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Performance improvements in self-encoded spread spectrum
Traditional spread spectrum uses deterministic pseudo-random sequences for signal spreading and de-spreading. Self-encoded spread spectrum (SESS) is a novel communication technique that derives its spreading code from the randomness of the source stream rather than using conventional pseudorandom noise (PN) code. Although SESS have been explored for the past ten years, a thorough analysis of various aspects of SESS system and its applications in both communications and navigation need to be studied.^ In this dissertation, we explored some new features of SESS in both communication and navigation systems. An extension of SESS namely coded-sequence self-encoded spread spectrum (CS-SESS) has been proposed and shown that it could further improve the system bit-error rate (BER) performance significantly without any bandwidth increase. We investigated the performance of CS-SESS with chip interleaving and applied the transmitter precoding to combat the channel dynamics of CS-SESS communication. We proposed a novel CS-SESS with increased modulation memory depth to further improve the BER performance and provided the detail study of this system and incorporated techniques like multiple-input multiple-output (MIMO) and Viterbi decoding to extract the temporal diversity gain. We also investigated the performance of both SESS and CS-SESS under pulsed noise jamming environment and showed that iterative detection not only can eliminate the jamming completely but also can provide additional temporal diversity gain. Finally, to further facilitate the use of SESS in navigation system, we incorporated SESS with phase shift keying (PSK) and binary offset carrier (BOC) signals to mitigate the multipath tracking error in global navigation satellite systems (GNSS) receivers by introducing code shuffling to enhance the accuracy of iterative detection in multipath scenario.^
Engineering, Computer|Engineering, General|Engineering, Electronics and Electrical
Duraisamy, Poomathi, "Performance improvements in self-encoded spread spectrum" (2012). ETD collection for University of Nebraska - Lincoln. AAI3546659.