Cross-Layer Scheduling Design for Multimedia Applications over Cognitive Ad Hoc Networks

In this paper,we study cross-layer scheduling scheme on multimedia application which considers both streaming traffic and data traffic over cognitive ad hoc networks.A cross-layer design is proposed to optimize SU's utility,which is used as an approach to balance the transmission efficiency and heterogeneous traffic in cognitive ad hoc networks.A framework is provided for utility-based optimal subcarrier assignment,power allocation strategy and corresponding modulation scheme,subject to the interference threshold to primary user(PU) and total transmit power constraint.Bayesian learning is adopted in subcarrier allocation strategy to avoid collision and alleviate the burden of information exchange on limited common control channel(CCC).In addition,the M/G/l queuing model is also introduced to analyze the expected delay of streaming traffic.Numerical results are given to demonstrate that the proposed scheme significantly reduces the blocking probability and outperforms the mentioned single-channel dynamic resource scheduling by almost 8%in term of system utility.

acSB:Anti-Collision Selective-Based Broadcast Protocol in CRAdHocs

As a fundamental operation in ad hoc networks,broadcast could achieve efficient message propagations.Particularl y in the cognitive radio ad hoc network where unlicensed users have different sets of available channels,broadcasts are carried out on multiple channels.Accordingly,channel selection and collision avoidance are challenging issues to balance the efficiency against the reliability of broadcasting.In this paper,an anticollision selective broadcast protocol,called acSB,is proposed.A channel selection algorithm based on limited neighbor information is considered to maximize success rates of transmissions once the sender and receiver have the same channel.Moreover,an anticollision scheme is adopted to avoid simultaneous rebroadcasts.Consequently,the proposed broadcast acSB outperforms other approaches in terms of smaller transmission delay,higher message reach rate and fewer broadcast collisions evaluated by simulations under different scenarios.

A Distributed Power Allocation Scheme in Green Cognitive Radio Ad Hoc Networks

For the realization of green communications in cognitive radio ad hoc networks(CRAHNs), selfadaptive and efficient power allocation for secondary users(SUs) is essential. With the distributed and timevarying network topology, it needs to consider how to optimize the throughput and power consuming, avoid the interference to primary users(PUs) and other SUs, and pay attention to the convergence and fairness of the algorithm. In this study, this problem is modeled as a constraint optimization problem. Each SU would adjust its power and corresponding strategy with the goal of maximizing its throughput. By studying the interactions between SUs in power allocation and strategy selection, we introduce best-response dynamics game theory and prove the existence of Nash equilibrium(NE) point for performance analysis. We further design a fully distributed algorithm to make the SUs formulate their strategy based on their utility functions, the strategy and number of neighbors in local area. Compared with the water-filling(WF) algorithm, the proposed scheme can significantly increase convergent speed and average throughput, and decrease the power consuming of SUs.