Fundamentals of Time-Varying Communication Channels

Matz, Gerald; Hlawatsch, Franz

doi:10.1016/b978-0-12-374483-8.00001-7

Cited by 62 publications

(31 citation statements)

References 55 publications

(87 reference statements)

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“…Although inferior in accuracy to stationary channel models, where the channel varies continuously (see e.g., [16]), its simplicity enables analytical approaches that are currently out of reach for more sophisticated models.…”

Section: Fading Channelsmentioning

confidence: 99%

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Toward Massive, Ultrareliable, and Low-Latency Wireless Communication With Short Packets

2016

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Abstract-Most of the recent advances in the design of highspeed wireless systems are based on information-theoretic principles that demonstrate how to efficiently transmit long data packets. However, the upcoming wireless systems, notably the 5G system, will need to support novel traffic types that use short packets. For example, short packets represent the most common form of traffic generated by sensors and other devices involved in Machine-toMachine (M2M) communications. Furthermore, there are emerging applications in which small packets are expected to carry critical information that should be received with low latency and ultrahigh reliability.Current wireless systems are not designed to support shortpacket transmissions. For example, the design of current systems relies on the assumption that the metadata (control information) is of negligible size compared to the actual information payload. Hence, transmitting metadata using heuristic methods does not affect the overall system performance. However, when the packets are short, metadata may be of the same size as the payload, and the conventional methods to transmit it may be highly suboptimal.In this article, we review recent advances in information theory, which provide the theoretical principles that govern the transmission of short packets. We then apply these principles to three exemplary scenarios (the two-way channel, the downlink broadcast channel, and the uplink random access channel), thereby illustrating how the transmission of control information can be optimized when the packets are short. The insights brought by these examples suggest that new principles are needed for the design of wireless protocols supporting short packets. These principles will have a direct impact on the system design.

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Section: Fading Channelsmentioning

confidence: 99%

“…The expressions (16) and (17) describe elegantly and succinctly the tradeoff between diversity gain and multiplexing gain at high SNR.…”

Section: Fading Channelsmentioning

confidence: 99%

Toward Massive, Ultrareliable, and Low-Latency Wireless Communication With Short Packets

2016

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“…If additionally it can be assumed that the channel variations are wide-sense stationary, which is usually a reasonable assumption over the typical timescales of interest for communication for both time-varying wireless communication channels [112] and underwater acoustic communication channels [172], then the received signal is cyclostationary, as shown below. Proof.…”

Section: Multichannel Adaptive Frequency-domain Equalizationmentioning

confidence: 99%

Graphical model driven methods in adaptive system identification

Yellepeddi¹

2016

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Identifying and tracking an unknown linear system from observations of its inputs and outputs is a problem at the heart of many different applications. Due to the complexity and rapid variability of modern systems, there is extensive interest in solving the problem with as little data and computation as possible.This thesis introduces the novel approach of reducing problem dimension by exploiting statistical structure on the input. By modeling the input to the system of interest as a graph-structured random process, it is shown that a large parameter identification problem can be reduced into several smaller pieces, making the overall problem considerably simpler.Algorithms that can leverage this property in order to either improve the performance or reduce the computational complexity of the estimation problem are developed. The first of these, termed the graphical expectation-maximization least squares (GEM-LS) algorithm, can utilize the reduced dimensional problems induced by the structure to improve the accuracy of the system identification problem in the low sample regime over conventional methods for linear learning with limited data, including regularized least squares methods.Next, a relaxation of the GEM-LS algorithm termed the relaxed approximate graph structured least squares (RAGS-LS) algorithm is obtained that exploits structure to perform highly efficient estimation. The RAGS-LS algorithm is then recast into a recursive framework termed the relaxed approximate graph structured recursive least squares (RAGS-RLS) algorithm, which can be used to track time-varying linear systems with low complexity while achieving tracking performance comparable to much more computationally intensive methods.The performance of the algorithms developed in the thesis in applications such as channel identification, echo cancellation and adaptive equalization demonstrate that the gains admitted by the graph framework are realizable in practice. The methods have wide applicability, and in particular show promise as the estimation and adaptation algorithms for a new breed of fast, accurate underwater acoustic modems.The contributions of the thesis illustrate the power of graphical model structure in simplifying difficult learning problems, even when the target system is not directly structured.Thesis Supervisor: James C. Preisig Title: Scientist Emeritus, Woods Hole Oceanographic Institution AcknowledgmentsPiglet noticed that even though he had a Very Small Heart, it could hold a rather large amount of Gratitude. Winnie the PoohA.A.MilneMy years at MIT have been about so much more than a degree. In the past six years you have introduced to more worlds than I ever knew existed. As this long and wonderful journey ends, I find that my heart can, too, hold so much gratitude, for everything that you have given.Of course, I haven't said who "you" is, so here goes.It is impossible to write any list of acknowledgements without having at the very top my thesis advisor Dr. James Preisig, who has truly been a wide-angle lens f...

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“…where C H (τ, ν) is the two-dimensional PSD of the channel process, usually referred to as scattering function [17]. In the remainder of the paper, we let the scattering function be normalized in volume according to…”

Section: System Model a Channel And Signal Modelmentioning

confidence: 99%

“…For a more complete description of the WSSUS channel model, the interested reader is referred to [17], [1].…”

Section: System Model a Channel And Signal Modelmentioning

confidence: 99%

On the Sensitivity of Continuous-Time Noncoherent Fading Channel Capacity

Durisi

Bölcskei

2012

IEEE Trans. Inform. Theory

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Abstract-The noncoherent capacity of stationary discrete-time fading channels is known to be very sensitive to the fine details of the channel model. More specifically, the measure of the support of the fading-process power spectral density (PSD) determines if noncoherent capacity grows logarithmically in SNR or slower than logarithmically. Such a result is unsatisfactory from an engineering point of view, as the support of the PSD cannot be determined through measurements. The aim of this paper is to assess whether, for general continuous-time Rayleigh-fading channels, this sensitivity has a noticeable impact on capacity at SNR values of practical interest.To this end, we consider the general class of band-limited continuous-time Rayleigh-fading channels that satisfy the widesense stationary uncorrelated-scattering (WSSUS) assumption and are, in addition, underspread. We show that, for all SNR values of practical interest, the noncoherent capacity of every channel in this class is close to the capacity of an AWGN channel with the same SNR and bandwidth, independently of the measure of the support of the scattering function (the two-dimensional channel PSD). Our result is based on a lower bound on noncoherent capacity, which is built on a discretization of the channel input-output relation induced by projecting onto Weyl-Heisenberg (WH) sets. This approach is interesting in its own right as it yields a mathematically tractable way of dealing with the mutual information between certain continuous-time random signals.

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Fundamentals of Time-Varying Communication Channels

Cited by 62 publications

References 55 publications

Toward Massive, Ultrareliable, and Low-Latency Wireless Communication With Short Packets

Toward Massive, Ultrareliable, and Low-Latency Wireless Communication With Short Packets

Graphical model driven methods in adaptive system identification

On the Sensitivity of Continuous-Time Noncoherent Fading Channel Capacity

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