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Modélisation spatio-temporelle ultra-large bande du canal de transmission pour réseaux corporels sans filvan Roy, Stéphane 22 December 2010 (has links)
Les avancées technologiques de ces dernières années, combinées au succès avéré et toujours croissant des communications sans fil, ont tout naturellement donné naissance à un nouveau type de réseaux sans fil, communément appelés Body Area networks. A terme, ces réseaux corporels sans fil doivent permettre à un ensemble de senseurs bio-médicaux répartis sur le corps humain de communiquer, soit pour échanger des informations en vue d'un traitement en temps réel du patient, soit pour enregistrer des données physiologiques en vue d'une analyse ultérieure.
L’objectif de cette Thèse vise la réduction de la consommation énergétique au niveau des senseurs de sorte à leur garantir une autonomie de quelques mois, voire de quelques années. En réponse à cette contrainte énergétique, une association innovante de deux technologies émergentes est proposée, à savoir une combinaison des transmissions à ultra-large bande aux systèmes à multiples antennes. Une nouvelle architecture pour les réseaux corporels sans fil est donc envisagée pour laquelle les performances doivent être évaluées. Notre principale contribution à cet objectif consiste en la proposition d'une modélisation spatio-temporelle complète du canal de transmission dans le cadre de senseurs répartis autour du corps. Cette modélisation fait appel à la définition de nouveaux modèles, l'élaboration d'outils spécifiques d'extraction de paramètres et une compréhension fine des mécanismes de propagation liés à la proximité du corps humain. Ce manuscrit présente les résultats majeurs de nos recherches en cette matière.
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Low-complexity list detection algorithms for the multiple-input multiple-output channelMilliner, David Louis 20 October 2009 (has links)
Modern communication systems demand ever-increasing data rates. Meeting this increased demand is not easy due to regulation and fundamental physical constraints. The utilization of more than one antenna at both the transmitter and receiver produces a multiple-input multiple-output (MIMO) channel, thereby enabling (under certain channel conditions) increased data rates without the need for increased bandwidth or transmission power. Concurrent with this increase in bandwidth is an increase in the receiver's computational complexity which, for a brute-force detector, increases exponentially. For receivers that possess error correcting capabilities, the problem of constructing a detector with low computational complexity that allows for near-exact a posteriori detection is challenging for transmission schemes employing even a modest number of transmit antennas and modulation alphabet sizes. The focus of this dissertation is on the construction of MIMO detection algorithms with low and fixed computational complexity. Specifically, the detection algorithms in this dissertation generate a list of potential transmission vectors resulting in realizable communication receivers with low and fixed computational complexity combined with low error rate performance in both coded and uncoded systems.
A key contribution in this dissertation is a breadth-first fixed-complexity algorithm known as the smart-ordered and candidate-adding algorithm that achieves a desirable performance-complexity tradeoff. This algorithm requires only a single pass of a search tree to find its list of transmission vectors. We then construct a framework within which we classify a large class of breadth-first detection algorithms.
The design of receiver algorithms for MIMO systems employing space-time codes and error correction is an important area of study. In this dissertation we propose a low and fixed computational complexity algorithm for an increasingly significant algebraic space-time code known as the golden code.
The notion of computational complexity is critical in the design of practical MIMO receivers. We provide an analysis of computational complexity in relation to list-based soft-output detection where, in some instances, bounds are placed on the computational complexity of MIMO detection. For this analysis we utilize a metric known as the number of branch metric computations.
The value at which the log-likelihood ratio (LLR) of conditional probabilities for a transmitted bit being either a 1 or a 0 is 'clipped' has an impact on a system's error rate performance. We propose a new approach for determining LLR clipping levels that, in contrast to prior approaches which clip to a predetermined fixed LLR clipping level, exploits channel state information to improve the error rate performance of suboptimal detection algorithms.
Orthogonal frequency-division (OFDM) multiplexing is an effective technique for combating frequency-selective wideband communication channels. It is common practice for MIMO-OFDM detectors to implement the same detector at each subcarrier, in which case the overall performance is dominated by the weakest subcarrier. We propose a hard-output list detection receiver strategy for MIMO-OFDM channels called nonuniform computational complexity allocation, whereby the receiver adapts the computational resources of the MIMO detector at each subcarrier to match a metric of the corresponding channel quality. The proposed nonuniform algorithm improves performance over uniform allocation.
