48 research outputs found

    Joint DOA and Array Manifold Estimation for a MIMO Array Using Two Calibrated Antennas

    Get PDF
    A simple scheme for joint direction of arrival (DOA) and array manifold estimation for a MIMO array system is proposed, where only two transmit antennas are calibrated initially. It first obtains a set of initial DOA results by employing a rotational invariance property between two sets of received data, and then more accurate DOA and array manifold estimation is obtained through a local searching algorithm with several iterations. No strict half wavelength spacing is required for the uncalibrated antennas to avoid the spatial aliasing problem

    Spatiotemporal-MIMO channel estimator and beamformer for 5G

    Get PDF
    With requirements of spiraling data rates and limited spectrum availability, there is an increased interest in mm-wave beamformer-based communications for 5G. For upcoming cellular networks, the critical point is to exploit the increased number of employable antennas at both Tx and Rx to: 1) combat increased path loss; 2) tackle higher interference due to higher user density; and 3) handle multipath effects in frequency selective channels. Toward this, a multi-beam spatiotemporal superresolution beamforming framework is proposed in this paper as a promising candidate to design beampatterns that mitigate/suppress co-channel interference and deliver massive gain in the desired directions. Initially, channel and signal models suitable for the mm-wave MIMO system are presented using the manifold vectors of both Tx and Rx antenna arrays. Based on these models, a novel subspace-based channel estimator is employed, which estimates delays, directions, velocities, and fading coefficients of the desired signal paths. This information is then exploited by the proposed spatiotemporal beamformer to provide a massive array gain that combats path loss without increasing the number of antenna array elements and to be tolerant to the near-far problem in a high interference environment. The performance of the proposed channel estimator and beamformer is examined using computer simulation studies

    Target Parameter Estimation for MIMO Radars

    Get PDF

    Transmit-Receive Beamforming for 60 GHz Indoor Wireless Communications

    Get PDF
    The vast unlicensed bandwidth available in the 60 GHz band is an attractive solution to provide multi-gigabit bit-rates over short distances in indoor environments. One of the crucial problems of the 60 GHz band is the limited link budget. In order to improve the link budget, antenna beam-forming techniques are employed at least at one end of the transceiver system. This thesis studies the topic of transmit-receive (Tx-Rx) beam-forming, investigating the impact of the array size and the nature of the channel (LOS/NLOS) on the system performance. The scope of the investigation is limited to uniform rectangular arrays (URA) and to analog beam-forming with one scalar weight per antenna. In order to evaluate the Tx-Rx system, a multiple-input multiple-output (MIMO) Semi-Deterministic Channel Model (SDCM) is introduced, based on a combination of ray-tracing and the well-known Saleh-Valenzuela statistical model. The MIMO channel is then applied to a beam-forming system based on beam-switching. With this technique, the Tx-Rx beam-vector pair that maximizes the average output SNR is selected within a codebook of pre-defined orthogonal beam-vectors spanning the whole 3-D space. The system performance is evaluated in terms of beam-forming gain, coherence bandwidth of the beam-formed channel, and average spectral efficiency in a band of 2 GHz. The simulation results show that the beam-switching technique improves the system performance; the improvement is proportional to the array size and is observed both in LOS and NLOS cases (where the LOS path is obstructed). The average spectral efficiency is compared to that of an optimal beam-forming scheme, showing an acceptable performance penalty. Finally, alternative analog beam-forming techniques are investigated and compared against the beam-switching method. The investigation shows that within the class of analog beam-forming, and for the considered channel, beam-switching is a valid cost-performance trade-off

    Modelos de canal para sistemas MIMO

    Get PDF
    Doutoramento em Engenharia ElectrotécnicaSystems equipped with multiple antennas at the transmitter and at the receiver, known as MIMO (Multiple Input Multiple Output) systems, offer higher capacities, allowing an efficient exploitation of the available spectrum and/or the employment of more demanding applications. It is well known that the radio channel is characterized by multipath propagation, a phenomenon deemed problematic and whose mitigation has been achieved through techniques such as diversity, beamforming or adaptive antennas. By exploring conveniently the spatial domain MIMO systems turn the characteristics of the multipath channel into an advantage and allow creating multiple parallel and independent virtual channels. However, the achievable benefits are constrained by the propagation channel’s characteristics, which may not always be ideal. This work focuses on the characterization of the MIMO radio channel. It begins with the presentation of the fundamental results from information theory that triggered the interest on these systems, including the discussion of some of their potential benefits and a review of the existing channel models for MIMO systems. The characterization of the MIMO channel developed in this work is based on experimental measurements of the double-directional channel. The measurement system is based on a vector network analyzer and a two-dimensional positioning platform, both controlled by a computer, allowing the measurement of the channel’s frequency response at the locations of a synthetic array. Data is then processed using the SAGE (Space-Alternating Expectation-Maximization) algorithm to obtain the parameters (delay, direction of arrival and complex amplitude) of the channel’s most relevant multipath components. Afterwards, using a clustering algorithm these data are grouped into clusters. Finally, statistical information is extracted allowing the characterization of the channel’s multipath components. The information about the multipath characteristics of the channel, induced by existing scatterers in the propagation scenario, enables the characterization of MIMO channel and thus to evaluate its performance. The method was finally validated using MIMO measurements.Os sistemas equipados com múltiplas antenas no emissor e no recetor, conhecidos como sistemas MIMO (Multiple Input Multiple Output), oferecem capacidades mais elevadas, permitindo melhor rentabilização do espectro e/ou utilização de aplicações mais exigentes. É sobejamente sabido que o canal rádio é caracterizado por propagação multipercurso, fenómeno considerado problemático e cuja mitigação tem sido conseguida através de técnicas como diversidade, formatação de feixe ou antenas adaptativas. Explorando convenientemente o domínio espacial os sistemas MIMO transformam as características multipercurso do canal numa mais-valia e permitem criar vários canais virtuais, paralelos e independentes. Contudo, os benefícios atingíveis são condicionados pelas características do canal de propagação, que poderão não ser sempre as ideais. Este trabalho centra-se na caracterização do canal rádio para sistemas MIMO. Inicia-se com a apresentação dos resultados fundamentais da teoria da informação que despoletaram todo o entusiamo em torno deste tipo de sistemas, sendo discutidas algumas das suas potencialidades e uma revisão dos modelos existentes para sistemas MIMO. A caracterização do canal MIMO desenvolvida neste trabalho assenta em medidas experimentais do canal direcional adquiridas em dupla via. O sistema de medida é baseado num analisador de redes vetorial e numa plataforma de posicionamento bidimensional, ambos controlados por um computador, permitindo obter a resposta em frequência do canal rádio nos vários pontos correspondentes à localização dos elementos de um agregado virtual. As medidas são posteriormente processadas com o algoritmo SAGE (Space-Alternating Expectation-Maximization), de forma a obter os parâmetros (atraso, direção de chegada e amplitude complexa) das componentes multipercurso mais significativas. Seguidamente, estes dados são tratados com um algoritmo de classificação (clustering) e organizados em grupos. Finalmente é extraída informação estatística que permite caracterizar o comportamento das componentes multipercurso do canal. A informação acerca das características multipercurso do canal, induzidas pelos espalhadores (scatterers) existentes no cenário de propagação, possibilita a caracterização do canal MIMO e assim avaliar o seu desempenho. O método foi por fim validado com medidas MIMO
    corecore