Stochastic Model Based Opportunistic Spectrum Access in Wireless Networks

We present a stochastic model based opportunistic channel access and transmission scheme for cognitive radioenabled secondary users for single data channel. We refer to this scheme as RIBS (Residual Idle Time Distribution based Scheme). In this scheme, the SU randomly senses the channel and if the channel is sensed idle, then it uses residual idle time distribution to estimate its transmission duration such that the probability of its interference with PU is below a predefined threshold. We derive analytical formulae for computing the average raw SU frames per transmission operation, average raw SU throughput, and the average sensing overhead for SU. Using simulation experiments, we show that using RIBS, SU can use the channel opportunistically without violating the interference probability constraint. We conduct simulation experiments by collecting channel occupancy data due to PU traffic in two different scenarios. In the first scenario, we synthetically generate channel occupancy data due to PU transmissions using two standard distributions (2-phase Erlang and Uniform distribution). We validate the analytical formulations using simulation with synthetic channel occupancy. In the second scenario, we simulate a TDMA-based PU network that runs realistic applications (VoIP and Web browsing). A pair of sender and receiver SU uses RIBS to opportunistically transmit on the channel. We analyze the characteristics of white spaces obtained due to these realistic applications, list some of the challenges in using RIBS in realistic scenarios, and provide comprehensive methodology to use RIBS in primary network running real applications.