948 resultados para Multi-user MIMO
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This dissertation discussed resource allocation mechanisms in several network topologies including infrastructure wireless network, non-infrastructure wireless network and wire-cum-wireless network. Different networks may have different resource constrains. Based on actual technologies and implementation models, utility function, game theory and a modern control algorithm have been introduced to balance power, bandwidth and customers' satisfaction in the system. ^ In infrastructure wireless networks, utility function was used in the Third Generation (3G) cellular network and the network was trying to maximize the total utility. In this dissertation, revenue maximization was set as an objective. Compared with the previous work on utility maximization, it is more practical to implement revenue maximization by the cellular network operators. The pricing strategies were studied and the algorithms were given to find the optimal price combination of power and rate to maximize the profit without degrading the Quality of Service (QoS) performance. ^ In non-infrastructure wireless networks, power capacity is limited by the small size of the nodes. In such a network, nodes need to transmit traffic not only for themselves but also for their neighbors, so power management become the most important issue for the network overall performance. Our innovative routing algorithm based on utility function, sets up a flexible framework for different users with different concerns in the same network. This algorithm allows users to make trade offs between multiple resource parameters. Its flexibility makes it a suitable solution for the large scale non-infrastructure network. This dissertation also covers non-cooperation problems. Through combining game theory and utility function, equilibrium points could be found among rational users which can enhance the cooperation in the network. ^ Finally, a wire-cum-wireless network architecture was introduced. This network architecture can support multiple services over multiple networks with smart resource allocation methods. Although a SONET-to-WiMAX case was used for the analysis, the mathematic procedure and resource allocation scheme could be universal solutions for all infrastructure, non-infrastructure and combined networks. ^
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The population of English Language Learners (ELLs) globally has been increasing substantially every year. In the United States alone, adult ELLs are the fastest growing portion of learners in adult education programs (Yang, 2005). There is a significant need to improve the teaching of English to ELLs in the United States and other English-speaking dominant countries. However, for many ELLs, speaking, especially to Native English Speakers (NESs), causes considerable language anxiety, which in turn plays a vital role in hindering their language development and academic progress (Pichette, 2009; Woodrow, 2006). ^ Task-based Language Teaching (TBLT), such as simulation activities, has long been viewed as an effective approach for second-language development. The current advances in technology and rapid emergence of Multi-User Virtual Environments (MUVEs) have provided an opportunity for educators to consider conducting simulations online for ELLs to practice speaking English to NESs. Yet to date, empirical research on the effects of MUVEs on ELLs' language development and speaking is limited (Garcia-Ruiz, Edwards, & Aquino-Santos, 2007). ^ This study used a true experimental treatment control group repeated measures design to compare the perceived speaking anxiety levels (as measured by an anxiety scale administered per simulation activity) of 11 ELLs (5 in the control group, 6 in the experimental group) when speaking to Native English Speakers (NESs) during 10 simulation activities. Simulations in the control group were done face-to-face, while those in the experimental group were done in the MUVE of Second Life. ^ The results of the repeated measures ANOVA revealed after the Huynh-Feldt epsilon correction, demonstrated for both groups a significant decrease in anxiety levels over time from the first simulation to the tenth and final simulation. When comparing the two groups, the results revealed a statistically significant difference, with the experimental group demonstrating a greater anxiety reduction. These results suggests that language instructors should consider including face-to-face and MUVE simulations with ELLs paired with NESs as part of their language instruction. Future investigations should investigate the use of other multi-user virtual environments and/or measure other dimensions of the ELL/NES interactions.^
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The population of English Language Learners (ELLs) globally has been increasing substantially every year. In the United States alone, adult ELLs are the fastest growing portion of learners in adult education programs (Yang, 2005). There is a significant need to improve the teaching of English to ELLs in the United States and other English-speaking dominant countries. However, for many ELLs, speaking, especially to Native English Speakers (NESs), causes considerable language anxiety, which in turn plays a vital role in hindering their language development and academic progress (Pichette, 2009; Woodrow, 2006). Task-based Language Teaching (TBLT), such as simulation activities, has long been viewed as an effective approach for second-language development. The current advances in technology and rapid emergence of Multi-User Virtual Environments (MUVEs) have provided an opportunity for educators to consider conducting simulations online for ELLs to practice speaking English to NESs. Yet to date, empirical research on the effects of MUVEs on ELLs’ language development and speaking is limited (Garcia-Ruiz, Edwards, & Aquino-Santos, 2007). This study used a true experimental treatment control group repeated measures design to compare the perceived speaking anxiety levels (as measured by an anxiety scale administered per simulation activity) of 11 ELLs (5 in the control group, 6 in the experimental group) when speaking to Native English Speakers (NESs) during 10 simulation activities. Simulations in the control group were done face-to-face, while those in the experimental group were done in the MUVE of Second Life. The results of the repeated measures ANOVA revealed after the Huynh-Feldt epsilon correction, demonstrated for both groups a significant decrease in anxiety levels over time from the first simulation to the tenth and final simulation. When comparing the two groups, the results revealed a statistically significant difference, with the experimental group demonstrating a greater anxiety reduction. These results suggests that language instructors should consider including face-to-face and MUVE simulations with ELLs paired with NESs as part of their language instruction. Future investigations should investigate the use of other multi-user virtual environments and/or measure other dimensions of the ELL/NES interactions.
