<p>This thesis is concerned with scheduling the use of resources, or allocating resources, so as to meet future demands for the entities produced by the resources. We consider applications in mobile communications such as scheduling users' transmissions so that the amount of transmitted information is maximized, and scenarios in the manufacturing industry where the task is to distribute work among production units so as to minimize the number of missed orders.</p><p>The allocation decisions are complicated by a lack of information concerning the future demand and possibly also about the capacities of the available resources. We therefore resort to using probability theory and the maximum entropy principle as a means for making rational decisions under uncertainty.</p><p>By using probabilities interpreted as a reasonable degree of belief, we find optimum decision rules for the manufacturing problem, bidding under uncertainty in a certain type of auctions, scheduling users in communications with uncertain channel qualities and uncertain arrival rates, quantization of channel information, partitioning bandwidth between interfering and non-interfering areas in cellular networks, hand-overs and admission control. Moreover, a new method for making optimum approximate Bayesian inference is introduced.</p><p>We further discuss reasonable optimization criteria for the mentioned applications, and provide an introduction to the topic of probability theory as an extension to two-valued logic. It is argued that this view unifies a wide range of resource-allocation problems, and we discuss various directions for further research.</p>

The low-voltage power distribution network is considered today as a serious candidate to provide residential customers with a high-speed access to communication services such as Internet. Outdoor Power-Line Communications (PLC) systems represent an alternative to the other classical 'last-mile solutions' such as ADSL, cable modems, or wireless access systems. We developed an accurate powerline channel simulation tool based on the Multiconductor Transmission Line theory. This tool is able to predict the end-to-end channel responses on the basis of the multiconductor cable structure and the network topology. Then the issue of optimal resource allocation in a multiuser environment was addressed in the light of the Multiuser Information Theory. Simultaneously active users are in competition for the limited resources that are the power (constrained by electro-magnetic compatibility restrictions) and the bandwidth (in the range of 1 to 10 MHz for outdoor PLC). The concept of multiuser balanced capacity was introduced to characterize the optimal resource allocation providing the maximum data rates with fairness constraints among the subscribers. The optimal PLC system was shown to require the shaping of the signal spectrum in the transmitters, and successive decoding in the receiver. A generic multiple access scheme based on Filter Banks (FB) was proposed, which offers the required spectral shaping with limited degrees of freedom. Classical multiple-access techniques (TDMA, CDMA, OFDMA) can be obtained by selecting the appropriate FB. The Minimum-Mean-Square-Error Decision-Feedback Joint Detector was shown to approach the performance of the optimal successive decoding receiver. Finally, the robustness of the proposed system against channel estimation and timing synchronization errors was addressed. The problem of multiuser timing synchronization was introduced, and practical multiuser timing error detectors were proposed.

This thesis is concerned with scheduling the use of resources, or allocating resources, so as to meet future demands for the entities produced by the resources. We consider applications in mobile communications such as scheduling users' transmissions so that the amount of transmitted information is maximized, and scenarios in the manufacturing industry where the task is to distribute work among production units so as to minimize the number of missed orders. The allocation decisions are complicated by a lack of information concerning the future demand and possibly also about the capacities of the available resources. We therefore resort to using probability theory and the maximum entropy principle as a means for making rational decisions under uncertainty. By using probabilities interpreted as a reasonable degree of belief, we find optimum decision rules for the manufacturing problem, bidding under uncertainty in a certain type of auctions, scheduling users in communications with uncertain channel qualities and uncertain arrival rates, quantization of channel information, partitioning bandwidth between interfering and non-interfering areas in cellular networks, hand-overs and admission control. Moreover, a new method for making optimum approximate Bayesian inference is introduced. We further discuss reasonable optimization criteria for the mentioned applications, and provide an introduction to the topic of probability theory as an extension to two-valued logic. It is argued that this view unifies a wide range of resource-allocation problems, and we discuss various directions for further research.

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.

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.