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Coordinated Beamforming and Common Message Decoding for Intercell Interference Mitigation in Multicell NetworksDahrouj, Hayssam 15 February 2011 (has links)
Conventional multicell wireless systems operate with out-of-cell interference treated as background noise; consequently, their performance faces two major limitations: 1)Signal processing is performed on a per-cell basis; and 2)Intercell interference detection is infeasible as intercell interference, although significantly above the noise level, is typically quite weak. In this thesis, we consider a multicell downlink scenario, where base-stations are equipped with multiple transmit antennas, the remote users are equipped with a single antenna, and multiple remote users are active simultaneously via spatial division multiplexing. We propose solutions for the above limitations by considering techniques for mitigating interference.
The first part of the thesis proposes solutions for the first limitation. It considers the benefit of coordinating base-stations across multiple cells, where
multiple base-stations may jointly optimize their respective beamformers to improve the overall system performance. It focuses on the design criteria of minimizing either the total weighted transmitted power or the maximum per-antenna power across the base-stations subject to signal-to-interference-and-noise-ratio (SINR) constraints at the remote users. The main contribution of this part is an efficient algorithm for finding the joint globally optimal beamformers across all base-stations. The proposed algorithm is based on a generalization of uplink-downlink duality to the multicell setting using the Lagrangian duality theory. An important feature is that it naturally leads to a distributed implementation in time-division duplex (TDD) systems. Simulation results suggest that coordinating the beamforming vectors alone already provides appreciable performance improvements as compared to the conventional per-cell optimized network.
The second part of the thesis considers the transmission of both private and common messages for the sole purpose of intercell
interference mitigation. It solves the issues of the second limitation mentioned above. It considers the benefit of designing
decodable interference signals by allowing common-private message splitting at the transmitter and common message decoding by users in adjacent cells. It solves a network optimization problem of jointly determining the appropriate users in adjacent cells for
rate splitting, the optimal beamforming vectors for both common and private messages, and the optimal common-private rates to minimize the total transmit power across the base-stations subject to service rate requirements for remote users. Observe that for fixed user selection and fixed common-private rate splitting, the optimization of beamforming vectors can be performed using a semidefinite programming approach. Further, this part of the thesis proposes a heuristic user-selection and rate splitting strategy to maximize the benefit of common message decoding. This part proposes a heuristic algorithm to characterize the improvement in the feasible rates with common-message decoding. Simulation results show that common message decoding can significantly improve both the total transmit power and the feasibility region for cell-edge users when base-stations are closely spaced from each other.
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Coordinated Beamforming and Common Message Decoding for Intercell Interference Mitigation in Multicell NetworksDahrouj, Hayssam 15 February 2011 (has links)
Conventional multicell wireless systems operate with out-of-cell interference treated as background noise; consequently, their performance faces two major limitations: 1)Signal processing is performed on a per-cell basis; and 2)Intercell interference detection is infeasible as intercell interference, although significantly above the noise level, is typically quite weak. In this thesis, we consider a multicell downlink scenario, where base-stations are equipped with multiple transmit antennas, the remote users are equipped with a single antenna, and multiple remote users are active simultaneously via spatial division multiplexing. We propose solutions for the above limitations by considering techniques for mitigating interference.
The first part of the thesis proposes solutions for the first limitation. It considers the benefit of coordinating base-stations across multiple cells, where
multiple base-stations may jointly optimize their respective beamformers to improve the overall system performance. It focuses on the design criteria of minimizing either the total weighted transmitted power or the maximum per-antenna power across the base-stations subject to signal-to-interference-and-noise-ratio (SINR) constraints at the remote users. The main contribution of this part is an efficient algorithm for finding the joint globally optimal beamformers across all base-stations. The proposed algorithm is based on a generalization of uplink-downlink duality to the multicell setting using the Lagrangian duality theory. An important feature is that it naturally leads to a distributed implementation in time-division duplex (TDD) systems. Simulation results suggest that coordinating the beamforming vectors alone already provides appreciable performance improvements as compared to the conventional per-cell optimized network.
