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Cognitive Radio Timing Protocol for Interference-Constrained Throughput Maximization
IEEE Transactions on Cognitive Communications and Networking ( IF 7.4 ) Pub Date : 2021-12-22 , DOI: 10.1109/tccn.2021.3137487
Arifa Ahmed 1 , Deepak Mishra 2 , Ganesh Prasad 1 , Krishna Lal Baishnab 1
Affiliation  

In this paper, we propose a cognitive radio timing protocol (CRTP) to optimize the time allocation for different phases of cognitive radio (CR) operation to maximize the throughput of the secondary user (SU) while satisfying the interference constraint of the primary user (PU). To investigate it, first, we present a three-phase transmission approach for a multi-antenna SU, where, in the first phase, the SU performs spectrum sensing. Subsequently, channel is estimated in the second phase and data is transmitted using beamforming in the third phase. Based on that, we define a frame structure and closed-form expressions for SU’s average throughput as well as interference energy received at the PU’s receiver are derived. Thereafter, we formulate a joint optimization problem to maximize SU’s throughput in underlying variables, sensing duration, channel estimation (CE) duration, and frame duration under the given constraint of interference. Later, the problem is formulated as the joint optimization problem in CE duration and frame duration at the obtained optimal sensing duration. As the problem is jointly nonconvex, we find the jointly optimal solution by a nontrivial alternating optimization algorithm. Via numerical results, we validate the analysis and lastly, it is observed that the joint optimization can achieve an improvement of around 34% against a benchmark.

中文翻译:


用于干扰受限吞吐量最大化的认知无线电定时协议



在本文中,我们提出了一种认知无线电定时协议(CRTP)来优化认知无线电(CR)操作不同阶段的时间分配,以最大化次要用户(SU)的吞吐量,同时满足主用户的干扰约束(聚氨酯)。为了研究它,首先,我们提出了一种多天线 SU 的三相传输方法,其中,在第一阶段,SU 执行频谱感知。随后,在第二阶段中估计信道,并在第三阶段中使用波束成形来发送数据。在此基础上,我们定义了一个帧结构,并导出了 SU 平均吞吐量的封闭式表达式以及 PU 接收器接收到的干扰能量。此后,我们制定了一个联合优化问题,以在给定干扰约束下最大化 SU 在基础变量、感知持续时间、信道估计 (CE) 持续时间和帧持续时间方面的吞吐量。随后,该问题被公式化为在获得的最佳感知持续时间下CE持续时间和帧持续时间的联合优化问题。由于问题是联合非凸的,我们通过非平凡交替优化算法找到联合最优解。通过数值结果,我们验证了分析,最后观察到联合优化相对于基准可以实现约 34% 的改进。
更新日期:2021-12-22
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