In spread spectrum systems employing parity bit selected spreading sequences, parity
bits generated from a linear block encoder are used to select a spreading code from
a set of mutually orthogonal spreading sequences. In this thesis, turbo receivers for
SS-PB systems are proposed and investigated. In the transmitter, data bits are rst
convolutionally encoded before being fed into SS-PB modulator. In fact, the parity
bit spreading code selection technique acts as an inner encoder in this system without
allocating any transmit energy to the additional redundancy provided by this technique.
The receiver implements a turbo processing by iteratively exchanging the soft information
on coded bits between a SISO detector and a SISO decoder. In this system,
detection is performed by incorporating the extrinsic information provided by the decoder
in the last iteration into the received signal to calculate the likelihood of each
detected bit in terms of LLR which is used as the input for a SISO decoder.
In addition, SISO detectors are proposed for MC-CDMA and MIMO-CDMA systems
that employ parity bit selected and permutation spreading. In the case of multiuser
scenario, a turbo SISO multiuser detector is introduced for SS-PB systems for both
synchronous and asynchronous channels. In such systems, MAI is estimated from the
extrinsic information provided by the SISO channel decoder in the previous iteration.
SISO multiuser detectors are also proposed for the case of multiple users in MC-CDMA
and MIMO-CDMA systems when parity bit selected and permutation spreading are used.
Simulations performed for all the proposed turbo receivers show a signi cant reduction
in BER in AWGN and fading channels over multiple iterations.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:OOU.#10393/20635 |
| Date | 25 January 2012 |
| Creators | Mirzaee, Alireza |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
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