ď„-achievable PLP region is also introduced to explicitly describe the tradeoff in PLP between different users. The second design challenge is structured quantization codebook design in wireless networks with limited feedback, for both MU-MIMO and CoMP. In the MU-MIMO network, two codebook constructions are proposed, which are based on structured transformations of a base codebook. In the CoMP network, a low-complexity construction is proposed to solve the problem of variable codebook dimensions due to changes in the number of coordinated BSs. The proposed construction is shown to have comparable performance with the standard approach based on a random search, while only requiring linear instead of exponential complexity. The final design challenge is resource allocation for physical layer security in MU-MIMO. To guarantee physical layer security, the achievable secrecy sum-rate is explicitly derived for the regularized channel inversion (RCI) precoder. To improve performance, power allocation and precoder design are jointly optimized using a new algorithm based on convex optimization techniques
Resource allocation and feedback in wireless multiuser networks
This thesis focuses on the design of algorithms for resource allocation and feedback in wireless multiuser and heterogeneous networks. In particular, three key design challenges expected to have a major impact on future wireless networks are considered: cross-layer scheduling; structured quantization codebook design for MU-MIMO networks with limited feedback; and resource allocation to provide physical layer security. The first design challenge is cross-layer scheduling, where policies are proposed for two network architectures: user scheduling in single-cell multiuser networks aided by a relay; and base station (BS) scheduling in CoMP. These scheduling policies are then analyzed to guarantee satisfaction of three performance metrics: SEP; packet delay; and packet loss probability (PLP) due to buffer overflow. The concept of the Ď„-achievable PLP region is also introduced to explicitly describe the tradeoff in PLP between different users. The second design challenge is structured quantization codebook design in wireless networks with limited feedback, for both MU-MIMO and CoMP. In the MU-MIMO network, two codebook constructions are proposed, which are based on structured transformations of a base codebook. In the CoMP network, a low-complexity construction is proposed to solve the problem of variable codebook dimensions due to changes in the number of coordinated BSs. The proposed construction is shown to have comparable performance with the standard approach based on a random search, while only requiring linear instead of exponential complexity. The final design challenge is resource allocation for physical layer security in MU-MIMO. To guarantee physical layer security, the achievable secrecy sum-rate is explicitly derived for the regularized channel inversion (RCI) precoder. To improve performance, power allocation and precoder design are jointly optimized using a new algorithm based on convex optimization techniques
Analysis and system design of a cooperative wireless network based on interference alignment
L'Interference Alignment è una delle più nuove tecniche di gestione dell' interferenza ed ha l'obiettivo di allineare al ricevitore i segnali interferenti, ottenendo così migliori prestazioni in termini di throughput. Al momento ci sono solo pochi studi riguardo questa tecnica in reti cooperative. In letteratura tutti i migliori risultati sono ottenuti sotto condizioni ideali, come fast-fading, canali completamente incorrelati, slot temporali arbitrariamente lunghi. Noi intendiamo analizzare lo scenario in condizioni normali e reali, ritenendo che proprio la cooperazione permetta di approssimare meglio le condizioni ideali. Il nostro intentento è di verificare se, tramite la cooperazione, sono ottenibili migliori risultati in termini di throughput e velocità di convergenza. All'inizio del nostro lavoro, studiamo e analizzaiamo vari scenari, estendendo i modelli correnti sia da un punto di vista temporale che dal punto di vista spaziale, il che significa permettere al sistema di poter lavorare su più di uno slot, introducendo al contempo entità cooperative. Poichè è difficile ottenere risultati in forma chiusa, preferiamo analizzare diversi setup cooperativi tramite simulazioni impieganti algoritmi iterativi. Quando possibile, cercheremo di generalizzare i risultati raggiunti empiricamente in maniera analitica. Dai risultati ottenuti, è difficile poter afferamare che un miglioramento capacitivo sia raggiungibile, perchè la correlazione di canale, anche in scenari cooperativi, limita irremidiabilmente le prestazioni. Tuttavia alcuni risultati rigurado la capacità sono comunque possibili. Nello specifico, se in scenari cooperativi sono poste ulteriori ipotesi di mutua conoscenza del canale da parte delle sorgenti, le configurazioni in queste condizioni ottengono migliori proprietà , riuscendo ad incrementare in questa maniera il proprio throughput. Infine si può affermare che la cooperazione è utile per migliorare la velocità di convergenza degli algoritmi di Interference Alignment e ciò è dimostrato non solo empiricamente, tramite le simulazioni, ma anche attraverso una interpretazione analitica. Riteniamo che specialmente quest'ultimo risultato possa essere sfruttato ed essere utile come miglioramento di applicazioni che utilizzano Interference Alignmen
A tutorial on the characterisation and modelling of low layer functional splits for flexible radio access networks in 5G and beyond
The centralization of baseband (BB) functions in a radio access network (RAN) towards data processing centres is receiving increasing interest as it enables the exploitation of resource pooling and statistical multiplexing gains among multiple cells, facilitates the introduction of collaborative techniques for different functions (e.g., interference coordination), and more efficiently handles the complex requirements of advanced features of the fifth generation (5G) new radio (NR) physical layer, such as the use of massive multiple input multiple output (MIMO). However, deciding the functional split (i.e., which BB functions are kept close to the radio units and which BB functions are centralized) embraces a trade-off between the centralization benefits and the fronthaul costs for carrying data between distributed antennas and data processing centres. Substantial research efforts have been made in standardization fora, research projects and studies to resolve this trade-off, which becomes more complicated when the choice of functional splits is dynamically achieved depending on the current conditions in the RAN. This paper presents a comprehensive tutorial on the characterisation, modelling and assessment of functional splits in a flexible RAN to establish a solid basis for the future development of algorithmic solutions of dynamic functional split optimisation in 5G and beyond systems. First, the paper explores the functional split approaches considered by different industrial fora, analysing their equivalences and differences in terminology. Second, the paper presents a harmonized analysis of the different BB functions at the physical layer and associated algorithmic solutions presented in the literature, assessing both the computational complexity and the associated performance. Based on this analysis, the paper presents a model for assessing the computational requirements and fronthaul bandwidth requirements of different functional splits. Last, the model is used to derive illustrative results that identify the major trade-offs that arise when selecting a functional split and the key elements that impact the requirements.This work has been partially funded by Huawei Technologies. Work by X. Gelabert and B. Klaiqi is partially funded by the European Union's Horizon Europe research and innovation programme (HORIZON-MSCA-2021-DN-0) under the Marie Skłodowska-Curie grant agreement No 101073265. Work by J. Perez-Romero and O. Sallent is also partially funded by the Smart Networks and Services Joint Undertaking (SNS JU) under the European Union’s Horizon Europe research and innovation programme under Grant Agreements No. 101096034 (VERGE project) and No. 101097083 (BeGREEN project) and by the Spanish Ministry of Science and Innovation MCIN/AEI/10.13039/501100011033 under ARTIST project (ref. PID2020-115104RB-I00). This last project has also funded the work by D. Campoy.Peer ReviewedPostprint (author's final draft