992 resultados para MIMO communication


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In this paper, the gamma-gamma probability distribution is used to model turbulent channels. The bit error rate (BER) performance of free space optical (FSO) communication systems employing on-off keying (OOK) or subcarrier binary phase-shift keying (BPSK) modulation format is derived. A tip-tilt adaptive optics system is also incorporated with a FSO system using the above modulation formats. The tip-tilt compensation can alleviate effects of atmospheric turbulence and thereby improve the BER performance. The improvement is different for different turbulence strengths and modulation formats. In addition, the BER performance of communication systems employing subcarrier BPSK modulation is much better than that of compatible systems employing OOK modulation with or without tip-tilt compensation.

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The findings are presented of a study conducted in the framework of the Nigerian-German Kainji Lake Fisheries Promotion Project to examine the role and structure of communication in fishing villages around Kainji Lake in Nigeria. The major aim was to be able to utilize the knowledge at a later stage in the project cycle to pass on fisheries extension messages to fishing communities. The study had the following terms of reference: 1) describe the structure and processes of communication of fishermen around Kainji Lake; 2) identify the formal and informal media of communication used by the fishermen to communicate information concerning their job; 3) describe the problems inhibiting usage of the different media identified; 4) ascertain the extent of use of mass media by fishermen around the lake; and, 5) identify acceptable ways by which fisheries information can be repackaged for the use of extension workers. (PDF contains 58 pages)

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The scalability of CMOS technology has driven computation into a diverse range of applications across the power consumption, performance and size spectra. Communication is a necessary adjunct to computation, and whether this is to push data from node-to-node in a high-performance computing cluster or from the receiver of wireless link to a neural stimulator in a biomedical implant, interconnect can take up a significant portion of the overall system power budget. Although a single interconnect methodology cannot address such a broad range of systems efficiently, there are a number of key design concepts that enable good interconnect design in the age of highly-scaled CMOS: an emphasis on highly-digital approaches to solving ‘analog’ problems, hardware sharing between links as well as between different functions (such as equalization and synchronization) in the same link, and adaptive hardware that changes its operating parameters to mitigate not only variation in the fabrication of the link, but also link conditions that change over time. These concepts are demonstrated through the use of two design examples, at the extremes of the power and performance spectra.

A novel all-digital clock and data recovery technique for high-performance, high density interconnect has been developed. Two independently adjustable clock phases are generated from a delay line calibrated to 2 UI. One clock phase is placed in the middle of the eye to recover the data, while the other is swept across the delay line. The samples produced by the two clocks are compared to generate eye information, which is used to determine the best phase for data recovery. The functions of the two clocks are swapped after the data phase is updated; this ping-pong action allows an infinite delay range without the use of a PLL or DLL. The scheme's generalized sampling and retiming architecture is used in a sharing technique that saves power and area in high-density interconnect. The eye information generated is also useful for tuning an adaptive equalizer, circumventing the need for dedicated adaptation hardware.

On the other side of the performance/power spectra, a capacitive proximity interconnect has been developed to support 3D integration of biomedical implants. In order to integrate more functionality while staying within size limits, implant electronics can be embedded onto a foldable parylene (‘origami’) substrate. Many of the ICs in an origami implant will be placed face-to-face with each other, so wireless proximity interconnect can be used to increase communication density while decreasing implant size, as well as facilitate a modular approach to implant design, where pre-fabricated parylene-and-IC modules are assembled together on-demand to make custom implants. Such an interconnect needs to be able to sense and adapt to changes in alignment. The proposed array uses a TDC-like structure to realize both communication and alignment sensing within the same set of plates, increasing communication density and eliminating the need to infer link quality from a separate alignment block. In order to distinguish the communication plates from the nearby ground plane, a stimulus is applied to the transmitter plate, which is rectified at the receiver to bias a delay generation block. This delay is in turn converted into a digital word using a TDC, providing alignment information.

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Signal processing techniques play important roles in the design of digital communication systems. These include information manipulation, transmitter signal processing, channel estimation, channel equalization and receiver signal processing. By interacting with communication theory and system implementing technologies, signal processing specialists develop efficient schemes for various communication problems by wisely exploiting various mathematical tools such as analysis, probability theory, matrix theory, optimization theory, and many others. In recent years, researchers realized that multiple-input multiple-output (MIMO) channel models are applicable to a wide range of different physical communications channels. Using the elegant matrix-vector notations, many MIMO transceiver (including the precoder and equalizer) design problems can be solved by matrix and optimization theory. Furthermore, the researchers showed that the majorization theory and matrix decompositions, such as singular value decomposition (SVD), geometric mean decomposition (GMD) and generalized triangular decomposition (GTD), provide unified frameworks for solving many of the point-to-point MIMO transceiver design problems.

