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Cagatay Capar

Researcher at Ericsson

Publications -  29
Citations -  698

Cagatay Capar is an academic researcher from Ericsson. The author has contributed to research in topics: Wireless network & Telecommunications link. The author has an hindex of 10, co-authored 29 publications receiving 697 citations. Previous affiliations of Cagatay Capar include IBM & University of Massachusetts Amherst.

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Patent

Network architecture, methods, and devices for a wireless communications network

Stefan Parkvall, +129 more
TL;DR: In this article, the uplink access configuration index is used to identify an uplink AP from among a predetermined plurality of AP configurations, and then the AP is transmitted to the wireless communications network according to the identified AP.
Proceedings ArticleDOI

Secret communication in large wireless networks without eavesdropper location information

TL;DR: In this paper, the authors present achievable scaling results on the per-node secure throughput that can be realized in a large random wireless network of n legitimate nodes in the presence of m eavesdroppers of unknown location.
Proceedings ArticleDOI

Network coding for facilitating secrecy in large wireless networks

TL;DR: This paper first employs simple examples to illustrate how an extension of the secure network coding approach can address difficult problems that have plagued wireless network security; for example, relaxing the known eavesdropper location assumption or avoiding the use of artificial noise generation.
Journal ArticleDOI

Broadcast Analysis for Extended Cooperative Wireless Networks

TL;DR: An asymptotic analysis using an extended random network setting under an additive white Gaussian channel model with path loss shows that the broadcast performance strongly depends on the path loss exponent of the medium.
Patent

Systems and methods for beam selection for hybrid beamforming

TL;DR: In this article, a beam selection method for hybrid beamforming is described, where a first subset of the first set of pairs of beam indices is selected according to a first pruning decision, where the first subset includes at least one of the pairs.