The second part of the thesis considers the transmission of both private and common messages for the sole purpose of intercell
interference mitigation. It solves the issues of the second limitation mentioned above. It considers the benefit of designing
decodable interference signals by allowing common-private message splitting at the transmitter and common message decoding by users in adjacent cells. It solves a network optimization problem of jointly determining the appropriate users in adjacent cells for
rate splitting, the optimal beamforming vectors for both common and private messages, and the optimal common-private rates to minimize the total transmit power across the base-stations subject to service rate requirements for remote users. Observe that for fixed user selection and fixed common-private rate splitting, the optimization of beamforming vectors can be performed using a semidefinite programming approach. Further, this part of the thesis proposes a heuristic user-selection and rate splitting strategy to maximize the benefit of common message decoding. This part proposes a heuristic algorithm to characterize the improvement in the feasible rates with common-message decoding. Simulation results show that common message decoding can significantly improve both the total transmit power and the feasibility region for cell-edge users when base-stations are closely spaced from each other.
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Modélisation spatio-temporelle ultra-large bande du canal de transmission pour réseaux corporels sans filVan Roy, Stéphane 22 December 2010 (has links)
Les avancées technologiques de ces dernières années, combinées au succès avéré et toujours croissant des communications sans fil, ont tout naturellement donné naissance à un nouveau type de réseaux sans fil, communément appelés Body Area networks. A terme, ces réseaux corporels sans fil doivent permettre à un ensemble de senseurs bio-médicaux répartis sur le corps humain de communiquer, soit pour échanger des informations en vue d'un traitement en temps réel du patient, soit pour enregistrer des données physiologiques en vue d'une analyse ultérieure.<p><p>L’objectif de cette Thèse vise la réduction de la consommation énergétique au niveau des senseurs de sorte à leur garantir une autonomie de quelques mois, voire de quelques années. En réponse à cette contrainte énergétique, une association innovante de deux technologies émergentes est proposée, à savoir une combinaison des transmissions à ultra-large bande aux systèmes à multiples antennes. Une nouvelle architecture pour les réseaux corporels sans fil est donc envisagée pour laquelle les performances doivent être évaluées. Notre principale contribution à cet objectif consiste en la proposition d'une modélisation spatio-temporelle complète du canal de transmission dans le cadre de senseurs répartis autour du corps. Cette modélisation fait appel à la définition de nouveaux modèles, l'élaboration d'outils spécifiques d'extraction de paramètres et une compréhension fine des mécanismes de propagation liés à la proximité du corps humain. Ce manuscrit présente les résultats majeurs de nos recherches en cette matière.<p> / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished
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Energy-efficient transmission strategies for multiantenna systemsNguyen, K.-G. (Kien-Giang) 03 June 2019 (has links)
Abstract
The rapid evolution of wireless networks to meet the requirements of explosive data traffic demand is escalating energy consumption beyond sustainable limits. Consequently, energy efficiency (EE) has emerged as a key performance indicator for future wireless networks to address the increasing concern over greenhouse gas emissions and sustainable economic growth.
This thesis studies energy-efficient transmission strategies for multiantenna wireless systems. The aim is to develop linear beamforming techniques maximizing the bit-per-Joule EE metric, focusing on three appealing scenarios: a coordinated multicell system; a fronthaul-constrained cloud radio access network (C-RAN); and a multi-pair wireless-powered relaying system. The primary emphasis is on suboptimal but efficient optimization approaches which are attractive for practical implementation.
The problem of achieving EE fairness in a multicell multiple-input single-output downlink system is studied first. Specifically, coordinated beamforming is designed to maximize the minimum EE among all base stations. Novel efficient iterative optimization methods solving the design problem in both centralized and decentralized fashions are proposed.
In a downlink C-RAN with finite-capacity fronthaul links, the network-wide EE performance is explored via a joint design of beamforming and remote radio head-user association. A relatively realistic power consumption model including rate-dependent circuit power and nonlinear power amplifiers' (PA) efficiency is also considered. To gain an insight into the optimal performance of the design problem, an algorithm achieving globally optimal solutions is devised. Towards practical implementation, two efficient iterative suboptimal methods are proposed aiming at yielding near-optimal performance.
