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Based on the concept of sparse Bayesian learning, an expectation and maximization algorithm is proposed for cooperative spectrum sensing and locationing of the primary transmitters in cognitive radio systems. Different from typical approaches, not only the signal strength, but also the number and the radio power profiles of the primary transmitters are estimated, which greatly facilitates resource...
Traditional multicast technology faces a serious state scalability problem when there are large numbers of concurrent groups in the network. As a new approach to solve this scalability problem, aggregated multicast forces multiple multicast groups to share a common distribution tree. This can be defined as a minimum grouping problem and is proved to be an NPC problem. An ant colony optimization algorithm...
In this paper, we address the problem of adaptive radio resource allocation and QoS provisioning for real-time (RT) and non-real-time (NRT) services in OFDMA systems. The proposed algorithm tightly couples the subchannel allocation and packet scheduling together through an integrated cross-layer approach in which each packet is assigned a priority value by taking both the instantaneous channel condition...
Many applications in the network have strict demands for QoS, such as bandwidth, delay, packet loss rate, etc. Finding the best routing to satisfy those requirements is, in general, an NP-hard problem. Many heuristic algorithms are used to solve this problem, which, however, either belonging to local search or centralized algorithms, cannot guarantee the finding of best solutions in real networks...
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