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This work has been realized by the author in his PhD course in Electronics, Computer Science and Telecommunication at the University of Bologna, Faculty of Engineering, Italy. The subject of this thesis regards important channel estimation aspects in wideband wireless communication systems, such as echo cancellation in digital video broadcasting systems and pilot aided channel estimation through an innovative pilot design in Multi-Cell Multi-User MIMO-OFDM network. All the documentation here reported is a summary of years of work, under the supervision of Prof. Oreste Andrisano, coordinator of Wireless Communication Laboratory - WiLab, in Bologna. All the instrumentation that has been used for the characterization of the telecommunication systems belongs to CNR (National Research Council), CNIT (Italian Inter-University Center), and DEIS (Dept. of Electronics, Computer Science, and Systems). From November 2009 to May 2010, the author spent his time abroad, working in collaboration with DOCOMO - Communications Laboratories Europe GmbH (DOCOMO Euro-Labs) in Munich, Germany, in the Wireless Technologies Research Group. Some important scientific papers, submitted and/or published on IEEE journals and conferences have been produced by the author.
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For single-user MIMO communication with uncoded and coded QAM signals, we propose bit and power loading schemes that rely only on channel distribution information at the transmitter. To that end, we develop the relationship between the average bit error probability at the output of a ZF linear receiver and the bit rates and powers allocated at the transmitter. This relationship, and the fact that a ZF receiver decouples the MIMO parallel channels, allow leveraging bit loading algorithms already existing in the literature. We solve dual bit rate maximization and power minimization problems and present performance resultsthat illustrate the gains of the proposed scheme with respect toa non-optimized transmission.
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Traditional machinery for manufacturing processes are characterised by actuators powered and co-ordinated by mechanical linkages driven from a central drive. Increasingly, these linkages are replaced by independent electrical drives, each performs a different task and follows a different motion profile, co-ordinated by computers. A design methodology for the servo control of high speed multi-axis machinery is proposed, based on the concept of a highly adaptable generic machine model. In addition to the dynamics of the drives and the loads, the model includes the inherent interactions between the motion axes and thus provides a Multi-Input Multi-Output (MIMO) description. In general, inherent interactions such as structural couplings between groups of motion axes are undesirable and needed to be compensated. On the other hand, imposed interactions such as the synchronisation of different groups of axes are often required. It is recognised that a suitable MIMO controller can simultaneously achieve these objectives and reconciles their potential conflicts. Both analytical and numerical methods for the design of MIMO controllers are investigated. At present, it is not possible to implement high order MIMO controllers for practical reasons. Based on simulations of the generic machine model under full MIMO control, however, it is possible to determine a suitable topology for a blockwise decentralised control scheme. The Block Relative Gain array (BRG) is used to compare the relative strength of closed loop interactions between sub-systems. A number of approaches to the design of the smaller decentralised MIMO controllers for these sub-systems has been investigated. For the purpose of illustration, a benchmark problem based on a 3 axes test rig has been carried through the design cycle to demonstrate the working of the design methodology.
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It is desirable that energy performance improvement is not realized at the expense of other network performance parameters. This paper investigates the trade off between energy efficiency, spectral efficiency and user QoS performance for a multi-cell multi-user radio access network. Specifically, the energy consumption ratio (ECR) and the spectral efficiency of several common frequency domain packet schedulers in a cellular E-UTRAN downlink are compared for both the SISO transmission mode and the 2x2 Alamouti Space Frequency Block Code (SFBC) MIMO transmission mode. It is well known that the 2x2 SFBC MIMO transmission mode is more spectrally efficient compared to the SISO transmission mode, however, the relationship between energy efficiency and spectral efficiency is undecided. It is shown that, for the E-UTRAN downlink with fixed transmission power, spectral efficiency improvement results into energy efficiency improvement. The effect of SFBC MIMO versus SISO on the user QoS performance is also studied. © 2011 IEEE.
