IEEE Transactions on Cognitive Communications and NetworkingIEEE认知通信与网络汇刊
IEEE Transactions on Cognitive Communications and Networking(英文缩写 IEEE T COGN COMMUN),ISSN 2332-7731,eISSN 2332-7731,中文译名:IEEE认知通信与网络汇刊 是一本学术期刊。本页汇总该期刊的最新影响因子、分区信息以及最新收录于 PubMed 的文献,帮助您快速了解期刊全貌。
发文量统计区间：2025-10-01 至 2026-09-30，按本站收录文献的发表日期统计。
期刊介绍
历年影响因子趋势
| JCR 数据年份 | 影响因子 | JCR 分区 |
|---|---|---|
| 2021 | 6.359 | Q1 |
| 2022 | 8.600 | Q1 |
| 2023 | 7.400 | Q1 |
| 2024 | 7.000 | Q1 |
| 2025 | 8.000 | Q1 |
IEEE Transactions on Cognitive Communications and Networking 最新收录文献
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1. Deterministic Move Lists for Federal Incumbent Protection in the CBRS Band.
PMID:日期:2020The 3.5 GHz citizens broadband radio service (CBRS) band in the U.S. is a key portion of mid-band spectrum shared between commercial operators and existing federal and non-federal incumbents. To protect the federal incumbents from harmful interference, a spectrum access system (SAS) is required to use a common, standardized algorithm, called the move list algorithm, to suspend transmissions of some CBRS devices (CBSDs) on channels in which the incumbent becomes active. However, the current reference move list implementation used for SAS testing is non-deterministic in that it uses a Monte Carlo estimate of the 95 percentile of the aggregate interference from CBSDs to the incumbent. This leads to uncertainty in move list results and in the aggregate interference check of the test. This paper uses upper and lower bounds on the aggregate interference distribution to compute deterministic move lists. These include the reference move list used by the testing system and an operational move list used by the SAS itself. We evaluate the performance of the proposed deterministic move lists using reference implementations of the standards and simulated CBSD deployments in the vicinity of federal incumbent dynamic protection areas.
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2. Performance Impact of Coexistence Groups in a GAA-GAA Coexistence Scheme in the CBRS Band.
PMID:日期:2020The General Authorized Access (GAA) users in the Citizens Broadband Radio Service (CBRS) band are the lowest priority users. They must make sure that they do not cause harmful interference to the higher tier users while cooperating with each other to minimize potential interference among themselves. Thus, efficient GAA coexistence scheme is essential for the operation of GAA users and to obtain high spectrum utilization. Towards this goal, the Wireless Innovation Forum (WInnForum) has recommended three schemes to facilitate GAA-GAA coexistence. We had reported a performance study of one of these schemes (called Approach 1), but that study did not have any Coexistence Group (CxG). A CxG is responsible for managing interference among its CBRS devices (CBSDs). In this paper, we study the performance of Approach 1 without CxGs as well as with different number of CxGs, in various configurations. We conduct our study around two locations in the USA using actual terrain and land cover data of the continental USA. We evaluate performance of the scheme at different deployment densities, using different propagation models at those two locations with different number of CxGs. We provide some interesting insights into the costs and benefits of having CxGs in the deployment.
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3. Intelligent Traffic Adaptive Resource Allocation for Edge Computing-based 5G Networks.
PMID:日期:2019The popularity of smart mobile devices has led to a tremendous increase in mobile traffic, which has put a considerable strain on the fifth generation of mobile communication networks (5G). Among the three application scenarios covered by 5G, ultra-high reliability and ultra-low latency (uRLLC) communication can best be realized with the assistance of artificial intelligence. For a combined 5G, edge computing and IoT-Cloud (a platform that integrates the Internet of Things and cloud) in particular, there remains many challenges to meet the uRLLC latency and reliability requirements despite a tremendous effort to develop smart data-driven methods. Therefore, this paper mainly focuses on artificial intelligence for controlling mobile-traffic flow. In our approach, we first develop a traffic-flow prediction algorithm that is based on long short-term memory (LSTM) with an attention mechanism to train mobile-traffic data in single-site mode. The algorithm is capable of effectively predicting the peak value of the traffic flow. For a multi-site case, we present an intelligent IoT-based mobile traffic prediction-and-control architecture capable of dynamically dispatching communication and computing resources. In our experiments, we demonstrate the effectiveness of the proposed scheme in reducing communication latency and its impact on lowering packet-loss ratio. Finally, we present future work and discuss some of the open issues.
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4. An Energy-Aware Retransmission Approach in SWIPT-Based Cognitive Relay Systems.
