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.
Joint tx-rx beamforming design for multicarrier mimo channels: a unified framework for convex optimization
2003864 citationsDaniel P. Palomar, M.A. Lagunas et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of M.A. Lagunas'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 M.A. Lagunas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M.A. Lagunas more than expected).
This network shows the impact of papers produced by M.A. Lagunas. 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 M.A. Lagunas. The network helps show where M.A. Lagunas may publish in the future.
Co-authorship network of co-authors of M.A. Lagunas
This figure shows the co-authorship network connecting the top 25 collaborators of M.A. Lagunas.
A scholar is included among the top collaborators of M.A. Lagunas 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 M.A. Lagunas. M.A. Lagunas is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Lagunas, M.A., et al.. (2018). A novel approach to MISO interference networks under maximum receive-power regulation. WSEAS Transactions on Systems and Control archive. 13(2018). 298–315.2 indexed citations
6.
Lagunas, Eva, Montse Nájar, & M.A. Lagunas. (2011). Space-time-frequency candidate methods for spectrum sensing. Open Repository and Bibliography (University of Luxembourg). 1234–1238.2 indexed citations
7.
Lagunas, M.A., Ana I. Pèrez-Neira, & Miguel Ángel Vázquez. (2010). Joint temporal-spatial reference beamforming: EIG beamforming. International Conference on Communications. 91–97.1 indexed citations
8.
Mendéz-Rojas, M.A., Ana I. Pèrez-Neira, & M.A. Lagunas. (2009). DVB-T Candidate power detector for Cognitive Radio. RECERCAT (Consorci de Serveis Universitaris de Catalunya). 1893–1897.1 indexed citations
9.
Zorba, Nizar, Ana I. Pèrez-Neira, & M.A. Lagunas. (2006). A reduced complexity MIMO broadcast scheme: Away between opportunistic and dirty paper implementation. European Signal Processing Conference. 1–5.2 indexed citations
Pascual‐Iserte, Antonio, et al.. (2003). Performance degradation of an OFDM-MIMO system with imperfect channel state information at the transmitter. RECERCAT (Consorci de Serveis Universitaris de Catalunya). 396–400.1 indexed citations
Palomar, Daniel P. & M.A. Lagunas. (2001). Capacity of spatially flattened frequency-selective MIMO channels using linear processing techniques in transmission.4 indexed citations
18.
Palomar, Daniel P., Montse Nájar, & M.A. Lagunas. (2000). Self-reference spatial diversity processing for spread spectrum communications. AEU - International Journal of Electronics and Communications. 54(5). 267–276.1 indexed citations
19.
Goldberg, J., Alba Pagés-Zamora, M.A. Lagunas, J.R. Fonollosa, & G. Vazquez. (1996). Experimental Results For An Sdma Mobile Communication's Antenna Array System. QRU Quaderns de Recerca en Urbanisme. 2. 455–458.1 indexed citations
20.
Ortigueira, Manuel Duarte & M.A. Lagunas. (1990). A recursive SVD algorithm for array signal processing. European Signal Processing Conference. 657–660.4 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.