46 research outputs found
Dual-based bounds for resource allocation in zero-forcing beamforming OFDMA-SDMA systems
We consider multi-antenna base stations using orthogonal frequency-division multiple access and space division multiple access techniques to serve single-antenna users. Some users, called real-time users, have minimum rate requirements and must be served in the current time slot while others, called non real-time users, do not have strict timing constraints and are served on a best-effort basis. The resource allocation (RA) problem is to find the assignment of users to subcarriers and the transmit beamforming vectors that maximize the total user rates subject to power and minimum rate constraints. In general, this is a nonlinear and non-convex program and the zero-forcing technique used here makes it integer as well, exact optimal solutions cannot be computed in reasonable time for realistic cases. For this reason, we present a technique to compute both upper and lower bounds and show that these are quite close for some realistic cases. First, we formulate the dual problem whose optimum provides an upper bound to all feasible solutions. We then use a simple method to get a primal-feasible point starting from the dual optimal solution, which is a lower bound on the primal optimal solution. Numerical results for several cases show that the two bounds are close so that the dual method can be used to benchmark any heuristic used to solve this problem. As an example, we provide numerical results showing the performance gap of the well-known weight adjustment method and show that there is considerable room for improvement
Efficient Methods for Resource Allocation in Multi-Antenna Orthogonal Frequency-Division Multiple Access (OFDMA) Systems
Résumé
Dans cette thĂšse, nous proposons une solution au problĂšme dâallocation de ressources dâun systĂšme MISO (Multiple Input Multiple Output) â OFDMA (Orthogonal Frequency Division Multiplexing Access) supportant des usagers requĂ©rant un dĂ©bit de transmission minimal. Ce problĂšme peut ĂȘtre modĂ©lisĂ© comme une optimisation non-linĂ©aire mixte avec variables entiĂšres. Nous nous sommes intĂ©ressĂ©s dans cette thĂšse Ă diverses mĂ©thodes permettant la rĂ©solution dâun tel problĂšme.
La premiĂšre approche Ă©tudiĂ©e utilise une mĂ©thode hors-ligne et permet dâobtenir une solution quasi-optimale qui peut ĂȘtre utilisĂ©e comme rĂ©fĂ©rences pour Ă©valuer la performance dâalgorithmes heuristiques pouvant ĂȘtre rĂ©alises en temps rĂ©el. Pour ce faire, nous cherchons une allocation rĂ©alisable en se basant sur la solution optimale du problĂšme dual. Nous obtenons la fonction duale et trouvons la solution Ă lâaide dâun algorithme itĂ©ratif Ă sous-gradient. Cette solution permet dâobtenir une borne supĂ©rieure Ă la solution optimale. Dâautre part, nous dĂ©veloppons une heuristique basĂ©e sur la solution du problĂšme dual pour obtenir une solution rĂ©alisable du problĂšme primaire qui constitue une borne inferieure Ă la solution optimale. Ces bornes nous permettent dâĂ©tablir que lâĂ©cart de dualitĂ© est petit pour les configurations Ă©tudiĂ©es et elles peuvent servir de rĂ©fĂ©rence pour lâĂ©valuation de performances des algorithmes heuristiques. La formulation duale nous fournit aussi une meilleure comprĂ©hension du sujet en Ă©tablissant un lien entre la rĂ©alisabilitĂ© de lâallocation de ressources et les dĂ©bits minimaux requis par les usagers.
Afin dâobtenir des mĂ©thodes de rĂ©solution plus pratiques pouvant ĂȘtre rĂ©alisĂ©es en temps rĂ©el, nous proposons deux heuristiques ayant une faible complexitĂ© et permettant dâatteindre des performances assez prĂ©s des performances optimales. Les performances ainsi obtenues sont lĂ©gĂšrement moins bonnes que celles dâautres algorithmes quâon retrouve dans la littĂ©rature, mais supportent une plus grande plage de valeurs de dĂ©bit minimal tout en rĂ©duisant la complexitĂ© de lâalgorithme dâallocation de ressources de plusieurs ordres de grandeur. LâĂ©cart entre la solution trouvĂ©e par ces algorithmes heuristiques et la borne supĂ©rieure duale est relativement faible. Par exemple, lâĂ©cart est de 10.7% en moyenne pour toutes les configurations Ă©tudiĂ©es. Lâaugmentation dans la plage de dĂ©bits minimaux supportes compares avec les mĂ©thodes disponibles dans la littĂ©rature est de 14.6% en moyenne. Cette amĂ©lioration est obtenue en considĂ©rant les variables duals de contrainte de dĂ©bits minimaux dans lâallocation de puissance aux usagers. Lâalgorithme heuristique proposĂ© sĂ©lectionne un ensemble dâusagers pour chaque sous-porteuse, mais contrairement aux autres mĂ©thodes proposĂ©es prĂ©cĂ©demment, lâalgorithme considĂšre lâensemble des usagers avec des contraintes de dĂ©bits minimaux dans la rĂ©assignation des sous-porteuses pour sâassurer que le niveau de service requis est rencontre. Suite Ă la sĂ©lection des ensembles dâusagers, un problĂšme dâallocation de puissance convexe est rĂ©solu. Des algorithmes permettant de rĂ©soudre efficacement et en un temps moindre les problĂšmes dâassignation des sous-porteuses aux usagers et dâallocation de puissance sont proposĂ©es dans cette thĂšse.