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We investigate the achievable ergodic sum-rate of multi-user multiple-input multiple-output systems in Ricean fading channels. We first derive a lower bound on the average signal-to-leakage-and-noise ratio by utilizing the Mullen's inequality, which is then used to analyze the effect of channel mean information on the achievable sum-rate. With these results, a novel statistical-eigenmode space-division multipleaccess downlink transmission scheme is proposed. For this scheme, we derive an exact closed-form expression for the achievable ergodic sum-rate. Our results show that the achievable ergodic sum-rate converges to a saturation value in the high signal-to-noise ratio (SNR) region and reaches to a lower limit value in the lower Ricean K-factor range. In addition, we present tractable upper and lower bounds, which are shown to be tight for any SNR and Ricean K-factor value. Finally, the theoretical analysis is validated via numerical simulations.
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Massive multi-user multiple-input multiple-output (MU-MIMO) systems are cellular networks where the base stations (BSs) are equipped with hundreds of antennas, N, and communicate with tens of mobile stations (MSs), K, such that, N ≫ K ≫ 1. Contrary to most prior works, in this paper, we consider the uplink of a single-cell massive MIMO system operating in sparse channels with limited scattering. This case is of particular importance in most propagation scenarios, where the prevalent Rayleigh fading assumption becomes idealistic. We derive analytical approximations for the achievable rates of maximum-ratio combining (MRC) and zero-forcing (ZF) receivers. Furthermore, we study the asymptotic behavior of the achievable rates for both MRC and ZF receivers, when N and K go to infinity under the condition that N/K → c ≥ 1. Our results indicate that the achievable rate of MRC receivers reaches an asymptotic saturation limit, whereas the achievable rate of ZF receivers grows logarithmically with the number of MSs.
Energy-efficient diversity combining for different access schemes in a multi-path dispersive channel
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Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e Computadores
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Com o crescente progresso tecnológico, surgem sistemas mais eficientes, mas também mais complexos e não-lineares. Isto torna-se mais evidente em sistemas Multi-Input Multi-Output (MIMO), devido a diferentes efeitos que uma entrada possa ter sobre diversas saídas. Para estes sistemas, a obtenção de modelos matemáticos que capturem, com precisão aceitável, a dinâmica do sistema, torna-se cada vez mais complexa e custosa. Sendo que muitos dos sistemas utilizados hoje em dia são MIMO, a diminuição na precisão dos modelos matemáticos é uma adversidade à eficiência dos sistemas de controlo. Isto deve-se a grande parte dos métodos de projeto de controladores terem como base o modelo do sistema. O trabalho realizado nesta dissertação pretende desenvolver uma estrutura de supervisão para sistemas MIMO, com base em controlo Unfalsified, ou Unfalsified Control (UC). Este consiste numa abordagem de controlo adaptativo, cujo processo de adaptação se traduz na seleção de um controlador, de entre um conjunto pré-determinado. Em cada momento é selecionado o controlador que mais se adequa ao objetivo de controlo pretendido. A utilização de UC representa uma possível solução para o problema apresentado, pois utiliza apenas dados experimentais recolhidos do funcionamento do processo. Assim, contorna a necessidade da existência de modelos do processo. Existem, no entanto, dificuldades associadas à comutação de controladores, pelo que este trabalho pretende também desenvolver uma estrutura de Bumpless Transfer (BT), de forma a reduzir estes efeitos. Finalmente, a utilização de dados experimentais implica que a aplicação de UC a um processo está apenas limitada ao ajuste dos parâmetros do sistema de supervisão, e à existência de um conjunto de controladores adequados.
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As Terabyte datasets become the norm, the focus has shifted away from our ability to produce and store ever larger amounts of data, onto its utilization. It is becoming increasingly difficult to gain meaningful insights into the data produced. Also many forms of the data we are currently producing cannot easily fit into traditional visualization methods. This paper presents a new and novel visualization technique based on the concept of a Data Forest. Our Data Forest has been designed to be used with vir tual reality (VR) as its presentation method. VR is a natural medium for investigating large datasets. Our approach can easily be adapted to be used in a variety of different ways, from a stand alone single user environment to large multi-user collaborative environments. A test application is presented using multi-dimensional data to demonstrate the concepts involved.
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An input variable selection procedure is introduced for the identification and construction of multi-input multi-output (MIMO) neurofuzzy operating point dependent models. The algorithm is an extension of a forward modified Gram-Schmidt orthogonal least squares procedure for a linear model structure which is modified to accommodate nonlinear system modeling by incorporating piecewise locally linear model fitting. The proposed input nodes selection procedure effectively tackles the problem of the curse of dimensionality associated with lattice-based modeling algorithms such as radial basis function neurofuzzy networks, enabling the resulting neurofuzzy operating point dependent model to be widely applied in control and estimation. Some numerical examples are given to demonstrate the effectiveness of the proposed construction algorithm.
