167 research outputs found
Exploitation of Robust AoA Estimation and Low Overhead Beamforming in mmWave MIMO System
The limited spectral resource for wireless communications and dramatic proliferation of new applications and services directly necessitate the exploitation of millimeter wave (mmWave) communications. One critical enabling technology for mmWave communications is multi-input multi-output (MIMO), which enables other important physical layer techniques, specifically beamforming and antenna array based angle of arrival (AoA) estimation. Deployment of beamforming and AoA estimation has many challenges. Significant training and feedback overhead is required for beamforming, while conventional AoA estimation methods are not fast or robust. Thus, in this thesis, new algorithms are designed for low overhead beamforming, and robust AoA estimation with significantly reduced signal samples (snapshots).
The basic principle behind the proposed low overhead beamforming algorithm in time-division duplex (TDD) systems is to increase the beam serving period for the reduction of the feedback frequency. With the knowledge of location and speed of each candidate user equipment (UE), the codeword can be selected from the designed multi-pattern codebook, and the corresponding serving period can be estimated. The UEs with long serving period and low interference are selected and served simultaneously. This algorithm is proved to be effective in keeping the high data rate of conventional codebook-based beamforming, while the feedback required for codeword selection can be cut down.
A fast and robust AoA estimation algorithm is proposed as the basis of the low overhead beamforming for frequency-division duplex (FDD) systems. This algorithm utilizes uplink transmission signals to estimate the real-time AoA for angle-based beamforming in environments with different signal to noise ratios (SNR). Two-step neural network models are designed for AoA estimation. Within the angular group classified by the first model, the second model further estimates AoA with high accuracy. It is proved that these AoA estimation models work well with few signal snapshots, and are robust to applications in low SNR environments. The proposed AoA estimation algorithm based beamforming generates beams without using reference signals. Therefore, the low overhead beamforming can be achieved in FDD systems.
With the support of proposed algorithms, the mmWave resource can be leveraged to meet challenging requirements of new applications and services in wireless communication systems
Millimeter Wave MIMO Channel Estimation Based on Adaptive Compressed Sensing
Multiple-input multiple-output (MIMO) systems are well suited for
millimeter-wave (mmWave) wireless communications where large antenna arrays can
be integrated in small form factors due to tiny wavelengths, thereby providing
high array gains while supporting spatial multiplexing, beamforming, or antenna
diversity. It has been shown that mmWave channels exhibit sparsity due to the
limited number of dominant propagation paths, thus compressed sensing
techniques can be leveraged to conduct channel estimation at mmWave
frequencies. This paper presents a novel approach of constructing beamforming
dictionary matrices for sparse channel estimation using the continuous basis
pursuit (CBP) concept, and proposes two novel low-complexity algorithms to
exploit channel sparsity for adaptively estimating multipath channel parameters
in mmWave channels. We verify the performance of the proposed CBP-based
beamforming dictionary and the two algorithms using a simulator built upon a
three-dimensional mmWave statistical spatial channel model, NYUSIM, that is
based on real-world propagation measurements. Simulation results show that the
CBP-based dictionary offers substantially higher estimation accuracy and
greater spectral efficiency than the grid-based counterpart introduced by
previous researchers, and the algorithms proposed here render better
performance but require less computational effort compared with existing
algorithms.Comment: 7 pages, 5 figures, in 2017 IEEE International Conference on
Communications Workshop (ICCW), Paris, May 201
A Survey of Beam Management for mmWave and THz Communications Towards 6G
Communication in millimeter wave (mmWave) and even terahertz (THz) frequency
bands is ushering in a new era of wireless communications. Beam management,
namely initial access and beam tracking, has been recognized as an essential
technique to ensure robust mmWave/THz communications, especially for mobile
scenarios. However, narrow beams at higher carrier frequency lead to huge beam
measurement overhead, which has a negative impact on beam acquisition and
tracking. In addition, the beam management process is further complicated by
the fluctuation of mmWave/THz channels, the random movement patterns of users,
and the dynamic changes in the environment. For mmWave and THz communications
toward 6G, we have witnessed a substantial increase in research and industrial
attention on artificial intelligence (AI), reconfigurable intelligent surface
(RIS), and integrated sensing and communications (ISAC). The introduction of
these enabling technologies presents both open opportunities and unique
challenges for beam management. In this paper, we present a comprehensive
survey on mmWave and THz beam management. Further, we give some insights on
technical challenges and future research directions in this promising area.Comment: accepted by IEEE Communications Surveys & Tutorial
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