ETD

Archivio digitale delle tesi discusse presso l'Università di Pisa

Tesi etd-03252013-100514


Tipo di tesi
Tesi di laurea magistrale
Autore
DELLA SANTA, NICOLA
URN
etd-03252013-100514
Titolo
Link Resource Adaptation for Cognitive BIC-OFDM Systems with Outdated Channel State Information
Dipartimento
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
INGEGNERIA DELLE TELECOMUNICAZIONI
Relatori
relatore Ing. Lottici, Vincenzo
relatore Ing. Andreotti, Riccardo
relatore Prof. Giannetti, Filippo
Parole chiave
  • LRA
  • BIC
  • OFDM Systems
  • MIMO
  • cognitive
  • Imperfect CSI
  • Outdated
Data inizio appello
22/04/2013
Consultabilità
Non consultabile
Data di rilascio
22/04/2053
Riassunto
In a world where mobility is ever increasing, people needs to communicate
with each other having timely access to information regardless of
the location of the individuals or the information to be exchanged. In
this scenario, the demand for advanced wireless communication systems
has prompted both the search for a better understanding of fundamental
limits in communication theory and their implications for the design
of high-efficient wireless systems. Hence, high data transmission rates,
wide area coverage, high quality of service (QoS) and efficient use of
transmission resources come out as the main design challenges to be met
by wireless communication engineers.
Recently, technological advances based on multiple antenna systems
(MIMO), multicarrier transmissions (OFDM) and advanced
error-correcting code schemes such as bit interleaved coded (BIC) modulation,
demonstrated the possibility to increase system performance and
to obtain the desirable QoS for the fourth generation of wireless system
and beyond. Another promising concept which gained considerable interest
in the wireless communication arena is Cognitive Radio. This allows
the shared use of the same spectrum bands between licensed (primary)
and unlicensed (secondary) users on a non-interference basis.
Due to the mobility of the users, however, radio propagation conditions
may change during the transmission, so that different packets
experience different channel conditions. Unfortunately, this inexorably
plagues the radio resource management, which would need a reliable (and
stable) knowledge of Channel State Information (CSI). As a matter of
fact, the transmitter has only an Imperfect and/or Outdated CSI, which
hinders resource allocation and make the system performance more and
more degraded.
The goal of this thesis is to tackle this issue, by designing a novel
algorithm for the prediction of radio channel variations in a cognitive
packed-based BIC-OFDM transmission system. The key idea is based
on the Effective SNR Mapping (ESM) concept, which maps the instantaneous
per-subcarrier SNRs into a single value, the effectiveSNR, which
is used at transmitter side to choose the optimal radio resource allocation.
The proposed performance prediction algorithm has been then
applied as the core of a novel link resource allocation (LRA) strategy for
a BIC-OFDM and Cognitive BIC-OFDM systems. Extensive numerical
results demonstrated the effectiveness of the proposed algorithms when
subject to radio channel variations. Finally, the LRA algorithm has also
been applied to a MIMO-SVD BIC-OFDM scheme, in order to obtain a
preliminary valuation of its effectiveness.
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