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A new technique for best effort delivery of broadcast bursty multi-slot messages is investigated, using random access with capture. It is shown that a combination of packet level coding and random spreading of a message's packets can improve message reception probability, satisfaction of delay constraints, and throughput in many cases. Furthermore, we show how the specific transmission strategy employed should depend on the message length, total offered traffic, and the specific delay constraints. In addition, we show how edge effects, the finite size of the network, and receiver capture significantly impact performance not only at the edges of the network, but also near the center of the network. Finally, we demonstrate how to leverage these edge effects so that the introduction of minimal feedback from only one or two nodes can substantially improve the probability of message reception for all nodes in the network.

Optimal resource allocations for best effort delivery of broadcasting bursty multi-slots messages with random access are investigated. We consider broadcast multi-slot messages originating from all nodes in wireless random access networks of varying sizes, with receivers employing capture. Allocation of both access probabilities and transmission energy needed for sending various amounts of coded packets are investigated. The distributed transmitters must cooperate by Duly using the resources They are allocated, so as not to cause additional collisions that would diminish the performance of the other users. We evaluate resource allocation schemes in terms of message loss probability, throughput, and probability of satisfaction of specific delay constraints. It is demonstrated that optimal strategies for these metrics depend on the total offered traffic, the number of nodes, and the capture effect. It is shown how the optimal throughput can be implemented with finite delay. Furthermore, we show how even in large networks with the optimal allocation strategy, edge effects and capture significantly impact performance not only at the edges of the network, but also in the center of the network. Finally, we demonstrate how the addition of minimal feedback and further cooperation to the optimal best effort delivery strategy can significantly increase the probability of 'reception for all nodes.