312 research outputs found
Recommended from our members
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
DNN-DANM: A High-Accuracy Two-Dimensional DOA Estimation Method Using Practical RIS
Reconfigurable intelligent surface (RIS) or intelligent reflecting surface
(IRS) has been an attractive technology for future wireless communication and
sensing systems. However, in the practical RIS, the mutual coupling effect
among RIS elements, the reflection phase shift, and amplitude errors will
degrade the RIS performance significantly. This paper investigates the
two-dimensional direction-of-arrival (DOA) estimation problem in the scenario
using a practical RIS. After formulating the system model with the mutual
coupling effect and the reflection phase/amplitude errors of the RIS, a novel
DNNDANM method is proposed for the DOA estimation by combining the deep neural
network (DNN) and the decoupling atomic norm minimization (DANM). The DNN step
reconstructs the received signal from the one with RIS impairments, and the
DANM step exploits the signal sparsity in the two-dimensional spatial domain.
Additionally, a semi-definite programming (SDP) method with low computational
complexity is proposed to solve the atomic minimization problem. Finally, both
simulation and prototype are carried out to show estimation performance, and
the proposed method outperforms the existing methods in the two-dimensional DOA
estimation with low complexity in the scenario with practical RIS.Comment: 11 pages, 12 figure
NoncovANM: Gridless DOA Estimation for LPDF System
Direction of arrival (DOA) estimation is an important research in the area of
array signal processing, and has been studied for decades. High resolution DOA
estimation requires large array aperture, which leads to the increase of
hardware cost. Besides, high accuracy DOA estimation methods usually have high
computational complexity. In this paper, the problem of decreasing the hardware
cost and algorithm complexity is addressed. First, considering the ability of
flexible controlling the electromagnetic waves and low-cost, an intelligent
reconfigurable surface (IRS)-aided low-cost passive direction finding (LPDF)
system is developed, where only one fully functional receiving channel is
adopted. Then, the sparsity of targets direction in the spatial domain is
exploited by formulating an atomic norm minimization (ANM) problem to estimate
the DOA. Traditionally, solving ANM problem is complex and cannot be realized
efficiently. Hence, a novel nonconvex-based ANM (NC-ANM) method is proposed by
gradient threshold iteration, where a perturbation is introduced to avoid
falling into saddle points. The theoretical analysis for the convergence of the
NC-ANM method is also given. Moreover, the corresponding Cram\'er-Rao lower
bound (CRLB) in the LPDF system is derived, and taken as the referred bound of
the DOA estimation. Simulation results show that the proposed method
outperforms the compared methods in the DOA estimation with lower computational
complexity in the LPDF system.Comment: 11 pages, 8 figure
Decision-Directed Hybrid RIS Channel Estimation with Minimal Pilot Overhead
To reap the benefits of reconfigurable intelligent surfaces (RIS), channel
state information (CSI) is generally required. However, CSI acquisition in RIS
systems is challenging and often results in very large pilot overhead,
especially in unstructured channel environments. Consequently, the RIS channel
estimation problem has attracted a lot of interest and also been a subject of
intense study in recent years. In this paper, we propose a decision-directed
RIS channel estimation framework for general unstructured channel models. The
employed RIS contains some hybrid elements that can simultaneously reflect and
sense the incoming signal. We show that with the help of the hybrid RIS
elements, it is possible to accurately recover the CSI with a pilot overhead
proportional to the number of users. Therefore, the proposed framework
substantially improves the system spectral efficiency compared to systems with
passive RIS arrays since the pilot overhead in passive RIS systems is
proportional to the number of RIS elements times the number of users. We also
perform a detailed spectral efficiency analysis for both the pilot-directed and
decision-directed frameworks. Our analysis takes into account both the channel
estimation and data detection errors at both the RIS and the BS. Finally, we
present numerous simulation results to verify the accuracy of the analysis as
well as to show the benefits of the proposed decision-directed framework.Comment: submitted for journal publication, 13 pages, 7 figure
Low-Rank Channel Estimation for Millimeter Wave and Terahertz Hybrid MIMO Systems
Massive multiple-input multiple-output (MIMO) is one of the fundamental technologies for 5G and beyond. The increased number of antenna elements at both the transmitter and the receiver translates into a large-dimension channel matrix. In addition, the power requirements for the massive MIMO systems are high, especially when fully digital transceivers are deployed. To address this challenge, hybrid analog-digital transceivers are considered a viable alternative. However, for hybrid systems, the number of observations during each channel use is reduced. The high dimensions of the channel matrix and the reduced number of observations make the channel estimation task challenging. Thus, channel estimation may require increased training overhead and higher computational complexity.