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Target localization has a wide range of military and civilian applications in wireless mobile networks. Examples include battle-field surveillance, emergency 911 (E911), traffc alert, habitat monitoring, resource allocation, routing, and disaster mitigation. Basic localization techniques include time-of-arrival (TOA), direction-of-arrival (DOA) and received-signal strength (RSS) estimation. Techniques that are proposed based on TOA and DOA are very sensitive to the availability of Line-of-sight (LOS) which is the direct path between the transmitter and the receiver. If LOS is not available, TOA and DOA estimation errors create a large localization error. In order to reduce NLOS localization error, NLOS identifcation, mitigation, and localization techniques have been proposed. This research investigates NLOS identifcation for multiple antennas radio systems. The techniques proposed in the literature mainly use one antenna element to enable NLOS identifcation. When a single antenna is utilized, limited features of the wireless channel can be exploited to identify NLOS situations. However, in DOA-based wireless localization systems, multiple antenna elements are available. In addition, multiple antenna technology has been adopted in many widely used wireless systems such as wireless LAN 802.11n and WiMAX 802.16e which are good candidates for localization based services. In this work, the potential of spatial channel information for high performance NLOS identifcation is investigated. Considering narrowband multiple antenna wireless systems, two xvNLOS identifcation techniques are proposed. Here, the implementation of spatial correlation of channel coeffcients across antenna elements as a metric for NLOS identifcation is proposed. In order to obtain the spatial correlation, a new multi-input multi-output (MIMO) channel model based on rough surface theory is proposed. This model can be used to compute the spatial correlation between the antenna pair separated by any distance. In addition, a new NLOS identifcation technique that exploits the statistics of phase difference across two antenna elements is proposed. This technique assumes the phases received across two antenna elements are uncorrelated. This assumption is validated based on the well-known circular and elliptic scattering models. Next, it is proved that the channel Rician K-factor is a function of the phase difference variance. Exploiting Rician K-factor, techniques to identify NLOS scenarios are proposed. Considering wideband multiple antenna wireless systems which use MIMO-orthogonal frequency division multiplexing (OFDM) signaling, space-time-frequency channel correlation is exploited to attain NLOS identifcation in time-varying, frequency-selective and spaceselective radio channels. Novel NLOS identi?cation measures based on space, time and frequency channel correlation are proposed and their performances are evaluated. These measures represent a better NLOS identifcation performance compared to those that only use space, time or frequency.
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Multi-input multi-output (MIMO) technology is an emerging solution for high data rate wireless communications. We develop soft-decision based equalization techniques for frequency selective MIMO channels in the quest for low-complexity equalizers with BER performance competitive to that of ML sequence detection. We first propose soft decision equalization (SDE), and demonstrate that decision feedback equalization (DFE) based on soft-decisions, expressed via the posterior probabilities associated with feedback symbols, is able to outperform hard-decision DFE, with a low computational cost that is polynomial in the number of symbols to be recovered, and linear in the signal constellation size. Building upon the probabilistic data association (PDA) multiuser detector, we present two new MIMO equalization solutions to handle the distinctive channel memory. With their low complexity, simple implementations, and impressive near-optimum performance offered by iterative soft-decision processing, the proposed SDE methods are attractive candidates to deliver efficient reception solutions to practical high-capacity MIMO systems. Motivated by the need for low-complexity receiver processing, we further present an alternative low-complexity soft-decision equalization approach for frequency selective MIMO communication systems. With the help of iterative processing, two detection and estimation schemes based on second-order statistics are harmoniously put together to yield a two-part receiver structure: local multiuser detection (MUD) using soft-decision Probabilistic Data Association (PDA) detection, and dynamic noise-interference tracking using Kalman filtering. The proposed Kalman-PDA detector performs local MUD within a sub-block of the received data instead of over the entire data set, to reduce the computational load. At the same time, all the inter-ference affecting the local sub-block, including both multiple access and inter-symbol interference, is properly modeled as the state vector of a linear system, and dynamically tracked by Kalman filtering. Two types of Kalman filters are designed, both of which are able to track an finite impulse response (FIR) MIMO channel of any memory length. The overall algorithms enjoy low complexity that is only polynomial in the number of information-bearing bits to be detected, regardless of the data block size. Furthermore, we introduce two optional performance-enhancing techniques: cross- layer automatic repeat request (ARQ) for uncoded systems and code-aided method for coded systems. We take Kalman-PDA as an example, and show via simulations that both techniques can render error performance that is better than Kalman-PDA alone and competitive to sphere decoding. At last, we consider the case that channel state information (CSI) is not perfectly known to the receiver, and present an iterative channel estimation algorithm. Simulations show that the performance of SDE with channel estimation approaches that of SDE with perfect CSI.