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This dissertation research concerns a novel self-encoded spread spectrum. It provides a feasible practical implementation for random spreading codes. The traditional transmit and receive PN code generators are not needed. Instead, the spreading codes are extracted from the user's information bits itself. Comparing to conventional CDMA, SESS completely abandons the use of pseudo-random spreading codes. The code variability doesn't depend on the spreading length like pseudo-random codes.
But because the self-encoded spreading sequence is random and time varying, data recovery requires that the despreading sequence be identical with the spreading sequence at the start of the transmission. Synchronization is one of the key techniques in SESS which seeks to recover the initial spreading sequence at the receiver without any prior knowledge. It includes two phases: initial acquisition and tracking. We consider initial acquisition as a global optimization problem and employ genetic search algorithm for converging to the global optimization efficiently. In the tracking phase, we use Markov chain analysis to examine the mean tracking time. We can verify them by simulation results as sequence length N=8. By comparing the analytical and simulation results, we can conclude that the Genetic model and Markov chain analysis can describe the process of the synchronization of SESS system reliably. We extended such synchronization model of SESS to longer sequence length as N=64 and achieved the shortest synchronization time by setting an optimum threshold. Optimal parameters are also considered to improve the synchronization time.
We also consider incorporating SESS with cooperative diversity technique to achieve spatial diversity gain with the number of relays. We observe the system’s stability in highly correlated rayleigh channels as well as in severe fading channels. Meanwhile, we also consider channel coding for time diversity gain (together with the soft decision Viterbi detection in receiver). Notice that we achieve both time diversity and special diversity while maintaining the same average power as the maximum ratio combiner.
Adviser: Lim Nguyen