Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Countries citing papers authored by Matti Latva‐aho
Since
Specialization
Citations
This map shows the geographic impact of Matti Latva‐aho's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Matti Latva‐aho with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matti Latva‐aho more than expected).
This network shows the impact of papers produced by Matti Latva‐aho. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Matti Latva‐aho. The network helps show where Matti Latva‐aho may publish in the future.
Co-authorship network of co-authors of Matti Latva‐aho
This figure shows the co-authorship network connecting the top 25 collaborators of Matti Latva‐aho.
A scholar is included among the top collaborators of Matti Latva‐aho based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Matti Latva‐aho. Matti Latva‐aho is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
López, Onel L. Alcaraz, et al.. (2021). On the SIR meta distribution in massive MTC networks with scheduling and data aggregation. University of Oulu Repository (University of Oulu).2 indexed citations
Manosha, K. B. Shashika, et al.. (2020). An initial access optimization algorithm for millimeter wave 5G NR networks. University of Oulu Repository (University of Oulu).5 indexed citations
12.
Alves, Hirley, et al.. (2020). Iterative Bayesian-based localization mechanism for industry verticals. University of Oulu Repository (University of Oulu).3 indexed citations
13.
Rajapaksha, Nuwanthika, Nandana Rajatheva, & Matti Latva‐aho. (2020). Low complexity autoencoder based end-to-end learning of coded communications systems. University of Oulu Repository (University of Oulu).8 indexed citations
14.
Alves, Hirley, et al.. (2019). In-band pilot overhead in ultra-reliable low latency decode and forward relaying. University of Oulu Repository (University of Oulu).2 indexed citations
15.
Rajatheva, Nandana, et al.. (2019). Autonomous driving without a burden:view from outside with elevated LiDAR. University of Oulu Repository (University of Oulu).20 indexed citations
16.
Shehab, Mohammad, Hirley Alves, & Matti Latva‐aho. (2018). Ultra reliable communication via opportunistic ARQ transmission in cognitive networks. University of Oulu Repository (University of Oulu).4 indexed citations
17.
Sanguanpuak, Tachporn, Sudarshan Guruacharya, Ekram Hossain, Nandana Rajatheva, & Matti Latva‐aho. (2018). Infrastructure sharing for mobile network operators:analysis of trade-offs and market. University of Oulu Repository (University of Oulu).26 indexed citations
18.
Bennis, Mehdi, et al.. (2018). Path Selection and Rate Allocation for Ultra-Reliable and Low Latency 5G mmWave Networks.1 indexed citations
19.
Shehab, Mohammad, et al.. (2017). On the effective energy efficiency of ultra-reliable networks in the finite blocklength regime. University of Oulu Repository (University of Oulu).5 indexed citations
20.
Abdel‐Hafez, Mohammed, Zexian Li, & Matti Latva‐aho. (2004). Evaluation of Uplink and Downlink MC-CDMA Receivers in Generalized Fading Channels(Wireless Communication Technology). IEICE Transactions on Communications. 87(1). 88–96.5 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.