In this thesis, we consider the transceiver design problems for linear time invariant (LTI) flat MIMO channels, linear time-varying narrowband MIMO channels, flat MIMO broadcast channels, and doubly selective scalar channels. Additionally, the channel estimation problem is also considered. The main contributions of this dissertation are the development of new matrix decompositions, and the uses of the matrix decompositions and majorization theory toward the practical transmit-receive scheme designs for transceiver optimization problems. Elegant solutions are obtained, novel transceiver structures are developed, ingenious algorithms are proposed, and performance analyses are derived.

The first part of the thesis focuses on transceiver design with LTI flat MIMO channels. We propose a novel matrix decomposition which decomposes a complex matrix as a product of several sets of semi-unitary matrices and upper triangular matrices in an iterative manner. The complexity of the new decomposition, generalized geometric mean decomposition (GGMD), is always less than or equal to that of geometric mean decomposition (GMD). The optimal GGMD parameters which yield the minimal complexity are derived. Based on the channel state information (CSI) at both the transmitter (CSIT) and receiver (CSIR), GGMD is used to design a butterfly structured decision feedback equalizer (DFE) MIMO transceiver which achieves the minimum average mean square error (MSE) under the total transmit power constraint. A novel iterative receiving detection algorithm for the specific receiver is also proposed. For the application to cyclic prefix (CP) systems in which the SVD of the equivalent channel matrix can be easily computed, the proposed GGMD transceiver has K/log_2(K) times complexity advantage over the GMD transceiver, where K is the number of data symbols per data block and is a power of 2. The performance analysis shows that the GGMD DFE transceiver can convert a MIMO channel into a set of parallel subchannels with the same bias and signal to interference plus noise ratios (SINRs). Hence, the average bit rate error (BER) is automatically minimized without the need for bit allocation. Moreover, the proposed transceiver can achieve the channel capacity simply by applying independent scalar Gaussian codes of the same rate at subchannels.

In the second part of the thesis, we focus on MIMO transceiver design for slowly time-varying MIMO channels with zero-forcing or MMSE criterion. Even though the GGMD/GMD DFE transceivers work for slowly time-varying MIMO channels by exploiting the instantaneous CSI at both ends, their performance is by no means optimal since the temporal diversity of the time-varying channels is not exploited. Based on the GTD, we develop space-time GTD (ST-GTD) for the decomposition of linear time-varying flat MIMO channels. Under the assumption that CSIT, CSIR and channel prediction are available, by using the proposed ST-GTD, we develop space-time geometric mean decomposition (ST-GMD) DFE transceivers under the zero-forcing or MMSE criterion. Under perfect channel prediction, the new system minimizes both the average MSE at the detector in each space-time (ST) block (which consists of several coherence blocks), and the average per ST-block BER in the moderate high SNR region. Moreover, the ST-GMD DFE transceiver designed under an MMSE criterion maximizes Gaussian mutual information over the equivalent channel seen by each ST-block. In general, the newly proposed transceivers perform better than the GGMD-based systems since the super-imposed temporal precoder is able to exploit the temporal diversity of time-varying channels. For practical applications, a novel ST-GTD based system which does not require channel prediction but shares the same asymptotic BER performance with the ST-GMD DFE transceiver is also proposed.

The third part of the thesis considers two quality of service (QoS) transceiver design problems for flat MIMO broadcast channels. The first one is the power minimization problem (min-power) with a total bitrate constraint and per-stream BER constraints. The second problem is the rate maximization problem (max-rate) with a total transmit power constraint and per-stream BER constraints. Exploiting a particular class of joint triangularization (JT), we are able to jointly optimize the bit allocation and the broadcast DFE transceiver for the min-power and max-rate problems. The resulting optimal designs are called the minimum power JT broadcast DFE transceiver (MPJT) and maximum rate JT broadcast DFE transceiver (MRJT), respectively. In addition to the optimal designs, two suboptimal designs based on QR decomposition are proposed. They are realizable for arbitrary number of users.

Finally, we investigate the design of a discrete Fourier transform (DFT) modulated filterbank transceiver (DFT-FBT) with LTV scalar channels. For both cases with known LTV channels and unknown wide sense stationary uncorrelated scattering (WSSUS) statistical channels, we show how to optimize the transmitting and receiving prototypes of a DFT-FBT such that the SINR at the receiver is maximized. Also, a novel pilot-aided subspace channel estimation algorithm is proposed for the orthogonal frequency division multiplexing (OFDM) systems with quasi-stationary multi-path Rayleigh fading channels. Using the concept of a difference co-array, the new technique can construct M^2 co-pilots from M physical pilot tones with alternating pilot placement. Subspace methods, such as MUSIC and ESPRIT, can be used to estimate the multipath delays and the number of identifiable paths is up to O(M^2), theoretically. With the delay information, a MMSE estimator for frequency response is derived. It is shown through simulations that the proposed method outperforms the conventional subspace channel estimator when the number of multipaths is greater than or equal to the number of physical pilots minus one.

