Distributed power allocation in dense cognitive networks: Primary receiver detectable case

In this paper, a binary power allocation scheme is proposed for dense cognitive networks with plentiful secondary nodes. During the power allocation, the capacity loss of the primary system is controlled to be lower than a predefined level; and the capacity of the secondary system is ensured to some extent. Most importantly, based on the theoretical derivations, the power allocation is proved to be executable distributedly by local decisions at each secondary node, which is especially suitable for cognitive networks. By the simulation, the restriction on the distance between the secondary sender and the primary receiver is achieved straightforwardly, which reflects that the capacity of both primary system and secondary system can be ensured to the predefined level if the distance between secondary senders and the primary receiver satisfies certain conditions.