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Advanced Techniques for High-Throughput Cellular Communications
The next generation wireless communication systems require ubiquitous high-throughput mobile connectivity under a range of challenging network settings (urban versus rural, high device density, mobility, etc). To improve the performance of the system, the physical layer design is of great importance. The previous research on improving the physical layer properties includes: a) highly directional transmissions that can enhance the throughput and spatial reuse; b) enhanced MIMO that can eliminate
contention, enabling linear increase of capacity with number of antennas; c) mmWave technologies which operate on GHz bandwidth to over substantially higher throughput; d) better cooperative spectrum sharing with cognitive radios; e) better multiple access method which can mitigate multiuser interference and allow more multi-users.
This dissertation addresses several techniques in the physical layer design of the next generation wireless communication systems. In chapter two, an orthogonal frequency division with code division multiple access (OFDM-CDMA) systems is proposed and a polyphase code is used to improve multiple access performance and make the OFDM signal satisfy the peak to average ratio (PAPR) constraint. Chapter three studies the I/Q imbalance for direct down converter. For wideband transmitter and receiver that use direct conversion for I/Q sampling, the I/Q imbalance becomes a critical issue. With higher I/Q imbalance, there will be higher degradation in quadrature amplitude modulation, which degrades the throughput tremendously. Chapter four investigate a problem of spectrum sharing for cognitive wideband communication. An energy-efficient sub-Nyquist sampling algorithm is developed for optimal sampling and spectrum sensing. In chapter ve, we study the channel estimation of millimeter wave full-dimensional MIMO communication. The problem is formulated as an atomic-norm minimization problem and algorithms are derived for the channel estimation in different situations.
In this thesis, mathematical optimization is applied as the main approach to analyze and solve the problems in the physical layer of wireless communication so that the high-throughput is achieved. The algorithms are derived along with the theoretical analysis, which are validated with numerical results
Space Time MUSIC: Consistent Signal Subspace Estimation for Wide-band Sensor Arrays
Wide-band Direction of Arrival (DOA) estimation with sensor arrays is an
essential task in sonar, radar, acoustics, biomedical and multimedia
applications. Many state of the art wide-band DOA estimators coherently process
frequency binned array outputs by approximate Maximum Likelihood, Weighted
Subspace Fitting or focusing techniques. This paper shows that bin signals
obtained by filter-bank approaches do not obey the finite rank narrow-band
array model, because spectral leakage and the change of the array response with
frequency within the bin create \emph{ghost sources} dependent on the
particular realization of the source process. Therefore, existing DOA
estimators based on binning cannot claim consistency even with the perfect
knowledge of the array response. In this work, a more realistic array model
with a finite length of the sensor impulse responses is assumed, which still
has finite rank under a space-time formulation. It is shown that signal
subspaces at arbitrary frequencies can be consistently recovered under mild
conditions by applying MUSIC-type (ST-MUSIC) estimators to the dominant
eigenvectors of the wide-band space-time sensor cross-correlation matrix. A
novel Maximum Likelihood based ST-MUSIC subspace estimate is developed in order
to recover consistency. The number of sources active at each frequency are
estimated by Information Theoretic Criteria. The sample ST-MUSIC subspaces can
be fed to any subspace fitting DOA estimator at single or multiple frequencies.
Simulations confirm that the new technique clearly outperforms binning
approaches at sufficiently high signal to noise ratio, when model mismatches
exceed the noise floor.Comment: 15 pages, 10 figures. Accepted in a revised form by the IEEE Trans.
on Signal Processing on 12 February 1918. @IEEE201
Localization of DOA trajectories -- Beyond the grid
The direction of arrival (DOA) estimation algorithms are crucial in
localizing acoustic sources. Traditional localization methods rely on
block-level processing to extract the directional information from multiple
measurements processed together. However, these methods assume that DOA remains
constant throughout the block, which may not be true in practical scenarios.
Also, the performance of localization methods is limited when the true
parameters do not lie on the parameter search grid. In this paper we propose
two trajectory models, namely the polynomial and bandlimited trajectory models,
to capture the DOA dynamics. To estimate trajectory parameters, we adopt two
gridless algorithms: i) Sliding Frank-Wolfe (SFW), which solves the Beurling
LASSO problem and ii) Newtonized Orthogonal Matching Pursuit (NOMP), which
improves over OMP using cyclic refinement. Furthermore, we extend our analysis
to include wideband processing. The simulation results indicate that the
proposed trajectory localization algorithms exhibit improved performance
compared to grid-based methods in terms of resolution, robustness to noise, and
computational efficiency
Time-Frequency-Space Transmit Design and Signal Processing with Dynamic Subarray for Terahertz Integrated Sensing and Communication
Terahertz (THz) integrated sensing and communication (ISAC) enables
simultaneous data transmission with Terabit-per-second (Tbps) rate and
millimeter-level accurate sensing. To realize such a blueprint, ultra-massive
antenna arrays with directional beamforming are used to compensate for severe
path loss in the THz band. In this paper, the time-frequency-space transmit
design is investigated for THz ISAC to generate time-varying scanning sensing
beams and stable communication beams. Specifically, with the dynamic
array-of-subarray (DAoSA) hybrid beamforming architecture and multi-carrier
modulation, two ISAC hybrid precoding algorithms are proposed, namely, a
vectorization (VEC) based algorithm that outperforms existing ISAC hybrid
precoding methods and a low-complexity sensing codebook assisted (SCA)
approach. Meanwhile, coupled with the transmit design, parameter estimation
algorithms are proposed to realize high-accuracy sensing, including a wideband
DAoSA MUSIC (W-DAoSA-MUSIC) method for angle estimation and a sum-DFT-GSS
(S-DFT-GSS) approach for range and velocity estimation. Numerical results
indicate that the proposed algorithms can realize centi-degree-level angle
estimation accuracy and millimeter-level range estimation accuracy, which are
one or two orders of magnitudes better than the methods in the millimeter-wave
band. In addition, to overcome the cyclic prefix limitation and Doppler effects
in the THz band, an inter-symbol interference- and inter-carrier
interference-tackled sensing algorithm is developed to refine sensing
capabilities for THz ISAC
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