IEEE Transactions on Cognitive Communications and Networking

Top Research Topics at IEEE Transactions on Cognitive Communications and Networking?

IEEE Transactions on Cognitive Communications and Networking mainly deals with areas of study such as Cognitive radio, Computer network, Wireless, Communication channel and Distributed computing. IEEE Transactions on Cognitive Communications and Networking explores topics in Cognitive radio which can be helpful for research in disciplines like Transmitter, Transmission (telecommunications), Real-time computing and Mathematical optimization. The Mathematical optimization works, particularly on Optimization problem are tackled in IEEE Transactions on Cognitive Communications and Networking.

It addresses concerns in Computer network which are intertwined with other disciplines, such as Wireless network and Throughput. The concepts on Wireless presented in IEEE Transactions on Cognitive Communications and Networking can also apply to other research fields, including Relay, Wireless sensor network, Deep learning, Artificial intelligence and Base station. The work on Artificial intelligence presented in IEEE Transactions on Cognitive Communications and Networking focuses on Artificial neural network in particular.

IEEE Transactions on Cognitive Communications and Networking connects the study in Base station with the closely related area of Beamforming. Discussions in IEEE Transactions on Cognitive Communications and Networking are anchored in the subject of Communication channel and the similar topic of Algorithm. The Distributed computing works featured in it incorporate elements from Resource allocation and Reinforcement learning.

• Cognitive radio (29.18%)
• Computer network (27.22%)
• Wireless (21.35%)

What are the most cited papers published in the journal?

• An Introduction to Deep Learning for the Physical Layer (1202 citations)
• Deep Reinforcement Learning for Dynamic Multichannel Access in Wireless Networks (224 citations)
• A Very Brief Introduction to Machine Learning With Applications to Communication Systems (222 citations)

Research areas of the most cited articles at IEEE Transactions on Cognitive Communications and Networking:

The journal publications cover a variety of subjects, including Cognitive radio, Wireless, Computer network, Reinforcement learning and Transmitter. The works on Wireless tackled in the published papers bring together disciplines like Underlay and Deep learning, Artificial intelligence. The published articles address concerns in Transmitter which are intertwined with other disciplines, such as Artificial neural network, Relay and Physical layer.

What topics the last edition of the journal is best known for?

• Computer network
• Artificial intelligence
• Statistics

The previous edition focused in particular on these issues:

The aim of IEEE Transactions on Cognitive Communications and Networking is to expand the discussion of research in Wireless, Computer network, Artificial intelligence, Distributed computing and Communication channel. While Wireless is the focus of the journal, it also provided insights into the studies of Relay, Wireless sensor network, Power control and Communications system. The close relationship between Throughput and Cognitive radio is one of the points of interest dissected in Computer network research.

Presentations on Artificial intelligence include those discussing Deep learning and Convolutional neural network. The presented Distributed computing research provided insight into the related

• Reinforcement learning which connect with Markov decision process,
• Enhanced Data Rates for GSM Evolution which intersects with area such as Server.. Communication channel research featured in IEEE Transactions on Cognitive Communications and Networking incorporates concerns from various other topics such as Algorithm, Telecommunications link and Base station.

The most cited articles from the last journal are:

• Channel Estimation Method and Phase Shift Design for Reconfigurable Intelligent Surface Assisted MIMO Networks (24 citations)
• Multi-Agent Deep Reinforcement Learning-Based Trajectory Planning for Multi-UAV Assisted Mobile Edge Computing (22 citations)
• Robust Secure Beamforming for Wireless Powered Cognitive Satellite-Terrestrial Networks (18 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

Top authors and change over time

The top authors publishing in IEEE Transactions on Cognitive Communications and Networking (based on the number of publications) are:

• Mohamed-Slim Alouini (10 papers) absent at the last edition,
• Dusit Niyato (9 papers) published 4 papers at the last edition, 2 more than at the previous edition,
• Marwan Krunz (8 papers) published 1 paper at the last edition the same number as at the previous edition,
• Zhu Han (7 papers) published 3 papers at the last edition, 1 more than at the previous edition,
• Xuemin Shen (7 papers) published 4 papers at the last edition, 1 more than at the previous edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing in IEEE Transactions on Cognitive Communications and Networking (based on the number of publications) are:

• Virginia Tech (19 papers) published 3 papers at the last edition, 2 more than at the previous edition,
• King Abdullah University of Science and Technology (14 papers) published 2 papers at the last edition, 1 less than at the previous edition,
• University of Electronic Science and Technology of China (14 papers) published 5 papers at the last edition the same number as at the previous edition,
• University of Oulu (13 papers) published 1 paper at the last edition,
• Tsinghua University (12 papers) published 6 papers at the last edition, 2 more than at the previous edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2021 edition, 15.97% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 28.93% were posted by at least one author from the top 10 institutions publishing in the journal. Another 13.22% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 18.18% of all publications and 39.67% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.