ABSTRACT

Cognitive Radio Ad-hoc Network (CRAHN) is one of the building blocks of heterogeneous networks to improve accessibility and spectral efficiency. The prioritized spectrum access is the key to maintain the efficiency of CRAHN. However, in CRAHN, TCP results in severe throughput reduction since it cannot differentiate between the packet loss due to SU’s transmission-blocking and packet loss due to congestion. In this paper, two significant events are investigated that caused secondary user blocking. Besides, using a Continuous-Time Markov chain (CTMC), we develop an analytical model to estimate the TCP throughput and end to end delay. The experimental results based on the NS2 confirm the accuracy of the proposed model and show that the throughput and the average end-to-end delay are improved based on the proposed CTMC model comparing with some transport protocol in the cognitive radio networks. The performance results through simulation show that the proposed model not only provides less energy consumption, also achieves up to 40% and 20% improvement of the throughput comparing with the classical TFRC and TFRC-CR, respectively.

摘要

认知无线电自组织网络 (CRAHN) 是异构网络的构建模块之一，可提高可访问性和频谱效率。优先的频谱接入是维持 CRAHN 效率的关键。然而，在 CRAHN 中，TCP 导致吞吐量严重下降，因为它无法区分由于 SU 的传输阻塞导致的数据包丢失和由于拥塞导致的数据包丢失。在本文中，调查了导致二级用户阻塞的两个重要事件。此外，使用连续时间马尔可夫链（CTMC），我们开发了一个分析模型来估计 TCP 吞吐量和端到端延迟。基于NS2的实验结果证实了所提出模型的准确性，并表明与认知无线电网络中的某些传输协议相比，基于所提出的CTMC模型的吞吐量和平均端到端延迟都有所提高。通过仿真得出的性能结果表明，与经典的 TFRC 和 TFRC-CR 相比，所提出的模型不仅能耗更低，而且吞吐量分别提高了 40% 和 20%。