A random multiple-access algorithm for the dependent feedback error channel

A noisy slotted channel is considered. It is assumed that channel feedback might be misinterpreted due to the existence of noise on the channel. Furthermore, this disturbance is dependent on the channel state (either good or bad) which varies from slot to slot according to a Markov chain. Consequently, the occurrence of a channel feedback error is dependent on previous occurrences of errors (i.e., with error memory). Under this assumption, the throughput performance of a random multiple-access algorithm (called a two-cell algorithm) is analyzed, and the result is compared with the throughput of the J. Capetanakis (1979) tree splitting algorithm operating over the same channel. It is shown that the two-cell algorithm retains positive throughputs for all possible values of channel state parameters, and for all practical purposes, it outperforms the Capetanakis algorithm in terms of insensitivity to channel feedback errors