In this paper, we consider a cognitive radio (CR) network where the primary network’s feedback information is utilized to develop an access scheme for the secondary network to exploit the underutilized primary spectrum resources. Secondary users (SUs) identify the spectrum opportunities by sensing the spectrum for primary users (PUs) activities and by listening to the PUs feedback. The feedback signals monitored in this research work are the channel quality indicator (CQI) and automatic repeat request (ARQ) available in the PUs network. For detecting the PUs activities, SUs employ soft energy sensing, where SUs access the PUs’ channel with access probabilities that are based on the sensed PUs’ energy level. The access probabilities are optimized to maximize the SUs service rate while maintaining the PUs queues’ stability. The system is modeled as a three-dimensional Markov chain (MC) that captures the number of packets in the PUs queues and the state of the two observed PUs’ feedback signals. The performance of the system is evaluated by deriving the SUs service rate and the average PUs packet delay. We compare the performance of the proposed system with other baseline systems utilizing different types of PUs’ feedback signals. Results reveal the improvement in the SUs service rate and the PUs’ delay of the proposed system compared to the baseline systems. This improvement is mainly due to the fact that in our proposed system SUs have access to extra information, in terms of PUs feedback, as compared to other systems. Therefore, SUs in our proposed system can have better inference on the PUs’ activities; thus more collisions between the PUs and the SUs can be avoided, resulting in significant performance gains in terms of SUs’ throughput and PUs’ average delay.Part of this work was published in [1].

中文翻译：

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认知无线电网络中基于混合ARQ-CQI反馈的接入方案

在本文中，我们考虑了一个认知无线电 (CR) 网络，其中利用主网络的反馈信息来开发辅助网络的接入方案，以利用未充分利用的主频谱资源。次要用户 (SU) 通过感知主要用户 (PU) 活动的频谱并听取 PU 反馈来识别频谱机会。本研究工作中监测的反馈信号是 PU 网络中可用的信道质量指标 (CQI) 和自动重传请求 (ARQ)。为了检测 PU 活动，SU 采用软能量感测，其中 SU 以基于检测到的 PU 能量水平的访问概率访问 PU 的信道。访问概率被优化以最大化 SU 服务率，同时保持 PU 队列的稳定性。该系统被建模为一个三维马尔可夫链 (MC)，它捕获 PU 队列中的数据包数量和两个观察到的 PU 反馈信号的状态。通过推导 SU 服务速率和平均 PU 数据包延迟来评估系统的性能。我们将所提出系统的性能与使用不同类型 PU 反馈信号的其他基线系统进行比较。结果表明，与基线系统相比，所提出系统的 SU 服务率和 PU 延迟有所改善。这种改进主要是由于在我们提出的系统中，与其他系统相比，在 PU 反馈方面，SU 可以访问额外信息。因此，我们提出的系统中的 SU 可以更好地推断 PU 的活动；