Physical layer-optimal and cross-layer channel access policies for hybrid overlay-underlay cognitive radio networks

The authors study the opportunistic spectrum access techniques for hybrid overlay-underlay cognitive radio networks. A secondary user (SU) chooses a channel, transmission mode and adjusts its power so that the interference limit is not crossed and its throughput is maximised. The authors assume that multiple primary user (PU) channels are available and the SU conducts spectrum sensing to access the channels. The objective is to maximise the throughput by switching between the overlay and underlay transmission modes. Using finite-horizon partially observable Markov decision process framework, the authors first study the optimal policies, where the PU is assumed to be in busy, concurrent or idle state, and the SU either stays idle or transmits with any of the two designed power levels. Although the PU's states are hidden, their activity statistics, transmission ranges and interference thresholds are assumed to be known. Via Monte Carlo simulation, the authors evaluate the performance of physical layer optimal policy (PLOP) and cross-layer policy (CLAP) and compare them with a fully observable optimal policy. The beliefs in each slot for both policies are updated using the forward algorithm based technique. Simulation results show that the proposed CLAP is more throughput efficient than the conventional PLOP.