This dissertation considers several coding techniques based on Reed-Solomon (RS) and low-density parity-check (LDPC) codes. These two prominent families of error-correcting codes have attracted a great amount of interest from both theorists and practitioners and have been applied in many communication scenarios. In particular, data storage systems have greatly benefited from these codes in improving the reliability of the storage media. The first part of this dissertation presents a unified framework based on rate-distortion (RD) theory to analyze and optimize multiple decoding trials of RS codes. Finding the best set of candidate decoding patterns is shown to be equivalent to a covering problem which can be solved asymptotically by RD theory. The proposed approach helps understand the asymptotic performance-versus-complexity trade-off of these multiple-attempt decoding algorithms and can be applied to a wide range of decoders and error models. In the second part, we consider spatially-coupled (SC) codes, or terminated LDPC convolutional codes, over intersymbol-interference (ISI) channels under joint iterative decoding. We empirically observe the phenomenon of threshold saturation whereby the belief-propagation (BP) threshold of the SC ensemble is improved to the maximum a posteriori (MAP) threshold of the underlying ensemble. More specifically, we derive a generalized extrinsic information transfer (GEXIT) curve for the joint decoder that naturally obeys the area theorem and estimate the MAP and BP thresholds. We also conjecture that SC codes due to threshold saturation can universally approach the symmetric information rate of ISI channels. In the third part, a similar analysis is used to analyze the MAP thresholds of LDPC codes for several multiuser systems, namely a noisy Slepian-Wolf problem and a multiple access channel with erasures. We provide rigorous analysis and derive upper bounds on the MAP thresholds which are shown to be tight in some cases. This analysis is a first step towards proving threshold saturation for these systems which would imply SC codes with joint BP decoding can universally approach the entire capacity region of the corresponding systems.

In this thesis, the problem of multiple access interference (MAI) suppression for the multi-carrier (MC) code division multiple access (CDMA) system, based on the multi-carrier modulation with modified Gaussian wavelet, associated with the combining process is investigated for Rayleigh fading channel. The main concern of this thesis is to derive a new scheme, based on the linearly constrained constant modulus (LCCM) criterion with the robust inverse QR decomposition (IQRD) recursive least squares (RLS) algorithm to improve the performance of the wavelet-based MC-CDMA system with combining process. To verify the merits of the new algorithm, the effect due to imperfect channel parameters estimation and near-far effect are investigated. We show that the proposed robust LCCM IQRD-RLS algorithm outperforms the conventional LCCM-gradient algorithm, in terms of output SINR, for MAI suppression under channel mismatch environment. Also, the performance of the modified Gaussian wavelet-based MC-CDMA system is superior to the one with wavelet-based MC-CDMA system. It is more robust to the channel mismatch and near-far effect. Moreover, the modified Gaussian wavelet-based MC-CDMA system with robust LCCM IQRD-RLS algorithm does have better performance over other conventional approaches, such as the LCCM-gradient algorithm, maximum ratio combining (MRC), and blind adaptation algorithm, in terms of the capability of MAI suppression and bit error rate (BER).

In this thesis, multiuser receivers for code division multiple-access (CDMA) downlink are studied under frequency selective fading channel conditions. The receivers investigated in this thesis attempt to estimate desired symbol as a linear combination of chip-rate sampled received signal sequence. A common matrix-vector representation of signals, which is similar to the model given by Paulraj et. al. is constructed in order to analyze the receivers studied in this thesis. Two receivers already well known in the literature are introduced and derived by using the common signal model. One of the receivers uses traditional matched filter and the other uses symbol-level linear minimum mean square error (MMSE) estimation. The receiver that uses traditional matched filter, also known as the conventional RAKE receiver, benefits from time diversity by combining the signal energy from multiple paths. The conventional RAKE receiver is optimal when multiple-access interference (MAI) is absent. Linear MMSE based receivers are known to suppress MAI and to be more robust to noise enhancement. The optimal symbol-level linear MMSE based receiver requires inversion of large matrices whose size is determined by either number of active users or spreading factor. These two parameters can be quite large in many practical systems and hence the computational load of this receiver can be a problem. In this thesis, two alternative low-complexity receivers, which are chip-level linear MMSE equalizer proposed by Krauss et. al. and interference-suppressing RAKE receiver proposed by Paulraj et. al., are compared with the linear full-rank MMSE based receiver and with the conventional RAKE receiver in terms of bit-error-rate performance. Various simulations are performed to evaluate the performance of the receivers and the parameters affecting the receiver performance are investigated.

