7 research outputs found
Design and Analysis of Wideband In-Band-Full-Duplex FR2-IAB Networks
This paper develops a 3GPP-inspired design for the in-band-full-duplex (IBFD)
integrated access and backhaul (IAB) networks in the frequency range 2 (FR2)
band, which can enhance the spectral efficiency (SE) and coverage while
reducing the latency. However, the self-interference (SI), which is usually
more than 100 dB higher than the signal-of-interest, becomes the major
bottleneck in developing these IBFD networks. We design and analyze a
subarray-based hybrid beamforming IBFD-IAB system with the RF beamformers
obtained via RF codebooks given by a modified Linde-Buzo-Gray (LBG) algorithm.
The SI is canceled in three stages, where the first stage of antenna isolation
is assumed to be successfully deployed. The second stage consists of the
optical domain (OD)-based RF cancellation, where cancelers are connected with
the RF chain pairs. The third stage is comprised of the digital cancellation
via successive interference cancellation followed by minimum mean-squared error
baseband receiver. Multiuser interference in the access link is canceled by
zero-forcing at the IAB-node transmitter. Simulations show that under 400 MHz
bandwidth, our proposed OD-based RF cancellation can achieve around 25 dB of
cancellation with 100 taps. Moreover, the higher the hardware impairment and
channel estimation error, the worse digital cancellation ability we can obtain
Design of Full-Duplex Millimeter-Wave Integrated Access and Backhaul Networks
One of the key technologies for the future cellular networks is full duplex
(FD)-enabled integrated access and backhaul (IAB) networks operating in the
millimeter-wave (mmWave) frequencies. The main challenge in realizing FD-IAB
networks is mitigating the impact of self-interference (SI) in the wideband
mmWave frequencies. In this article, we first introduce the 3GPP IAB network
architectures and wideband mmWave channel models. By utilizing the
subarray-based hybrid precoding scheme at the FD-IAB node, multiuser
interference is mitigated using zero-forcing at the transmitter, whereas the
residual SI after successfully deploying antenna and analog cancellation is
canceled by a minimum mean square error baseband combiner at the receiver. The
spectral efficiency (SE) is evaluated for the RF insertion loss (RFIL) with
different kinds of phase shifters and channel uncertainty. Simulation results
show that, in the presence of the RFIL, the almost double SE, which is close to
that obtained from fully connected hybrid precoding, can be achieved as
compared to half duplex systems when the uncertainties are of low strength
In-band-full-duplex integrated access and backhaul enabled next generation wireless networks
In sixth generation (6G) wireless networks, the severe traffic congestion in the microwave frequencies motivates the exploration of the large available bandwidth in the millimetre-wave (mmWave) frequencies to achieve higher network capacity and data rate. Since large-scale antenna arrays and dense base station deployment are required, the hybrid beamforming architecture and the recently proposed integrated access and backhaul (IAB) networks become potential candidates for providing cost and hardware-friendly techniques for 6G wireless networks. In addition, in-band-full-duplex (IBFD) has been recently paid much more research attention since it can make the transmission and reception occur in the same time and frequency band, which nearly doubles the communication spectral efficiency (SE) compared with state-of-the-art half-duplex (HD) systems. Since 6G will explore sensing as its new capability, future wireless networks can go far beyond communications. Motivated by this, the development of integrated sensing and communications (ISAC) systems, where radar and communication systems share the same spectrum resources and hardware, has become one of the major goals in 6G. This PhD thesis focuses on the design and analysis of IBFD-IAB wireless networks in the frequency range 2 (FR2) band (≥ 24.250 GHz) at mmWave frequencies for the potential use in 6G.
Firstly, we develop a novel design for the single-cell FR2-IBFD-IAB networks with subarray-based hybrid beamforming, which can enhance the SE and coverage while reducing the latency. The radio frequency (RF) beamformers are obtained via RF codebooks given by a modified matrix-wise Linde-Buzo-Gray (LBG) algorithm. The self-interference (SI) is cancelled in three stages, where the first stage of antenna isolation is assumed to be successfully deployed. The second stage consists of the optical domain-based RF cancellation, where cancellers are connected with the RF chain pairs. The third stage is comprised of the digital cancellation via successive interference cancellation followed by minimum mean-squared error (MSE) baseband receiver. Multiuser interference in the access link is cancelled by zero-forcing at the IAB-node transmitter. The proposed codebook algorithm avoids undesirable low-rank behaviour, while the proposed staged-SI cancellation (SIC) shows satisfactory cancellation performance in the wideband IBFD scenario.
However, the system performance can be affected by the hardware impairments (HWI) and RF effective channel estimation errors.
Secondly, we study an FR2-IBFD-ISAC-IAB network for vehicle-to-everything communications, where the IAB-node acts as a roadside unit performing sensing and communication simultaneously (i.e., at the same time and frequency band). The SI due to the IBFD operation will be cancelled in the propagation, analogue, and digital domains; only the residual SI (RSI) is reserved for performance analysis. Considering the subarray-based hybrid beamforming structure, including HWI and RF effective SI channel estimation error, the unscented Kalman filter is used for tracking multiple vehicles in the studied scenario. The proposed system shows an enhanced SE compared with the HD system, and the tracking MSEs averaged across all vehicles of each state parameter are close to their posterior Cramér-Rao lower bounds.
