Cross-Layer Design for Congestion, Contention, and Power Control in CRAHNs under Packet Collision Constraints

In this paper, we investigate the cross-layer design for congestion, contention, and power control in multi-hop cognitive radio ad-hoc networks (CRAHNs). In particular, we develop a unified optimization framework achieving flexible tradeoff between energy efficiency and network utility maximization where we design two novel cross-layer cognitive algorithms comprising efficient powered-controlled MAC protocols for CRAHNs based on the concepts of social welfare and net revenue in economics. The proposed framework can balance interference, collision, and congestion among cognitive users (CUs) including cognitive sources and cognitive links while utilizing stochastic spectrum holes vacated by licensed users (LUs). The former allows both cognitive sources and cognitive links to simultaneously adjust their transmission parameters (i.e., transmit power, persistence probability, and rate) following the law of diminishing returns whereas the latter forces cognitive links to control the persistence probability and transmit power in order to asymptotically balance the offered load regulated by cognitive sources. Our proposed protocols are then validated and their performance is compared with the existing MAC schemes in the literature via numerical studies.