Finalement, nous Ă©tudions aussi de quelle façon ces algorithmes peuvent ĂȘtre utilises pour rĂ©soudre le problĂšme dâallocation de ressources dans une cellule utilisant la technologie LTE (Long Term Evolution)-Advanced. Les mĂ©thodes Ă©tudiĂ©es dans cette thĂšse font partie dâun nouvel ensemble dâalgorithmes nĂ©cessaires pour supporter des applications temps rĂ©el Ă haut dĂ©bit et a lâefficacitĂ© spectrale requise dans les prochains rĂ©seaux dâaccĂšs sans-fil de quatriĂšme gĂ©nĂ©ration.----------Abstract In this dissertation, we solve the Resource Allocation (RA) problem of a Multiple Input Single Output (MISO) â Orthogonal Frequency Division Multiplexing Access (OFDMA) sysÂŹtem supporting minimum rates. This problem can be modelled as a non-linear Mixed Integer Program (NLMIP). We are interested in various kinds of methods to solve this problem. First, our focus is on an oïŹ-line method that gives near-optimal solutions that serve as benchmark for more practical methods. For this purpose, we propose a method based on the optimal solution of the dual problem. We obtain a dual function and solve the dual problem through subgradient iterations. Then, we find upper and lower bounds for the optimal solution and verify that the duality gap is small for the system configurations studied. Therefore, the dual optimal serves as a reference for any feasible solution produced by the heuristic methods. The dual formulation also gives a better insight into the problem, as it shows us the relation between the problemâs feasibility and the minimum rate requirements. To obtain more practical methods, we propose two heuristics that have very low com-putational complexity and give performances not far from the optimal. We compare their performance against other methods proposed in the literature and find that they give a somewhat lower performance, but support a wider range of minimum rates while reducing the computational complexity of the algorithm by several orders of magnitude. The gap beÂŹtween the objective achieved by the heuristics and the upper bound given by the dual optimal is not large. For example, in our experiments this gap is 10.7% averaging over all performed numerical evaluations for all system configurations. The increase in the range of the supÂŹported minimum rates when compared with the method reported in the literature is 14.6% on average. This increase is achieved by considering the rate constraint dual variables in the user power allocation stage. The proposed heuristics select a set of users for each subcarrier, but contrary to other reported methods used to solve the throughput maximization problem, they consider the set of real-time (RT) users to ensure that their minimum rate requirements are met. Then, they solve a power allocation problem for ïŹx subcarrier assignment, which is a convex problem that is simpler to solve. We use efficient algorithms for the subcarrier assignment and power allocation stages to solve the problem much quicker. Finally, we adapt the algorithms to solve the RA problem in a single cell using LTE (Long Term Evolution)âAdvanced technology. The methods examined in this dissertation are part of the new set of algorithms needed to support the high rate applications and spectral efficiency required in the wireless access of upcoming 4G networks
Advances in Multi-User Scheduling and Turbo Equalization for Wireless MIMO Systems
Nach einer Einleitung behandelt Teil 2 Mehrbenutzer-Scheduling fĂŒr die
AbwÀrtsstrecke von drahtlosen MIMO Systemen mit einer Sendestation und
kanaladaptivem precoding: In jeder Zeit- oder Frequenzressource kann eine
andere Nutzergruppe gleichzeitig bedient werden, rÀumlich getrennt durch
unterschiedliche Antennengewichte. Nutzer mit korrelierten KanÀlen sollten
nicht gleichzeitig bedient werden, da dies die rÀumliche Trennbarkeit
erschwert. Die Summenrate einer Nutzermenge hÀngt von den Antennengewichten
ab, die wiederum von der Nutzerauswahl abhÀngen. Zur Entkopplung des
Problems schlÀgt diese Arbeit Metriken vor basierend auf einer geschÀtzten
Rate mit ZF precoding. Diese lÀsst sich mit Hilfe von wiederholten
orthogonalen Projektionen abschÀtzen, wodurch die Berechnung von
Antennengewichten beim Scheduling entfÀllt. Die RatenschÀtzung kann
basierend auf momentanen Kanalmessungen oder auf gemittelter Kanalkenntnis
berechnet werden und es können Datenraten- und Fairness-Kriterien
berĂŒcksichtig werden. Effiziente Suchalgorithmen werden vorgestellt, die
die gesamte Systembandbreite auf einmal bearbeiten können und zur
KomplexitĂ€tsreduktion die Lösung in Zeit- und Frequenz nachfĂŒhren können.
