This book is the outcome of the panel discussions held on the special event honor-
ing first 50 PhD students of Prof. Ramjee Prasad. Several of his PhD students are
today worldwide telecommunication leaders themselves. Over 60 post-docs, PhDs,
colleagues and the scientific staff were present at the event to celebrate the research
and development achievements in the field of mobile and wireless communication.
In this paper we revisit hybrid analog-digital precoding systems with emphasis on their modelling
and radio-frequency (RF) losses, to realistically evaluate their benefits in 5G system implementations.
For this, we decompose the analog beamforming networks (ABFN) as a bank of commonly used RF
components and formulate realistic model constraints based on their S-parameters. Specifically, we
concentrate on fully-connected ABFN (FC-ABFN) and Butler networks for implementing the discrete
Fourier transform (DFT) in the RF domain. The results presented in this paper reveal that the performance
and energy efficiency of hybrid precoding systems are severely affected, once practical factors are
considered in the overall design. In this context, we also show that Butler RF networks are capable of
providing better performances than FC-ABFN for systems with a large number of RF chains.
Modeling and simulation of nonlinear systems provide communication system designers
with a tool to predict and verify overall system performance under nonlinearity and
complex communication signals. Traditionally, RF system designers use deterministic
signals (discrete tones), which can be implemented in circuit simulators, to predict the
performance of their nonlinear circuits/systems. However, RF system designers are usually
faced with the problem of predicting system performance when the input to the system
is real-world communication signals which have a random nature.
Before delving into the details of orthogonal frequency division multiplexing (OFDM), relevant
background material must be presented first. The purpose of this chapter is to provide the necessary
building blocks for the development of OFDM principles. Included in this chapter are reviews of stochastic
and random process, discrete-time signals and systems, and the Discrete Fourier Transform (DFT). Tooled
with the necessary mathematical foundation, we proceed with an overview of digital communication
systems and OFDM communication systems. We conclude the chapter with summaries of the OFDM
wireless LAN standards currently in existence and a high-level comparison of single carrier systems versus
OFDM.
Many good textbooks exist on probability and random processes written at the under-
graduate level to the research level. However, there is no one handy and ready book
that explains most of the essential topics, such as random variables and most of their
frequently used discrete and continuous probability distribution functions; moments,
transformation, and convergences of random variables; characteristic and generating
functions; estimation theory and the associated orthogonality principle; vector random
variables; random processes and their autocovariance and cross-covariance functions; sta-
tionarity concepts; and random processes through linear systems and the associated
Wiener and Kalman filters.
Electrostatic discharge (ESD) is one of the most prevalent threats to the reliability
of electronic components. It is an event in which a finite amount of charge is trans-
ferred from one object (i.e., human body) to another (i.e., microchip). This process
can result in a very high current passing through the microchip within a very short
period of time, and, hence, more than 35% of chip damages can be attributed to an
ESD-related event. As such, designing on-chip ESD structures to protect integrated
circuits against the ESD stresses is a high priority in the semiconductor industry.
Since OpenStreetMap (OSM) appeared more than ten years ago, new
collaborative mapping approaches have emerged in different areas and have become
important components of localised information and services based on localisation.
There is now increased awareness of the importance of the space-time attributes of
almost every event and phenomenon. Citizens now have endless possibilities to
quickly geographically locate themselves with an accuracy previously thought
impossible. Based on these societal drivers, we proposed a number of collaborative
mapping experiments (“mapping parties”) to delegates of a large open-source
geospatial conference and to citizens of the conference’s host city during July 2015.
There exist two essentially different approaches to the study of dynamical systems, based on
the following distinction:
time-continuous nonlinear differential equations ? time-discrete maps
One approach starts from time-continuous differential equations and leads to time-discrete
maps, which are obtained from them by a suitable discretization of time. This path is
pursued, e.g., in the book by Strogatz [Str94]. 1 The other approach starts from the study of
time-discrete maps and then gradually builds up to time-continuous differential equations,
see, e.g., [Ott93, All97, Dev89, Has03, Rob95]. After a short motivation in terms of nonlinear
differential equations, for the rest of this course we shall follow the latter route to dynamical
systems theory. This allows a generally more simple way of introducing the important
concepts, which can usually be carried over to a more complex and physically realistic
context.