The need for high data rates is increasing rapidly, forcing a shift of wireless communication towards higher frequency bands such as millimeter Wave (mmWave) and terahertz (THz). The wireless channel at these bands is comprised of only a few dominant paths. This makes the channel sparse in the angular domain and the resulting channel matrix has a low rank. This thesis aims to provide channel estimation solutions benefiting from the low rankness and sparse nature of the channel. The motivation behind this thesis is to offer a desirable trade-off between training overhead and computational complexity while providing a desirable estimate of the channel
Blind Goal-Oriented Massive Access for Future Wireless Networks
Emerging communication networks are envisioned to support massive wireless
connectivity of heterogeneous devices with sporadic traffic and diverse
requirements in terms of latency, reliability, and bandwidth. Providing
multiple access to an increasing number of uncoordinated users and sharing the
limited resources become essential in this context. In this work, we revisit
the random access (RA) problem and exploit the continuous angular group
sparsity feature of wireless channels to propose a novel RA strategy that
provides low latency, high reliability, and massive access with limited
bandwidth resources in an all-in-one package. To this end, we first design a
reconstruction-free goal-oriented optimization problem, which only preserves
the angular information required to identify the active devices. To solve this,
we propose an alternating direction method of multipliers (ADMM) and derive
closed-form expressions for each ADMM step. Then, we design a clustering
algorithm that assigns the users in specific groups from which we can identify
active stationary devices by their angles. For mobile devices, we propose an
alternating minimization algorithm to recover their data and their channel
gains simultaneously, which allows us to identify active mobile users.
Simulation results show significant performance gains in terms of active user
detection and false alarm probabilities as compared to state-of-the-art RA
schemes, even with limited number of preambles. Moreover, unlike prior work,
the performance of the proposed blind goal-oriented massive access does not
depend on the number of devices
Interference Removal for Radar/Communication Co-existence: the Random Scattering Case
In this paper we consider an un-cooperative spectrum sharing scenario,
wherein a radar system is to be overlaid to a pre-existing wireless
communication system. Given the order of magnitude of the transmitted powers in
play, we focus on the issue of interference mitigation at the communication
receiver. We explicitly account for the reverberation produced by the
(typically high-power) radar transmitter whose signal hits scattering centers
(whether targets or clutter) producing interference onto the communication
receiver, which is assumed to operate in an un-synchronized and un-coordinated
scenario. We first show that receiver design amounts to solving a non-convex
problem of joint interference removal and data demodulation: next, we introduce
two algorithms, both exploiting sparsity of a proper representation of the
interference and of the vector containing the errors of the data block. The
first algorithm is basically a relaxed constrained Atomic Norm minimization,
while the latter relies on a two-stage processing structure and is based on
alternating minimization. The merits of these algorithms are demonstrated
through extensive simulations: interestingly, the two-stage alternating
minimization algorithm turns out to achieve satisfactory performance with
moderate computational complexity
Role of Reconfigurable Intelligent Surfaces in 6G Radio Localization: Recent Developments, Opportunities, Challenges, and Applications
Reconfigurable intelligent surfaces (RISs) are seen as a key enabler low-cost
and energy-efficient technology for 6G radio communication and localization. In
this paper, we aim to provide a comprehensive overview of the current research
progress on the RIS technology in radio localization for 6G. Particularly, we
discuss the RIS-assisted radio localization taxonomy and review the studies of
RIS-assisted radio localization for different network scenarios, bands of
transmission, deployment environments, as well as near-field operations. Based
on this review, we highlight the future research directions, associated
technical challenges, real-world applications, and limitations of RIS-assisted
radio localization
- …