Selection of a cognitive radio channel in cognitive-radio vehicular ad hoc network is a challenging task; it requires periodic sensing of cognitive radio channels by vehicles. This makes vehicles to spend valuable time in sensing that could have been used for data transmission. Road side units may help the vehicles in performing the sensing task. The sensed data should be processed in such a way that the selected channel is not used by its primary users during the transmission of data by a secondary user. This requires the sensed data of past few days to be processed for selection of best channel. In this work, the sensed data is processed according to each minute of the day and a linear programming problem is formulated and solved for calculating the optimum channel. The proposed protocol has been simulated and compared with the random allocation of channels and existing clustering based cognitive medium access control protocol. The results show that the proposed protocol achieves a 12% increase in packet delivery ratio and 21% increase in throughput. The average delay is improved by 6% and the PU collision is decreased by more than 50%.

中文翻译：

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基于区域超级集群的CR-VANET最优信道选择

在认知无线电车载自组织网络中选择认知无线电信道是一项具有挑战性的任务；它需要车辆定期感知认知无线电信道。这使得车辆将宝贵的时间花在本可用于数据传输的传感上。路边单元可以帮助车辆执行传感任务。应以这样一种方式处理感测数据，即在次要用户传输数据期间，其主要用户不使用所选信道。这需要处理过去几天的感测数据以选择最佳频道。在这项工作中，根据一天中的每一分钟处理感测数据，并制定和解决线性规划问题以计算最佳信道。所提出的协议已经被模拟并与信道的随机分配和现有的基于聚类的认知媒体访问控制协议进行了比较。结果表明，所提出的协议实现了 12% 的数据包交付率增加和 21% 的吞吐量增加。平均延迟提升6%，PU碰撞降低50%以上。