31 research outputs found
Collaborative Beamforming for Distributed Wireless Ad Hoc Sensor Networks
The performance of collaborative beamforming is analyzed using the theory of
random arrays. The statistical average and distribution of the beampattern of
randomly generated phased arrays is derived in the framework of wireless ad hoc
sensor networks. Each sensor node is assumed to have a single isotropic antenna
and nodes in the cluster collaboratively transmit the signal such that the
signal in the target direction is coherently added in the far- eld region. It
is shown that with N sensor nodes uniformly distributed over a disk, the
directivity can approach N, provided that the nodes are located sparsely
enough. The distribution of the maximum sidelobe peak is also studied. With the
application to ad hoc networks in mind, two scenarios, closed-loop and
open-loop, are considered. Associated with these scenarios, the effects of
phase jitter and location estimation errors on the average beampattern are also
analyzed.Comment: To appear in the IEEE Transactions on Signal Processin
A review on frequency synchronization in collaborative beamforming: a practical approach
Coherent signal reception from distributed beamforming nodes of virtual antenna array formation requires frequency synchronization of the participating nodes. Signals at the target receiver are out of phase due to unsynchronized local oscillator’s (LO) reference signal of all the nodes in the systems. Practical cases of this problem are considered. In this article, a brief overview is presented of the need for the frequency synchronization and the resulting effect of mitigation avoidance. A variant of the closed-loop feedback algorithm is used to provide LO drifts information to the beamforming transmitters. These feedbacks are used to estimate, correct, and predict the nonlinear LO offsets that will result in near (0) phase offset of the received signal. The algorithms are implemented in software defined radio (SDR) and transmitted through the RF front end of devices like the NI 2920/N210 USRP
Theory and Applications of Aperiodic (Random) Phased Arrays
A need for network centric topologies using mobile wireless communications makes it important
to investigate new distributed beamforming techniques. Platforms such as micro air vehicles (MAVs),
unattended ground sensors (UGSs), and unpiloted aerial vehicles (UAVs) can all benefit from advances in this area utilizing advantages in stealth, enhanced survivability and maximum maneuverability. Moreover, in this dissertation, electromagnetic radiation is investigated such that the signal power of each element is coherently added in the far-field region of a specified target direction with net destructive interference occurring in all other regions to suppress sidelobe behavior. This provides superior range and resolution characteristics for a variety of applications including; early warning radar, ballistic missile defense and search and rescue efforts.
A wide variety of topologies can be used to confine geometrically these mobile random arrays for analysis. The distribution function for these topologies must be able to generalize the randomness within the geometry. By this means it is feasible to assume the random element distribution of a very large volumetric space will yield either a normal or Gaussian distribution. Therefore the underlying assumption stands that the statistically averaged beam pattern develops from an arrangement of uniformly or Gaussian distrusted elements; both confined to a variety of geometry of radius A and is further generalized using a simple theory based upon the Fourier Transform. Hence, this theory will be derived and serve as the foundation for advanced performance characteristics of these arrays such as its ability for sidelobe tapering, adaptive nulling and multi beam control. In addition it will be shown that for the most ideal of conditions a steerable beam pattern free of sidelobe behavior (better known as a Gaussian distribution) is quite possible. As well these random array structures will be shown to provide superior bandwidth capability over tradiational array structures since they are frequency independent. Last of all a summary of the random array analysis and its results concludes this dissertation
IEEE Access Special Section: Antenna and Propagation for 5G and Beyond
5G is not just the next evolution of 4G technology; it is a paradigm shift. “5G and beyond” will enable bandwidth in excess of 100s of Mb/s with a latency of less than 1 ms, in addition to providing connectivity to billions of devices. The verticals of 5G and beyond are not limited to smart transportation, industrial IoT, eHealth, smart cities, and entertainment services, transforming the way humanity lives, works, and engages with its environment
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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Beam alignment for millimeter wave vehicular communications
Millimeter wave (mmWave) has the potential to provide vehicles with high data rate communications that will enable a whole new range of applications. Its use, however, is not straightforward due to its challenging propagation characteristics. One approach to overcome the propagation challenge is the use of directional beams, but it requires a proper alignment and presents a challenging engineering problem, especially under the high vehicular mobility.