Teil 3 zeigt wie mehrere Sendestationen koordiniertes Scheduling und
kooperative Signalverarbeitung einsetzen können. Mittels orthogonalen
Projektionen ist es möglich, Inter-Site Interferenz zu schÀtzen, ohne
Antennengewichte berechnen zu mĂŒssen. Durch ein Konzept virtueller Nutzer
kann der obige Scheduling-Ansatz auf mehrere Sendestationen und sogar
Relays mit SDMA erweitert werden. Auf den benötigten Signalisierungsaufwand
wird kurz eingegangen und eine Methode zur SchÀtzung der Summenrate eines
Systems ohne Koordination besprochen. Teil4 entwickelt Optimierungen fĂŒr
Turbo Entzerrer. Diese Nutzen Signalkorrelation als Quelle von Redundanz.
Trotzdem kann eine Kombination mit MIMO precoding sinnvoll sein, da bei
Annahme realistischer Fehler in der Kanalkenntnis am Sender keine optimale
InterferenzunterdrĂŒckung möglich ist. Mit Hilfe von EXIT Charts wird eine
neuartige Methode zur adaptiven Nutzung von a-priori-Information zwischen
Iterationen entwickelt, die die Konvergenz verbessert. Dabei wird gezeigt,
wie man semi-blinde KanalschĂ€tzung im EXIT chart berĂŒcksichtigen kann.
In Computersimulationen werden alle Verfahren basierend auf
4G-Systemparametern ĂŒberprĂŒft.After an introduction, part 2 of this thesis deals with downlink multi-user
scheduling for wireless MIMO systems with one transmitting station
performing channel adaptive precoding:Different user subsets can be served
in each time or frequency resource by separating them in space with
different antenna weight vectors. Users with correlated channel matrices
should not be served jointly since correlation impairs the spatial
separability.The resulting sum rate for each user subset depends on the
precoding weights, which in turn depend on the user subset. This thesis
manages to decouple this problem by proposing a scheduling metric based on
the rate with ZF precoding such as BD, written with the help of orthogonal
projection matrices. It allows estimating rates without computing any
antenna weights by using a repeated projection approximation.This rate
estimate allows considering user rate requirements and fairness criteria
and can work with either instantaneous or long term averaged channel
knowledge.Search algorithms are presented to efficiently solve user
grouping or selection problems jointly for the entire system bandwidth
while being able to track the solution in time and frequency for complexity
reduction.
Part 3 shows how multiple transmitting stations can benefit from
cooperative scheduling or joint signal processing. An orthogonal projection
based estimate of the inter-site interference power, again without
computing any antenna weights, and a virtual user concept extends the
scheduling approach to cooperative base stations and finally included SDMA
half-duplex relays in the scheduling.Signalling overhead is discussed and a
method to estimate the sum rate without coordination.
Part 4 presents optimizations for Turbo Equalizers. There, correlation
between user signals can be exploited as a source of redundancy.
Nevertheless a combination with transmit precoding which aims at reducing
correlation can be beneficial when the channel knowledge at the transmitter
contains a realistic error, leading to increased correlation. A novel
method for adaptive re-use of a-priori information between is developed to
increase convergence by tracking the iterations online with EXIT charts.A
method is proposed to model semi-blind channel estimation updates in an
EXIT chart.
Computer simulations with 4G system parameters illustrate the methods using realistic channel models.Im Buchhandel erhÀltlich:
Advances in Multi-User Scheduling and Turbo Equalization for Wireless MIMO Systems / Fuchs-Lautensack,Martin
Ilmenau: ISLE, 2009,116 S.
ISBN 978-3-938843-43-