A Resource Allocation Algorithm for Real-Time Streaming in Cognitive Networks

Cognitive radios have been proposed as a means to implement efficient reuse of the licensed spectrum. Commonly, wireless networks are characterized by a fixed spectrum assignment policy. The limited available spectrum and the inefficiency in the spectrum usage necessitate a new communication paradigm to exploit the existing wireless spectrum opportunistically. We consider a simple single-cell scenario with two data up-links, one licensed to use the spectral resource (primary) and the other unlicensed (secondary or cognitive). It is assumed that the cognitive user accesses the channel only when the channel is sensed idle. An ON-OFF channel model is used for the primary link, where traffic statistical characteristics are taken into account. We study a practical resource allocation algorithm that assigns the uplink to the secondary users according to a channel-and-queues aware scheduler when primary link OFF periods are sensed. We fit the resource allocation algorithm to the widely investigated orthogonal frequency division multiple access (OFDMA) scheme and we exploit multiuser diversity by applying a smart power allocation within independent OFDMA subchannels. A video encoder rate control is introduced in order to limit the video frame loss due to overflow that trades the video frame loss probability with the overall encoding quality. Lastly, the performance of the cognitive network model is investigated under the proposed resource allocation algorithm.