基于PU统计延迟的机会协作认知无线网络资源分配

Tao Wang, Yichen Wang, Zhuang Li, Zhangnan Wang
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引用次数: 0

摘要

认知无线网络(cognitive radio network, CRN)中的协作可以在保证主用户(PU)服务质量(QoS)的同时,提高主用户(PU)和从用户(SU)的性能。本文提出了一种机会合作认知无线网络(OCCRN)的联合时隙和功率分配策略,使PU和SU可以机会合作以提高系统性能。该方案旨在实现双重效益,既能提高SU的吞吐量,又能降低PU的功耗,同时又能保护PU的统计延迟QoS提供。根据有效容量理论,将统计时延QoS需求转化为有效容量需求。因此,我们制定了一个多目标优化问题,在满足PU的统计延迟要求和SU的功率预算的前提下,最大化SU的有效容量和最小化PU的平均功耗。利用加权法,将多目标优化问题转化为单目标优化问题,验证其为凸,然后用拉格朗日对偶方法求解。利用提出的资源分配策略,OCCRN首先选择每一帧的传输模式,并在给定约束条件下动态调整PU和SU的时隙和传输功率,以优化双重效益。仿真结果显示了在不同的统计延迟QoS要求下,SU的吞吐量和PU的功耗之间的权衡,说明了PU和SU如何相互协作以达到最优性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Resource Allocation in Opportunistic Cooperative Cognitive Radio Network with PU's Statistical Delay QoS Provisioning
Cooperation in cognitive radio network (CRN) can improve the performance of both primary user (PU) and secondary user (SU) while guaranteeing PU's quality-of-service (QoS). In this paper, we propose a joint time slot and power allocation policy for an opportunistic cooperative cognitive radio network (OCCRN) where PU and SU can opportunistically cooperate with each other to improve the system performance. The proposed scheme aims at two-fold benefits that can improve SU's throughput and reduce PU's power consumption while protecting PU's statistical delay QoS provisioning. According to the theory of effective capacity, the statistical delay QoS requirement can be converted into the requirement of the effective capacity. Thus, we formulated a multi-objective optimization problem maximizing SU's effective capacity and minimizing PU's average power consumption subject to PU's statistical delay requirement and SU's power budget. With the weighting method, the multi-objective optimization problem is transformed into a single-objective optimization problem which is verified as convex and then solved by the Lagrangian dual method. Utilizing the proposed resource allocation policy, the OCCRN first chooses the transmission mode for each frame and dynamically adjusts the time slot and transmission power of both PU and SU to optimize the two-fold benefits under given constraints. Simulation results demonstrate the trade-off between SU's throughput and PU's power consumption under diverse statistical delay QoS requirements, illustrating how PU and SU cooperate with each other to achieve optimal performance.
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