893 research outputs found
Structured random measurements in signal processing
Compressed sensing and its extensions have recently triggered interest in
randomized signal acquisition. A key finding is that random measurements
provide sparse signal reconstruction guarantees for efficient and stable
algorithms with a minimal number of samples. While this was first shown for
(unstructured) Gaussian random measurement matrices, applications require
certain structure of the measurements leading to structured random measurement
matrices. Near optimal recovery guarantees for such structured measurements
have been developed over the past years in a variety of contexts. This article
surveys the theory in three scenarios: compressed sensing (sparse recovery),
low rank matrix recovery, and phaseless estimation. The random measurement
matrices to be considered include random partial Fourier matrices, partial
random circulant matrices (subsampled convolutions), matrix completion, and
phase estimation from magnitudes of Fourier type measurements. The article
concludes with a brief discussion of the mathematical techniques for the
analysis of such structured random measurements.Comment: 22 pages, 2 figure
Secrecy Rate of the Cooperative RSMA-Aided UAV Downlink Relying on Optimal Relay Selection
The Cooperative Rate-Splitting (CRS) scheme, proposed evolves from
conventional Rate Splitting (RS) and relies on forwarding a portion of the RS
message by the relaying users. In terms of secrecy enhancement, it has been
shown that CRS outperforms its non-cooperative counterpart for a two-user
Multiple Input Single Output (MISO) Broadcast Channel (BC). Given the massive
connectivity requirement of 6G, we have generalized the existing secure
two-user CRS framework to the multi-user framework, where the highest-security
users must be selected as the relay nodes. This paper addresses the problem of
maximizing the Worst-Case Secrecy Rate (WCSR) in a UAV-aided downlink network
where a multi-antenna UAV Base-Station (UAV-BS) serves a group of users in the
presence of an external eavesdropper (Eve). We consider a practical scenario in
which only imperfect channel state information of Eve is available at the
UAV-BS. Accordingly, we conceive a robust and secure resource allocation
algorithm, which maximizes the WCSR by jointly optimizing both the Secure
Relaying User Selection (SRUS) and the network parameter allocation problem,
including the RS transmit precoders, message splitting variables, time slot
sharing and power allocation. To circumvent the resultant non-convexity owing
to the discrete variables imposed by SRUS, we propose a two-stage algorithm
where the SRUS and network parameter allocation are accomplished in two
consecutive stages. With regard to the SRUS, we study both centralized and
distributed protocols. On the other hand, for jointly optimizing the network
parameter allocation we resort to the Sequential Parametric Convex
Approximation (SPCA) algorithm. Our numerical results show that the proposed
solution significantly outperforms the existing benchmarks for a wide range of
network loads in terms of the WCSR.Comment: arXiv admin note: text overlap with arXiv:1910.07843 by other author
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