PMID:日期:2019In this paper, cooperative spectrum sharing is considered between a primary user (PU) and a secondary user (SU), where the off-the-grid secondary transmitter (ST) serves as a cognitive relay to forward both the received primary and secondary signals by exploiting simultaneous wireless information and power transfer (SWIPT). Based on a two-phase relaying model, power splitting is adopted by the ST for energy harvesting and information processing in the first phase. Next, the harvested energy at the ST is used to amplify-and-forward a linearly weighted combination of the primary and secondary signals, in the second phase. To enhance the reliability of the system and utilize the energy harvested more wisely, an energy-aware retransmission (EAR) scheme is proposed in the first phase to guarantee that a certain minimum amount of energy is collected by the ST before launching the second phase. Both outage and throughput performances are theoretically analyzed for the PU and the SU. Simulation results demonstrate that a win-win relationship is built between the PU and the SU under proper parameter configurations, and the proposed EAR scheme can bring additional performance gains in unfavorable conditions imposed under and
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5. Deep Learning Classification of 3.5 GHz Band Spectrograms with Applications to Spectrum Sensing.
PMID:日期:2019In the United States, the Federal Communications Commission has adopted rules permitting commercial wireless networks to share spectrum with federal incumbents in the 3.5 GHz Citizens Broadband Radio Service band. These rules require commercial systems to vacate the band when sensors detect radars operated by the U.S. military; a key example being the SPN-43 air traffic control radar. Such sensors require highly-accurate detection algorithms to meet their operating requirements. In this paper, using a library of over 14,000 3.5 GHz band spectrograms collected by a recent measurement campaign, we investigate the performance of thirteen methods for SPN-43 radar detection. Namely, we compare classical methods from signal detection theory and machine learning to several deep learning architectures. We demonstrate that machine learning algorithms appreciably outperform classical signal detection methods. Specifically, we find that a three-layer convolutional neural network offers a superior tradeoff between accuracy and computational complexity. Last, we apply this three-layer network to generate descriptive statistics for the full 3.5 GHz spectrogram library. Our findings highlight potential weaknesses of classical methods and strengths of modern machine learning algorithms for radar detection in the 3.5 GHz band.
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6. Resource Selection in Cognitive Networks With Spiking Neural Networks.
PMID:日期:2018-08-14This paper explores the feasibility of a spiking neural network-based approach to cognitive networking, that is potentially suitable for low-power neuromorphic chips. We discuss the design of a cognitive network controller (CNC), which can dynamically optimize the selection of resources for recurrent network tasks, based on both its assigned objectives and observations of the actual performance achieved by each resource. We present a coding strategy for the action decisions based on the time-to-fire of spikes, a learning algorithm, and a regulation method to keep synapse strengths within an adequate range. To evaluate the proposed method, we apply the CNC to a challenged network environment using simulation. In this scenario, the CNC requires to optimize the average file transfer time over a multichannel space communication link, which is available only for a time window because of orbital dynamics. Compared to conventional methods, we show that the CNC achieves its objective for a broad range of offered loads. We examine the impact of key system factors that include learning and space protocol parameters. The proposed CNC potentially fosters the development of new cognitive networking applications.
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7. Dynamic Spectrum Access Algorithms Based on Survival Analysis.
PMID:日期:2017-11-09In this study, we design and implement two algorithms for dynamic spectrum access that are based on survival analysis. They use a non-parametric estimate of the cumulative hazard function to predict the remaining idle time available for secondary transmission subject to the constraint of a preset probability of successful completion. In addition to theoretical performance analysis of the algorithms, we evaluate them using data collected from a long term evolution band to model primary user activity to demonstrate their effectiveness in real-world scenarios, even at fine time scales. The algorithms are run in different configurations, i.e., they are trained and run on a few combinations of data sets. Our results show that as long as the cumulative hazard functions are fairly similar across datasets, the algorithms can be trained on one dataset and run on that of another without any significant degradation of performance. The algorithms achieve fairly high white space utilization and have a measured probability of interference that is at or below the preset threshold.
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8. 3.5 GHz Environmental Sensing Capability Detection Thresholds and Deployment.
PMID:日期:2017-09-01Spectrum sharing in the 3.5 GHz band between commercial and government users along U.S. coastal areas depends on an environmental sensing capability (ESC)-that is, a network of radio frequency sensors and a decision system-to detect the presence of incumbent shipborne radar systems and trigger protective measures, as needed. It is well known that the sensitivity of these sensors depends on the aggregate interference generated by commercial systems to the incumbent radar receivers, but to date no comprehensive study has been made of the aggregate interference in realistic scenarios and its impact on the requirement for detection of the radar signal. This paper presents systematic methods for determining the placement of ESC sensors and their detection thresholds to adequately protect incumbent shipborne radar systems from harmful interference. Using terrain-based propagation models and a population-based deployment model, the analysis finds the offshore distances at which protection must be triggered and relates these to the detection levels of coastline sensors. We further show that sensor placement is a form of the well-known set cover problem, which has been shown to be NP-complete, and demonstrate practical solutions achieved with a greedy algorithm. Results show detection thresholds to be as much as 22 dB lower than required by current industry standards. The methodology and results presented in this paper can be used by ESC operators for planning and deployment of sensors and by regulators for testing sensor performance.