This paper proposes efficient
backoff algorithms for uplink multi-packet reception (MPR) capable IEEE 802.11
systems in order to maximize the system throughput. According to the proposed
algorithms, each station (STN) estimates, in a Bayesian manner under an
unsaturated channel traffic condition, the number of backlogged STNs sharing
the multiple access channel to obtain an optimal (re)transmission probability.
Additionally, an access point and associated STNs cooperate by exchanging
information piggybacked in transmitted data packets and the corresponding
acknowledgment packets. The mean and variance of the queuing delays of the
proposed algorithms are extensively evaluated via simulations under various
environments such as time-varying populations and various asymmetric traffic
conditions and compared to those of the conventional binary exponential backoff
(BEB) algorithm. Furthermore, the queuing performance of the proposed
algorithms is compared to the queuing delay lower bound obtained from a system
that has perfect knowledge of the backlog size. Numerical results demonstrate
the robustness of the proposed algorithms in various environments, and that
they outperform the BEB algorithm.
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