Thirdly, we analyse the performance of the multi-cell wideband single-hop backhaul FR2-IBFD-IAB networks by using stochastic geometry analysis. We model the wired-connected next generation NodeBs (gNBs) as the Matérn hard-core point process (MHCPP) to meet the real-world deployment requirement and reduce the cost caused by wired connection in the network. We first derive association probabilities that reflect how likely the typical user-equipment is served by a gNB or an IAB-node based on the maximum long-term averaged biased-received-desired-signal power criteria. Further, by leveraging the composite Gamma-Lognormal distribution, we derive results for the signal to interference plus noise ratio coverage, capacity with outage, and ergodic capacity of the network. In order to assess the impact of noise, we consider the sidelobe gain on inter-cell interference links and the analogue to digital converter quantization noise. Compared with the HD transmission, the designated system shows an enhanced capacity when the SIC operates successfully. We also study how the power bias and density ratio of the IAB-node to gNB, and the hard-core distance can affect system performance.
Overall, this thesis aims to contribute to the research efforts of shaping the 6G wireless networks by designing and analysing the FR2-IBFD-IAB inspired networks in the FR2 band at mmWave frequencies that will be potentially used in 6G for both communication only and ISAC scenarios
LiDAR aided simulation pipeline for wireless communication in vehicular traffic scenarios
Abstract. Integrated Sensing and Communication (ISAC) is a modern technology under development for Sixth Generation (6G) systems. This thesis focuses on creating a simulation pipeline for dynamic vehicular traffic scenarios and a novel approach to reducing wireless communication overhead with a Light Detection and Ranging (LiDAR) based system. The simulation pipeline can be used to generate data sets for numerous problems. Additionally, the developed error model for vehicle detection algorithms can be used to identify LiDAR performance with respect to different parameters like LiDAR height, range, and laser point density. LiDAR behavior on traffic environment is provided as part of the results in this study. A periodic beam index map is developed by capturing antenna azimuth and elevation angles, which denote maximum Reference Signal Receive Power (RSRP) for a simulated receiver grid on the road and classifying areas using Support Vector Machine (SVM) algorithm to reduce the number of Synchronization Signal Blocks (SSBs) that are needed to be sent in Vehicle to Infrastructure (V2I) communication. This approach effectively reduces the wireless communication overhead in V2I communication
Experimental Investigations of Millimeter Wave Beamforming
The millimeter wave (mmW) band, commonly referred to as the frequency band between 30 GHz and 300 GHz, is seen as a possible candidate to increase achievable rates for mobile applications due to the existence of free spectrum. However, the high path loss necessitates the use of highly directional antennas. Furthermore, impairments and power constraints make it difficult to provide full digital beamforming systems. In this thesis, we approach this problem by proposing effective beam alignment and beam tracking algorithms for low-complex analog beamforming (ABF) systems, showing their applicability by experimental demonstration. After taking a closer look at particular features of the mmW channel properties and introducing the beamforming as a spatial filter, we begin our investigations with the application of detection theory for the non-convex beam alignment problem. Based on an M-ary hypothesis test, we derive algorithms for defining the length of the training signal efficiently. Using the concept of black-box optimization algorithms, which allow optimization of non-convex algorithms, we propose a beam alignment algorithm for codebook-based ABF based systems, which is shown to reduce the training overhead significantly. As a low-complex alternative, we propose a two-staged gradient-based beam alignment algorithm that uses convex optimization strategies after finding a subregion of the beam alignment function in which the function can be regarded convex. This algorithm is implemented in a real-time prototype system and shows its superiority over the exhaustive search approach in simulations and experiments. Finally, we propose a beam tracking algorithm for supporting mobility. Experiments and comparisons with a ray-tracing channel model show that it can be used efficiently in line of sight (LoS) and non line of sight (NLoS) scenarios for walking-speed movements
RLOps:Development Life-cycle of Reinforcement Learning Aided Open RAN
Radio access network (RAN) technologies continue to witness massive growth,
with Open RAN gaining the most recent momentum. In the O-RAN specifications,
the RAN intelligent controller (RIC) serves as an automation host. This article
introduces principles for machine learning (ML), in particular, reinforcement
learning (RL) relevant for the O-RAN stack. Furthermore, we review
state-of-the-art research in wireless networks and cast it onto the RAN
framework and the hierarchy of the O-RAN architecture. We provide a taxonomy of
the challenges faced by ML/RL models throughout the development life-cycle:
from the system specification to production deployment (data acquisition, model
design, testing and management, etc.). To address the challenges, we integrate
a set of existing MLOps principles with unique characteristics when RL agents
are considered. This paper discusses a systematic life-cycle model development,
testing and validation pipeline, termed: RLOps. We discuss all fundamental
parts of RLOps, which include: model specification, development and
distillation, production environment serving, operations monitoring,
safety/security and data engineering platform. Based on these principles, we
propose the best practices for RLOps to achieve an automated and reproducible
model development process.Comment: 17 pages, 6 figrue