Abstract
Self-encoded spread spectrum eliminates the need for traditional pseudo noise (PN) code generators. In a self-encoded multiple access (SEMA) system, the number of users is not limited by the number of available sequences, unlike code division multiple access (CDMA) systems that employ PN codes such as m-, Gold or Kassami sequences. SEMA provides a convenient way of supporting multi-rate, multi-level grades of service in multimedia communications and prioritized heterogeneous networking systems. In this paper, we propose multiuser convolutional channel coding in SEMA that provides fewer cross-correlations among users and thereby reducing multiple access interference (MAI). We analyze SEMA multiuser convolutional coding in additive white Gaussian noise (AWGN) channels as well as fading channels. Our analysis includes downlink synchronous system as well as asynchronous system such as uplink mobile-to-base station communication.
Highlights
In code division multiple access (CDMA) communications, each user is assigned a unique pseudo noise (PN) spreading sequence that has a low cross-correlation with other users' sequences
We developed multiuser convolutional coding directly applicable to self-encoded multiple access (SEMA) in synchronous downlink as well as asynchronous uplink cellular systems
We show that SEMA multiuser convolutional coding can improve performance over conventional convolutional coding
Summary
In CDMA communications, each user is assigned a unique PN spreading sequence that has a low cross-correlation with other users' sequences. This prevents code collisions between the users and controls MAI. PN code generators are typically linear feedback shift register circuits that generate maximal-length or related sequences. These deterministic sequences provide low cross-correlations that are critical for achieving good system performance. Notice that the contents of the delay registers in the transmitter and receiver should be identical at the start of the transmission This is accomplished as part of the initial synchronization procedure. We present the performance analysis and simulation both in uplink asynchronous and downlink synchronous channels
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