Imperfect Spectrum(不完美的光谱)研究综述
Imperfect Spectrum 不完美的光谱 - To evaluate access delay, we propose an access delay model by jointly considering imperfect spectrum sensing and multi-channel multi-SU transmission, from the cross-layer perspective. [1] The imperfect spectrum monitoring (SM) is a major obstacle to detect the emergence of primary user (PU) quickly during the cognitive users’ (CUs’) data transmission which results data-loss and introduces the interference at PU. [2] In this paper, we take the practical assumption of imperfect spectrum sensing into consideration. [3] Due to imperfect spectrum sensing, secondary transmitters (STs) may cause interference to the primary receiver (PR) and make it difficult for the PR to select a proper modulation and/or coding scheme (MCS). [4] CR technology with imperfect spectrum sensing is adopted by the MD to find the spectrum access opportunities. [5] Nevertheless, STs may cause uncertain interference to the primary receiver (PR) due to imperfect spectrum sensing, which is particularly significant when the wireless links between the primary transmitter (PT) and STs are extremely weak and the wireless links between STs and the PR are non-ignorable. [6] In this paper, considering imperfect spectrum sensing in a cognitive cooperative system, we study the performance optimization for throughput maximization of secondary user (SU) and average delay minimization under maximum delay constraint of primary user (PU) with harvested energy from radio frequency signal of active PU by cooperative SU. [7] Specifically, the paper focuses on the impact of imperfect spectrum sensing on AoI minimization in this setting. [8] This paper investigates the energy efficient resource allocation scheme for orthogonal frequency division multiplexing based heterogeneous cognitive radio network (HCRN) under imperfect spectrum sensing scenario with guaranteed quality of service (QoS). [9] We derive expressions for the average achievable throughput in MIMO-NOMA CR networks with imperfect spectrum sensing using the BCED technique. [10] The effect of imperfect spectrum sensing, PU traffic load, sensing time, the order of sensing, interference channel gains, and number of PUs on the throughput has been investigated. [11] The secondary user aims to minimize the average AoI by adaptively making sensing and update decisions based on its energy availability and the availability of the primary spectrum with either perfect or imperfect spectrum sensing. [12] The interference is caused by an imperfect spectrum sensing of the secondary users (SUs). [13] In the proposed scheme, we assume imperfect spectrum sensing. [14] In this context, this work successfully finds a novel method to accurately estimate the channel DC even under Imperfect Spectrum Sensing (ISS) without requiring any prior knowledge about the licensed channel activity. [15]为了评估接入延迟，我们从跨层的角度，结合不完善的频谱感知和多通道多SU传输，提出了一种接入延迟模型。 [1] 不完善的频谱监测（SM）是在认知用户（CU）数据传输过程中快速检测主用户（PU）出现的主要障碍，导致数据丢失并在PU处引入干扰。 [2] 在本文中，我们考虑了不完美频谱感知的实际假设。 [3] 由于不完善的频谱感知，次要发射机（ST）可能会对主要接收机（PR）造成干扰，并使PR难以选择适当的调制和/或编码方案（MCS）。 [4] MD采用频谱感知不完善的CR技术来寻找频谱接入机会。 [5] 然而，由于频谱感知不完善，ST 可能会对主接收器 (PR) 造成不确定的干扰，这在主发射器 (PT) 和 ST 之间的无线链路极弱且 ST 和 PR 之间的无线链路非常薄弱的情况下尤其显着。不可忽视。 [6] 在本文中，考虑到认知协作系统中不完美的频谱感知，我们研究了在主用户（PU）最大延迟约束下从射频信号中获取能量的次用户（SU）吞吐量最大化和平均延迟最小化的性能优化。合作 SU 的主动 PU。 [7] 具体来说，本文重点关注在此设置中不完美的频谱感知对 AoI 最小化的影响。 [8] 本文研究了在保证服务质量（QoS）的不完美频谱感知场景下，基于正交频分复用的异构认知无线电网络（HCRN）的节能资源分配方案。 [9] 我们使用 BCED 技术推导出具有不完美频谱感测的 MIMO-NOMA CR 网络中平均可实现吞吐量的表达式。 [10] 研究了不完善的频谱感知、PU流量负载、感知时间、感知顺序、干扰信道增益和PU数量对吞吐量的影响。 [11] 次要用户旨在通过基于其能量可用性和具有完美或不完美频谱感知的主要频谱的可用性自适应地做出感知和更新决策来最小化平均AoI。 [12] 干扰是由次要用户（SU）的不完善的频谱感知引起的。 [13] 在所提出的方案中，我们假设不完美的频谱感知。 [14] 在这种情况下，这项工作成功地找到了一种新方法，即使在不完美频谱传感 (ISS) 下也能准确估计信道 DC，而无需任何有关许可信道活动的先验知识。 [15]
Considering Imperfect Spectrum 考虑不完美的频谱