Finally, a multi-pair amplify-forward relaying network is considered, in which energy-constrained relays adopting time-switching protocol harvest energy from the radio frequency signals transmitted by users. To maintain EE fairness among all user pairs, joint optimization of system parameters, such as users' transmit power, relay beamforming, and energy harvesting (EH) time, is studied. Impacts of rate-dependent circuit power, nonlinear PAs' efficiency and nonlinear EH circuits on the achievable performance are also addressed. / Tiivistelmä
Langattomat verkot ovat kehittyneet nopeasti räjähdysmäisesti kasvavan dataliikenteen mahdollistamiseksi, minkä seurauksena energiankulutus on kasvanut kestävän kehityksen rajat ylittävällä tavalla. Siksi energiatehokkuudesta (EE, energy efficiency) on tullut uusien langattomien verkkojen keskeinen suunnittelukriteeri vastauksena kasvavaan huoleen kasvihuonepäästöistä ja kestävästä talouskasvusta.
Väitöskirjassa tutkitaan moniantennisten langattomien järjestelmien energiatehokkaita tiedonsiirtostrategioita. Tavoitteena on kehittää lineaarisia keilanmuodostustekniikoita, jotka maksimoivat energiatehokkuuden mitattuna bitteinä joulea kohden, keskittymällä kolmeen kiinnostavaan vaihtoehtoon, joita ovat koordinoitu monisolujärjestelmän lähetys laskevalla siirtotiellä, pilvipohjainen radioliityntäverkko (C-RAN, cloud radio access network), jossa laskentayksikön ja varsinaisen radiolähettimen välinen yhteys (fronthaul) on rahoitettu, ja usean parin relejärjestelmiin, joissa releet toimivat paristoilla. Työn pääpaino on alioptimaalisissa, mutta käytännöllisesti tehokkaissa optimointimenetelmissä. Pääpaino on alioptimaalisissa mutta tehokkaissa optimointitavoissa, jotka ovat kiinnostavia käytännön toteutuksen näkökulmasta.
Ensiksi tarkastellaan tasapuolisen energiatehokkuuden saavuttamista monisoluisessa laskevan siirtotien moni-tulo yksi-lähtö (MISO, multiple-input single-output) -järjestelmässä. Koordinoitu keilanmuodostus on suunniteltu erityisesti maksimoimaan energiatehokkuuden minimitaso kaikilla tukiasemilla. Tarkemmin sanottuna pyritään maksimoimaan huonoin energiatehokkuus solmujen välillä, kun käytetään yhteistoiminnallista keilanmuodostusta. Muodostetun ongelman ratkaisemiseksi ehdotetaan edistyksellisiä iteratiivisia menetelmiä käyttämällä sekä keskitettyjä että hajautettuja ratkaisuja.
Laskevan siirtosuunnan fronthaul-rajoitetussa C-RAN-järjestelmässä selvitetään verkonlaajuista energiatehokkuutta keilanmuodostuksen ja palvelevan tukiaseman yhteisoptimoinnilla. Tässä käytetään verrattain realistista tehonkulutusmallia, joka sisältää datanopeudesta riippuvan prosessointitehon ja epälineaarisen tehovahvistimen (PA, power amplifier) hyötysuhteen. Jotta saadaan käsitys ongelman optimaalisesta suorituskyvystä, siihen kehitetään globaalisti optimaalinen menetelmä. Lisäksi ehdotetaan kaksi käytännöllisempää iteratiivista menetelmää, jotka saavuttavat lähes optimaalisen suorituskyvyn.
Lopuksi keskitytään monen parin vahvista-ja-välitä eteenpäin (AF. amplify and forward) verkkoon, jossa aikajakokytkentää käyttävät energiarajoitetut toistimet keräävät energiaa käyttäjien lähettämistä radiosignaaleista. Jotta saavutetaan EE:n oikeudenmukaisuus kaikkien parien välillä, parametrit, kuten käyttäjien lähetysteho, toistimen keilanmuodostus, ja energiankeräysaika suunnitellaan yhdessä. Tässä tutkitaan nopeusriippuvaisen piirin tehon, epälineaarisen tehovahvistimen hyötysuhteen ja epälineaaristen energiankeräyspiirien tehon vaikutusta suorituskykyyn.
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