PN code tracking plays a very important role in CDMA communication systems. In literature, the influences of multipath fading and of multiuser interference on PN code tracking are studied separately. The multipath fading influence is mitigated by combining a rake receiver and a channel estimator in the Delay-Locked Loop (DLL). The multiuser interference is overcome by incorporating a data estimator into the DLL. In the downlink, PN code tracking may suffer from the multipath fading influence. However, the multipath fading and the multiuser interference influences exist in the uplink. Unfortunately, sole use of the aforementioned methods cannot solve out both influences simultaneously. In this thesis, two new Coherent Decision-Directed Delay-Locked Loop (CDD-DLL) PN-Code tracking schemes are developed and either can overcome both influences. First, a channel and a data estimators are incorporated into the DLL inherent with a rake receiver. This new scheme works properly in an environment with multipath fading and multiuser interference. Second, the original CDD-DLL is combined with a multipath interference canceller (MPI) to reduce both influences. Analytical results are derived for the two schemes proposed and are validated with numerical simulations. Simulation results show that the conventional DLLs working in a multipath fading and multiuser interference environment can be significantly improved using the new schemes. Moreover, the latter outperforms the former because the multipath interference is cancelled completely.

Made available in DSpace on 2014-12-17T15:47:52Z (GMT). No. of bitstreams: 1 KaioAAD_DISSERT.pdf: 2396419 bytes, checksum: 9761258d74c5a831492561ccf81ab7b3 (MD5) Previous issue date: 2010-05-10 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / Education is one of the oldest activities practiced by man, but today it is still performed often without creating dialogues and discussions among all those involved, and students are passives agents without interactivity with teachers and the content approached. This work presents a tool used for providing interactivity in educational environments using cell phones, in this way, teachers can use technology to assist in process of education and have a better evaluation of students. The tool developed architecture is shown, exposing features of wireless communication technologies used and how is the connection management using Bluetooth technology, which has a limited number of simultaneous connections. The details of multiple Bluetooth connections and how the system should behave by numerous users are displayed, showing a comparison between different methods of managing connections. Finally, the results obtained with the use of the tool are presented, followed by the analysis of them and a conclusion on the work / O ensino ? uma das atividades mais antigas exercidas pelo homem, por?m hoje ela ainda ? realizada muitas vezes sem a cria??o de di?logos e debates entre todos os envolvidos, sendo os alunos muitas vezes agentes passivos, n?o havendo interatividade com os professores e o conte?do abordado. Este trabalho apresenta uma ferramenta utilizada para prover interatividade em ambientes educacionais por meio de celulares, desta forma professores podem fazer uso da tecnologia para auxiliar no ensino e ter uma melhor avalia??o dos alunos. A arquitetura da ferramenta desenvolvida ? mostrada, trazendo caracter?sticas de tecnologias de comunica??o sem fio utilizadas e como ? feito o gerenciamento de conex?es atrav?s de Bluetooth, que possui um n?mero limitado de conex?es simult?neas. Os detalhes das m?ltiplas conex?es Bluetooth e como o sistema deve se comportar mediante in?meros usu?rios s?o exibidos, mostrando um comparativo entre diferentes m?todos de gerenciamento das conex?es. Por ?ltimo, s?o mostrados os resultados obtidos com o uso da ferramenta, seguido pela an?lise dos mesmos e uma conclus?o sobre o trabalho desenvolvido