87 research outputs found
Antenna Selection With Beam Squint Compensation for Integrated Sensing and Communications
Next-generation wireless networks strive for higher communication rates,
ultra-low latency, seamless connectivity, and high-resolution sensing
capabilities. To meet these demands, terahertz (THz)-band signal processing is
envisioned as a key technology offering wide bandwidth and sub-millimeter
wavelength. Furthermore, THz integrated sensing and communications (ISAC)
paradigm has emerged jointly access spectrum and reduced hardware costs through
a unified platform. To address the challenges in THz propagation, THz-ISAC
systems employ extremely large antenna arrays to improve the beamforming gain
for communications with high data rates and sensing with high resolution.
However, the cost and power consumption of implementing fully digital
beamformers are prohibitive. While hybrid analog/digital beamforming can be a
potential solution, the use of subcarrier-independent analog beamformers leads
to the beam-squint phenomenon where different subcarriers observe distinct
directions because of adopting the same analog beamformer across all
subcarriers. In this paper, we develop a sparse array architecture for THz-ISAC
with hybrid beamforming to provide a cost-effective solution. We analyze the
antenna selection problem under beam-squint influence and introduce a manifold
optimization approach for hybrid beamforming design. To reduce computational
and memory costs, we propose novel algorithms leveraging grouped subarrays,
quantized performance metrics, and sequential optimization. These approaches
yield a significant reduction in the number of possible subarray
configurations, which enables us to devise a neural network with classification
model to accurately perform antenna selection.Comment: 14pages10figures, submitted to IEE
Rate-splitting multiple access for non-terrestrial communication and sensing networks
Rate-splitting multiple access (RSMA) has emerged as a powerful and flexible
non-orthogonal transmission, multiple access (MA) and interference management
scheme for future wireless networks. This thesis is concerned with the application of
RSMA to non-terrestrial communication and sensing networks. Various scenarios
and algorithms are presented and evaluated.
First, we investigate a novel multigroup/multibeam multicast beamforming strategy
based on RSMA in both terrestrial multigroup multicast and multibeam satellite
systems with imperfect channel state information at the transmitter (CSIT). The
max-min fairness (MMF)-degree of freedom (DoF) of RSMA is derived and shown
to provide gains compared with the conventional strategy. The MMF beamforming
optimization problem is formulated and solved using the weighted minimum mean
square error (WMMSE) algorithm. Physical layer design and link-level simulations
are also investigated. RSMA is demonstrated to be very promising for multigroup
multicast and multibeam satellite systems taking into account CSIT uncertainty
and practical challenges in multibeam satellite systems.
Next, we extend the scope of research from multibeam satellite systems to satellite-
terrestrial integrated networks (STINs). Two RSMA-based STIN schemes are
investigated, namely the coordinated scheme relying on CSI sharing and the co-
operative scheme relying on CSI and data sharing. Joint beamforming algorithms
are proposed based on the successive convex approximation (SCA) approach to
optimize the beamforming to achieve MMF amongst all users. The effectiveness and
robustness of the proposed RSMA schemes for STINs are demonstrated.
Finally, we consider RSMA for a multi-antenna integrated sensing and communications (ISAC) system, which simultaneously serves multiple communication users
and estimates the parameters of a moving target. Simulation results demonstrate
that RSMA is beneficial to both terrestrial and multibeam satellite ISAC systems by
evaluating the trade-off between communication MMF rate and sensing Cramer-Rao
bound (CRB).Open Acces
Security and Privacy for Modern Wireless Communication Systems
The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in node–edge–cloud computation; security and privacy design for low-power wide-area IoT networks; security and privacy design for vehicle networks; security and privacy design for underwater communications networks
Modelling, Dimensioning and Optimization of 5G Communication Networks, Resources and Services
This reprint aims to collect state-of-the-art research contributions that address challenges in the emerging 5G networks design, dimensioning and optimization. Designing, dimensioning and optimization of communication networks resources and services have been an inseparable part of telecom network development. The latter must convey a large volume of traffic, providing service to traffic streams with highly differentiated requirements in terms of bit-rate and service time, required quality of service and quality of experience parameters. Such a communication infrastructure presents many important challenges, such as the study of necessary multi-layer cooperation, new protocols, performance evaluation of different network parts, low layer network design, network management and security issues, and new technologies in general, which will be discussed in this book
D4.2 Intelligent D-Band wireless systems and networks initial designs
This deliverable gives the results of the ARIADNE project's Task 4.2: Machine Learning based network intelligence. It presents the work conducted on various aspects of network management to deliver system level, qualitative solutions that leverage diverse machine learning techniques. The different chapters present system level, simulation and algorithmic models based on multi-agent reinforcement learning, deep reinforcement learning, learning automata for complex event forecasting, system level model for proactive handovers and resource allocation, model-driven deep learning-based channel estimation and feedbacks as well as strategies for deployment of machine learning based solutions. In short, the D4.2 provides results on promising AI and ML based methods along with their limitations and potentials that have been investigated in the ARIADNE project
Robust cell-free mmWave/sub-THz access using minimal coordination and coarse synchronization
This study investigates simpler alternatives to coherent joint transmission
for supporting robust connectivity against signal blockage in mmWave/sub-THz
access networks. By taking an information-theoretic viewpoint, we demonstrate
analytically that with a careful design, full macrodiversity gains and
significant SNR gains can be achieved through canonical receivers and minimal
coordination and synchronization requirements at the infrastructure side. Our
proposed scheme extends non-coherent joint transmission by employing a special
form of diversity to counteract artificially induced deep fades that would
otherwise make this technique often compare unfavorably against standard
transmitter selection schemes. Additionally, the inclusion of an Alamouti-like
space-time coding layer is shown to recover a significant fraction of the
optimal performance. Our conclusions are based on an insightful multi-point
intermittent block fading channel model that enables rigorous ergodic and
outage rate analysis, while also considering timing offsets due to imperfect
delay compensation. Although simplified, our approach captures the essential
features of modern mmWave/sub-THz communications, thereby providing practical
design guidelines for realistic systems
Full-Duplex Wireless for 6G: Progress Brings New Opportunities and Challenges
The use of in-band full-duplex (FD) enables nodes to simultaneously transmit
and receive on the same frequency band, which challenges the traditional
assumption in wireless network design. The full-duplex capability enhances
spectral efficiency and decreases latency, which are two key drivers pushing
the performance expectations of next-generation mobile networks. In less than
ten years, in-band FD has advanced from being demonstrated in research labs to
being implemented in standards and products, presenting new opportunities to
utilize its foundational concepts. Some of the most significant opportunities
include using FD to enable wireless networks to sense the physical environment,
integrate sensing and communication applications, develop integrated access and
backhaul solutions, and work with smart signal propagation environments powered
by reconfigurable intelligent surfaces. However, these new opportunities also
come with new challenges for large-scale commercial deployment of FD
technology, such as managing self-interference, combating cross-link
interference in multi-cell networks, and coexistence of dynamic time division
duplex, subband FD and FD networks.Comment: 21 pages, 15 figures, accepted to an IEEE Journa
- …