In this dissertation, fast and efficient beam alignment solutions suitable for vehicular applications are developed. To better quantify the problem, first the impact of directional beams on the temporal variation of the channels is investigated theoretically. The proposed model includes both the Doppler effect and the pointing error due to mobility. The channel coherence time is derived, and a new concept called the beam coherence time is proposed for capturing the overhead of mmWave beam alignment.
Next, an efficient learning-based beam alignment framework is proposed. The core of this framework is the beam pair selection methods that use side information (position in this case) and past beam measurements to identify promising beam directions and eliminate unnecessary beam training. Three offline learning methods for beam pair selection are proposed: two statistics-based and one machine learning-based methods. The two statistical learning methods consist of a heuristic and an optimal selection that minimizes the misalignment probability. The third one uses a learning-to-rank approach from the recommender system literature. The proposed approach shows an order of magnitude lower overhead than existing standard (IEEE 802.11ad) enabling it to support large arrays at high speed.
Finally, an online version of the optimal statistical learning method is developed. The solution is based on the upper confidence bound algorithm with a newly introduced risk-aware feature that helps avoid severe misalignment during the learning. Along with the online beam pair selection, an online beam pair refinement is also proposed for learning to adapt the codebook to the environment to further maximize the beamforming gain. The combined solution shows a fast learning behavior that can quickly achieve positive gain over the exhaustive search on the original (and unrefined) codebook. The results show that side information can help reduce mmWave link configuration overhead.Electrical and Computer Engineerin
Demonstration of passive acoustic detection and tracking of unmanned underwater vehicles
Submitted in partial fulfillment of the requirements for the degree of Master of Science at the
Massachusetts Institute of Technology
and the
Woods Hole Oceanographic Institution June 2018In terms of national security, the advancement of unmanned underwater vehicle
(UUV) technology has transformed UUVs from tools for intelligence, surveillance,
and reconnaissance and mine countermeasures to autonomous platforms that can
perform complex tasks like tracking submarines, jamming, and smart mining. Today,
they play a major role in asymmetric warfare, as UUVs have attributes that are
desirable for less-established navies. They are covert, easy to deploy, low-cost, and
low-risk to personnel. The concern of protecting against UUVs of malicious intent is
that existing defense systems fall short in detecting, tracking, and preventing the vehicles
from causing harm. Addressing this gap in technology, this thesis is the first to
demonstrate passively detecting and tracking UUVs in realistic environments strictly
from the vehicle’s self-generated noise. This work contributes the first power spectral
density estimate of an underway micro-UUV, field experiments in a pond and river
detecting a UUV with energy thresholding and spectral filters, and field experiments
in a pond and river tracking a UUV using conventional and adaptive beamforming.
The spectral filters resulted in a probability of detection of 96% and false alarms
of 18% at a distance of 100 m, with boat traffic in a river environment. Tracking
the vehicle with adaptive beamforming resulted in a 6.2±5.7 ∘ absolute difference in
bearing. The principal achievement of this work is to quantify how well a UUV can
be covertly tracked with knowledge of its spectral features. This work can be implemented
into existing passive acoustic surveillance systems and be applied to larger
classes of UUVs, which potentially have louder identifying acoustic signatures.Support from the National Defense
Science and Engineering Graduate Fellowship and Draper Labs Fellowship, as well as
DARPA for the support of the Bluefin Sandshark unmanned underwater vehicle.
This research was conducted with Government support under and awarded by DoD,
Air Force Office of Scientific Research, National Defense Science and Engineering Graduate
(NDSEG) Fellowship, 32 CFR 168a
Direct communication radio Iinterface for new radio multicasting and cooperative positioning
Cotutela: Universidad de defensa UNIVERSITA’ MEDITERRANEA DI REGGIO CALABRIARecently, the popularity of Millimeter Wave (mmWave) wireless networks has increased due to their capability to cope with the escalation of mobile data demands caused by the unprecedented proliferation of smart devices in the fifth-generation (5G). Extremely high frequency or mmWave band is a fundamental pillar in the provision of the expected gigabit data rates. Hence, according to both academic and industrial communities, mmWave technology, e.g., 5G New Radio (NR) and WiGig (60 GHz), is considered as one of the main components of 5G and beyond networks. Particularly, the 3rd Generation Partnership Project (3GPP) provides for the use of licensed mmWave sub-bands for the 5G mmWave cellular networks, whereas IEEE actively explores the unlicensed band at 60 GHz for the next-generation wireless local area networks. In this regard, mmWave has been envisaged as a new technology
layout for real-time heavy-traffic and wearable applications.