To evaluate access delay, we propose an access delay model by jointly considering imperfect spectrum sensing and multi-channel multi-SU transmission, from the cross-layer perspective. [1] In this paper, considering imperfect spectrum sensing in a cognitive cooperative system, we study the performance optimization for throughput maximization of secondary user (SU) and average delay minimization under maximum delay constraint of primary user (PU) with harvested energy from radio frequency signal of active PU by cooperative SU. [2]为了评估接入延迟，我们从跨层的角度，结合不完善的频谱感知和多通道多SU传输，提出了一种接入延迟模型。 [1] 在本文中，考虑到认知协作系统中不完美的频谱感知，我们研究了在主用户（PU）最大延迟约束下从射频信号中获取能量的次用户（SU）吞吐量最大化和平均延迟最小化的性能优化。合作 SU 的主动 PU。 [2]
imperfect spectrum sensing 不完善的频谱传感
To evaluate access delay, we propose an access delay model by jointly considering imperfect spectrum sensing and multi-channel multi-SU transmission, from the cross-layer perspective. [1] In this paper, we take the practical assumption of imperfect spectrum sensing into consideration. [2] Due to imperfect spectrum sensing, secondary transmitters (STs) may cause interference to the primary receiver (PR) and make it difficult for the PR to select a proper modulation and/or coding scheme (MCS). [3] CR technology with imperfect spectrum sensing is adopted by the MD to find the spectrum access opportunities. [4] Nevertheless, STs may cause uncertain interference to the primary receiver (PR) due to imperfect spectrum sensing, which is particularly significant when the wireless links between the primary transmitter (PT) and STs are extremely weak and the wireless links between STs and the PR are non-ignorable. [5] In this paper, considering imperfect spectrum sensing in a cognitive cooperative system, we study the performance optimization for throughput maximization of secondary user (SU) and average delay minimization under maximum delay constraint of primary user (PU) with harvested energy from radio frequency signal of active PU by cooperative SU. [6] Specifically, the paper focuses on the impact of imperfect spectrum sensing on AoI minimization in this setting. [7] This paper investigates the energy efficient resource allocation scheme for orthogonal frequency division multiplexing based heterogeneous cognitive radio network (HCRN) under imperfect spectrum sensing scenario with guaranteed quality of service (QoS). [8] We derive expressions for the average achievable throughput in MIMO-NOMA CR networks with imperfect spectrum sensing using the BCED technique. [9] The effect of imperfect spectrum sensing, PU traffic load, sensing time, the order of sensing, interference channel gains, and number of PUs on the throughput has been investigated. [10] The secondary user aims to minimize the average AoI by adaptively making sensing and update decisions based on its energy availability and the availability of the primary spectrum with either perfect or imperfect spectrum sensing. [11] The interference is caused by an imperfect spectrum sensing of the secondary users (SUs). [12] In the proposed scheme, we assume imperfect spectrum sensing. [13] In this context, this work successfully finds a novel method to accurately estimate the channel DC even under Imperfect Spectrum Sensing (ISS) without requiring any prior knowledge about the licensed channel activity. [14]为了评估接入延迟，我们从跨层的角度，结合不完善的频谱感知和多通道多SU传输，提出了一种接入延迟模型。 [1] 在本文中，我们考虑了不完美频谱感知的实际假设。 [2] 由于不完善的频谱感知，次要发射机（ST）可能会对主要接收机（PR）造成干扰，并使PR难以选择适当的调制和/或编码方案（MCS）。 [3] MD采用频谱感知不完善的CR技术来寻找频谱接入机会。 [4] 然而，由于频谱感知不完善，ST 可能会对主接收器 (PR) 造成不确定的干扰，这在主发射器 (PT) 和 ST 之间的无线链路极弱且 ST 和 PR 之间的无线链路非常薄弱的情况下尤其显着。不可忽视。 [5] 在本文中，考虑到认知协作系统中不完美的频谱感知，我们研究了在主用户（PU）最大延迟约束下从射频信号中获取能量的次用户（SU）吞吐量最大化和平均延迟最小化的性能优化。合作 SU 的主动 PU。 [6] 具体来说，本文重点关注在此设置中不完美的频谱感知对 AoI 最小化的影响。 [7] 本文研究了在保证服务质量（QoS）的不完美频谱感知场景下，基于正交频分复用的异构认知无线电网络（HCRN）的节能资源分配方案。 [8] 我们使用 BCED 技术推导出具有不完美频谱感测的 MIMO-NOMA CR 网络中平均可实现吞吐量的表达式。 [9] 研究了不完善的频谱感知、PU流量负载、感知时间、感知顺序、干扰信道增益和PU数量对吞吐量的影响。 [10] 次要用户旨在通过基于其能量可用性和具有完美或不完美频谱感知的主要频谱的可用性自适应地做出感知和更新决策来最小化平均AoI。 [11] 干扰是由次要用户（SU）的不完善的频谱感知引起的。 [12] 在所提出的方案中，我们假设不完美的频谱感知。 [13] 在这种情况下，这项工作成功地找到了一种新方法，即使在不完美频谱传感 (ISS) 下也能准确估计信道 DC，而无需任何有关许可信道活动的先验知识。 [14]