认知Ad-hoc网络中的快速邻居发现

在认知Ad-hoc网络中,邻居发现是MAC协议、拓扑管理、路由协议运行的前提,对网络性能有重要影响。针对认知Ad-hoc网络中节点的可用信道集异构和缺乏全网公共控制信道的特点,提出了基于可用频谱相似性的快速邻居发现算法。与现有同步邻居算法要求节点在全网可用信道集上切换以进行邻居发现的机制不同,所提算法要求节点在各自的可用信道集上切换,以一定的概率λ发送包含节点信息的分组。由于认知Ad-hoc网络全网可用信道集一般很大,而对于每个节点来说可能仅有几个可用信道,因此所提算法大大减小了邻居发现的时间开销。仿真分析表明,与现有算法相比,所提算法的时间开销至少降低了47%。

Fast Neighbor Discovery in Cognitive Radio Ad-hoc Networks

In the infrastructure-less cognitive radio Ad-hoc networks(CRAHNs),neighbor discovery is the precondition of the execution of the protocols of MAC,topology management and routing,thus has great influence on the perfor-mance of the network.According to the environment of heterogeneous available channel sets and absence of common control channel in CRAHNs,a fast neighbor discovery algorithm based on the spectrum comparability(FNDSC) was proposed in this paper.Different from the existing synchronous algorithms that require users to switch on global channel set(GCS) in the network,a cognitive radio user following FDNSC switches on its respective available channel set(ACS) and transmits beacon messages with a probabilityλ.As GCS is generally big while the number of available channels for a specific user is probably small,the discovery process is considerably shortened.Simulation results show that the proposed algorithm reduces the discovery time by at least 47% compared with existing solutions.