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首页> 外文期刊>Vehicular Technology, IEEE Transactions on >Cross-Layer Design for TCP Performance Improvement in Cognitive Radio Networks
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Cross-Layer Design for TCP Performance Improvement in Cognitive Radio Networks

机译:认知无线电网络中用于TCP性能改进的跨层设计

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摘要

In cognitive radio (CR) networks, the end-to-end transmission-control protocol (TCP) performance experienced by secondary users is a very important factor that evaluates the secondary user perceived quality of service (QoS). Most previous works in CR networks ignore the TCP performance. In this paper, we take a cross-layer design approach to jointly consider the spectrum sensing, access decision, physical-layer modulation and coding scheme, and data-link layer frame size in CR networks to maximize the TCP throughput in CR networks. The wireless channel and the primary network usage are modeled as a finite-state Markov process. Due to the miss detection and the estimation error experienced by secondary users, the system state cannot be directly observed. Consequently, we formulate the cross-layer TCP throughput optimization problem as a partially observable Markov decision process (POMDP). Simulation results show that the design parameters in CR networks have a significant impact on the TCP throughput, and the TCP throughput can be substantially improved if the low-layer parameters in CR networks are optimized jointly.
机译:在认知无线电(CR)网络中,次要用户体验的端到端传输控制协议(TCP)性能是评估次要用户感知服务质量(QoS)的非常重要的因素。 CR网络中以前的大多数工作都忽略了TCP性能。在本文中,我们采用跨层设计方法来共同考虑CR网络中的频谱感知,访问决策,物理层调制和编码方案以及数据链路层帧大小,以最大化CR网络中的TCP吞吐量。无线信道和主要网络使用情况被建模为有限状态马尔可夫过程。由于次要用户遇到的未命中检测和估计错误,因此无法直接观察系统状态。因此,我们将跨层TCP吞吐量优化问题公式化为部分可观察的马尔可夫决策过程(POMDP)。仿真结果表明,CR网络中的设计参数对TCP吞吐量有重大影响,如果共同优化CR网络中的低层参数,则可以大大提高TCP吞吐量。

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