Multicast in Multihop CRNs Under Uncertain Spectrum Availability: A Network Coding Approach

The benefits of network coding on multicast in traditional multihop wireless networks have already been extensively demonstrated in previous works. However, most existing approaches cannot be directly applied to multihop cognitive radio networks (CRNs), given the unpredictable primary user occupancy on licensed channels. Specifically, due to the unpredictable occupancy, the channel's available bandwidth is time-varying and uncertain. Accordingly, the capacity of the link using that channel is also uncertain, which can significantly affect the network coding subgraph optimization and may result in severe throughput loss if not properly handled. In this paper, we study the problem of network coding-based multicast in multihop CRNs while considering the uncertain spectrum availability. To capture the uncertainty of spectrum availability, we first formulate our problem as a chance-constrained program. Given the computational intractability of the above-mentioned program, we then transform the original problem into a tractable convex optimization problem, through appropriate Bernstein approximation with relaxation on link scheduling. We further leverage Lagrangian relaxation-based optimization techniques to propose an efficient distributed algorithm for the original problem. Extensive simulation results show that the proposed algorithm achieves higher multicast rates, compared with a state-of-the-art non-network coding algorithm in multihop CRNs, and a conservative robust network coding algorithm that treats the link capacity as a constant value in the optimization.