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[ES]Hoy en día, los sistemas de comunicación inalámbricos soportan un amplio número de servicios como la voz, datos y vídeos que requieren unas grandes tasas de transmisión. Por ello la mejora de la calidad del enlace que ofrecen los sistemas MIMO es clave. El problema surge al colocar varias antenas en un terminal móvil sin que aparezca un acoplamiento entre las distintas antenas que evite el correcto funcionamiento de estas. En este documento se realizará un estudio de los diferentes métodos de desacoplo entre antenas PIFA (Planar Inverted-F antenna) en un terminal móvil.

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Network information theory and channels with memory are two important but difficult frontiers of information theory. In this two-parted dissertation, we study these two areas, each comprising one part. For the first area we study the so-called entropy vectors via finite group theory, and the network codes constructed from finite groups. In particular, we identify the smallest finite group that violates the Ingleton inequality, an inequality respected by all linear network codes, but not satisfied by all entropy vectors. Based on the analysis of this group we generalize it to several families of Ingleton-violating groups, which may be used to design good network codes. Regarding that aspect, we study the network codes constructed with finite groups, and especially show that linear network codes are embedded in the group network codes constructed with these Ingleton-violating families. Furthermore, such codes are strictly more powerful than linear network codes, as they are able to violate the Ingleton inequality while linear network codes cannot. For the second area, we study the impact of memory to the channel capacity through a novel communication system: the energy harvesting channel. Different from traditional communication systems, the transmitter of an energy harvesting channel is powered by an exogenous energy harvesting device and a finite-sized battery. As a consequence, each time the system can only transmit a symbol whose energy consumption is no more than the energy currently available. This new type of power supply introduces an unprecedented input constraint for the channel, which is random, instantaneous, and has memory. Furthermore, naturally, the energy harvesting process is observed causally at the transmitter, but no such information is provided to the receiver. Both of these features pose great challenges for the analysis of the channel capacity. In this work we use techniques from channels with side information, and finite state channels, to obtain lower and upper bounds of the energy harvesting channel. In particular, we study the stationarity and ergodicity conditions of a surrogate channel to compute and optimize the achievable rates for the original channel. In addition, for practical code design of the system we study the pairwise error probabilities of the input sequences.

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International communication strategy followed by Ikea analysis of campaigns in different countries, features and possible justifications of the differerences.

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The frame of a laser diode transmitter for intersatellite communication is concisely introduced. A simple, novel and visual method for measuring the diffraction-limited wavefront of the transmitter by a Jamin double-shearing interferometer is proposed. To verify the validity of the measurement, the far-field divergence of beam is additionally rigorously analysed in terms of the Fraunhofer diffraction. The measurement, the necessary analyses and discussion are given in detail. By directly measuring the fringe widths and quantitatively interpreting the interference fringes, the minimum detectable wavefront height (DWH) of the wavefront is only 0.2 gimel (the distance between the perfect plane wavefront and the actual wavefront at the transmitting aperture) and the corresponding divergence is only 65.84 mu rad. This indicates that the wavefront approaches the diffraction-limited condition. The results show that this interferometer is a powerful tool for testing the semiconductor laser beam's wavefront, especially the diffraction-limited wavefront.

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This research is concerned with block coding for a feedback communication system in which the forward and feedback channels are independently disturbed by additive white Gaussian noise and average power constrained. Two coding schemes are proposed in which the messages to be coded for transmission over the forward channel are realized as a set of orthogonal waveforms. A finite number of forward and feedback transmissions (iterations) per message is made. Information received over the feedback channel is used to modify the waveform transmitted on successive forward iterations in such a way that the expected value of forward signal energy is zero on all iterations after the first. Similarly, information is sent over the feedback channel in such a way that the expected value of feedback signal energy is also zero on all iterations after the first. These schemes are shown to achieve a lower probability of error than the best one-way coding scheme at all rates up to the forward channel capacity, provided only that the feedback channel capacity be greater than the forward channel capacity. These schemes make more efficient use of the available feedback power than existing feedback coding schemes, and therefore require less feedback power to achieve a given error performance.

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We propose a novel communication technique which utilizes a set of mutually distinguishable optical patterns instead of convergent facula to transmit information. The communication capacity is increased by exploiting the optical spatial bandwidth resources. An optimum detector for this communication is proposed based on maximum-likelihood decision. The fundamental rule of designing signal spatial pattern is formulated from analysis of the probability of error decision. Finally, we present a typical electro-optical system scheme of the proposed communication. (c) 2006 Elsevier GmbH. All rights reserved.