This very work is devoted to solving the problem of mmWave band communication system while enhancing its advantages through utilizing the direct communication radio interface for NR multicasting, cooperative positioning, and mission-critical applications. The main contributions presented in this work include: (i) a set of mathematical frameworks and simulation tools to characterize multicast traffic delivery in mmWave directional systems; (ii) sidelink
relaying concept exploitation to deal with the channel condition deterioration of dynamic multicast systems and to ensure mission-critical and ultra-reliable low-latency communications; (iii) cooperative positioning techniques analysis for enhancing cellular positioning accuracy for 5G+ emerging applications that require not only improved communication characteristics but also precise localization.
Our study indicates the need for additional mechanisms/research that can be utilized: (i) to further improve multicasting performance in 5G/6G systems; (ii) to investigate sideline aspects, including, but not limited to, standardization perspective and the next relay selection strategies; and (iii) to design cooperative positioning systems based on Device-to-Device (D2D) technology
Performance analysis and algorithm design for distributed transmit beamforming
Wireless sensor networks has been one of the major research topics in recent years because
of its great potential for a wide range of applications. In some application scenarios, sensor
nodes intend to report the sensing data to a far-field destination, which cannot be realized by
traditional transmission techniques. Due to the energy limitations and the hardware constraints
of sensor nodes, distributed transmit beamforming is considered as an attractive candidate for
long-range communications in such scenarios as it can reduce energy requirement of each sensor
node and extend the communication range. However, unlike conventional beamforming,
which is performed by a centralized antenna array, distributed beamforming is performed by
a virtual antenna array composed of randomly located sensor nodes, each of which has an
independent oscillator. Sensor nodes have to coordinate with each other and adjust their transmitting
signals to collaboratively act as a distributed beamformer. The most crucial problem of
realizing distributed beamforming is to achieve carrier phase alignment at the destination. This
thesis will investigate distributed beamforming from both theoretical and practical aspects.
First, the bit error ratio performance of distributed beamforming with phase errors is analyzed,
which is a key metric to measure the system performance in practice. We derive two distinct
expressions to approximate the error probability over Rayleigh fading channels corresponding
to small numbers of nodes and large numbers of nodes respectively. The accuracy of both
expressions is demonstrated by simulation results. The impact of phase errors on the system
performance is examined for various numbers of nodes and different levels of transmit power.
Second, a novel iterative algorithm is proposed to achieve carrier phase alignment at the destination
in static channels, which only requires one-bit feedback from the destination. This
algorithm is obtained by combining two novel schemes, both of which can greatly improve the
convergence speed of phase alignment. The advantages in the convergence speed are obtained
by exploiting the feedback information more efficiently compared to existing solutions.
Third, the proposed phase alignment algorithm is modified to track time-varying channels. The
modified algorithm has the ability to detect channel amplitude and phase changes that arise over
time due to motion of the sensors or the destination. The algorithm can adjust key parameters
adaptively according to the changes, which makes it more robust in practical implementation
A Review of Indoor Millimeter Wave Device-based Localization and Device-free Sensing Technologies and Applications
The commercial availability of low-cost millimeter wave (mmWave)
communication and radar devices is starting to improve the penetration of such
technologies in consumer markets, paving the way for large-scale and dense
deployments in fifth-generation (5G)-and-beyond as well as 6G networks. At the
same time, pervasive mmWave access will enable device localization and
device-free sensing with unprecedented accuracy, especially with respect to
sub-6 GHz commercial-grade devices. This paper surveys the state of the art in
device-based localization and device-free sensing using mmWave communication
and radar devices, with a focus on indoor deployments. We first overview key
concepts about mmWave signal propagation and system design. Then, we provide a
detailed account of approaches and algorithms for localization and sensing
enabled by mmWaves. We consider several dimensions in our analysis, including
the main objectives, techniques, and performance of each work, whether each
research reached some degree of implementation, and which hardware platforms
were used for this purpose. We conclude by discussing that better algorithms
for consumer-grade devices, data fusion methods for dense deployments, as well
as an educated application of machine learning methods are promising, relevant
and timely research directions.Comment: 43 pages, 13 figures. Accepted in IEEE Communications Surveys &
Tutorials (IEEE COMST