863 research outputs found
6G White Paper on Machine Learning in Wireless Communication Networks
The focus of this white paper is on machine learning (ML) in wireless
communications. 6G wireless communication networks will be the backbone of the
digital transformation of societies by providing ubiquitous, reliable, and
near-instant wireless connectivity for humans and machines. Recent advances in
ML research has led enable a wide range of novel technologies such as
self-driving vehicles and voice assistants. Such innovation is possible as a
result of the availability of advanced ML models, large datasets, and high
computational power. On the other hand, the ever-increasing demand for
connectivity will require a lot of innovation in 6G wireless networks, and ML
tools will play a major role in solving problems in the wireless domain. In
this paper, we provide an overview of the vision of how ML will impact the
wireless communication systems. We first give an overview of the ML methods
that have the highest potential to be used in wireless networks. Then, we
discuss the problems that can be solved by using ML in various layers of the
network such as the physical layer, medium access layer, and application layer.
Zero-touch optimization of wireless networks using ML is another interesting
aspect that is discussed in this paper. Finally, at the end of each section,
important research questions that the section aims to answer are presented
Low-Complexity Sub-band Digital Predistortion for Spurious Emission Suppression in Noncontiguous Spectrum Access
Noncontiguous transmission schemes combined with high power-efficiency
requirements pose big challenges for radio transmitter and power amplifier (PA)
design and implementation. Due to the nonlinear nature of the PA, severe
unwanted emissions can occur, which can potentially interfere with neighboring
channel signals or even desensitize the own receiver in frequency division
duplexing (FDD) transceivers. In this article, to suppress such unwanted
emissions, a low-complexity sub-band DPD solution, specifically tailored for
spectrally noncontiguous transmission schemes in low-cost devices, is proposed.
The proposed technique aims at mitigating only the selected spurious
intermodulation distortion components at the PA output, hence allowing for
substantially reduced processing complexity compared to classical linearization
solutions. Furthermore, novel decorrelation based parameter learning solutions
are also proposed and formulated, which offer reduced computing complexity in
parameter estimation as well as the ability to track time-varying features
adaptively. Comprehensive simulation and RF measurement results are provided,
using a commercial LTE-Advanced mobile PA, to evaluate and validate the
effectiveness of the proposed solution in real world scenarios. The obtained
results demonstrate that highly efficient spurious component suppression can be
obtained using the proposed solutions
Tunable n-path notch filters for blocker suppression: modeling and verification
N-path switched-RC circuits can realize filters with very high linearity and compression point while they are tunable by a clock frequency. In this paper, both differential and single-ended N-path notch filters are modeled and analyzed. Closed-form equations provide design equations for the main filtering characteristics and nonidealities such as: harmonic mixing, switch resistance, mismatch and phase imbalance, clock rise and fall times, noise, and insertion loss. Both an eight-path single-ended and differential notch filter are implemented in 65-nm CMOS technology. The notch center frequency, which is determined by the switching frequency, is tunable from 0.1 to 1.2 GHz. In a 50- environment, the N-path filters provide power matching in the passband with an insertion loss of 1.4–2.8 dB. The rejection at the notch frequency is 21–24 dB,P1 db> + 2 dBm, and IIP3 > + 17 dBm
Survey of Spectrum Sharing for Inter-Technology Coexistence
Increasing capacity demands in emerging wireless technologies are expected to
be met by network densification and spectrum bands open to multiple
technologies. These will, in turn, increase the level of interference and also
result in more complex inter-technology interactions, which will need to be
managed through spectrum sharing mechanisms. Consequently, novel spectrum
sharing mechanisms should be designed to allow spectrum access for multiple
technologies, while efficiently utilizing the spectrum resources overall.
Importantly, it is not trivial to design such efficient mechanisms, not only
due to technical aspects, but also due to regulatory and business model
constraints. In this survey we address spectrum sharing mechanisms for wireless
inter-technology coexistence by means of a technology circle that incorporates
in a unified, system-level view the technical and non-technical aspects. We
thus systematically explore the spectrum sharing design space consisting of
parameters at different layers. Using this framework, we present a literature
review on inter-technology coexistence with a focus on wireless technologies
with equal spectrum access rights, i.e. (i) primary/primary, (ii)
secondary/secondary, and (iii) technologies operating in a spectrum commons.
Moreover, we reflect on our literature review to identify possible spectrum
sharing design solutions and performance evaluation approaches useful for
future coexistence cases. Finally, we discuss spectrum sharing design
challenges and suggest future research directions
Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks
Soaring capacity and coverage demands dictate that future cellular networks
need to soon migrate towards ultra-dense networks. However, network
densification comes with a host of challenges that include compromised energy
efficiency, complex interference management, cumbersome mobility management,
burdensome signaling overheads and higher backhaul costs. Interestingly, most
of the problems, that beleaguer network densification, stem from legacy
networks' one common feature i.e., tight coupling between the control and data
planes regardless of their degree of heterogeneity and cell density.
Consequently, in wake of 5G, control and data planes separation architecture
(SARC) has recently been conceived as a promising paradigm that has potential
to address most of aforementioned challenges. In this article, we review
various proposals that have been presented in literature so far to enable SARC.
More specifically, we analyze how and to what degree various SARC proposals
address the four main challenges in network densification namely: energy
efficiency, system level capacity maximization, interference management and
mobility management. We then focus on two salient features of future cellular
networks that have not yet been adapted in legacy networks at wide scale and
thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and
device-to-device (D2D) communications. After providing necessary background on
CoMP and D2D, we analyze how SARC can particularly act as a major enabler for
CoMP and D2D in context of 5G. This article thus serves as both a tutorial as
well as an up to date survey on SARC, CoMP and D2D. Most importantly, the
article provides an extensive outlook of challenges and opportunities that lie
at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201
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