1,720,965 research outputs found
DSVCA: A novel distributed clustering algorithm for wireless sensor networks based on statistical data correlation
No full textTopology-aware System Design Exploration for Embedded Applications implemented onto Heterogeneous Multiprocessor SoC
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Application-Specific System-Level Design Space Exploration for Heterogeneous Multiprocessor Embedded Platforms
No full textSmolyak’s Algorithm: A Simple and Accurate Framework for the Analysis of Correlated Log-Normal Power-Sums
No full textThe accurate analysis of Log–Normal power–sums requires the computation of multidimensional integrals with unknown closed–form. Typical approaches to numerically com- pute them are based on the full tensor–product formula, whose complexity raises exponentially with the number of summands. In this Letter, we propose a different method which is called Smolyak’s algorithm. It belongs to the family of numerical integration techniques on sparse grids, and can be used in conjunction with several approximation methods for Log–Normal power–sums. Numerical results will show a complexity reduction greater than 99% without numerical accuracy degradation
Cooperative Spectrum Sensing for Cognitive Radio Networks with Amplify and Forward Relaying over Correlated Log-Normal Shadowing
No full textDistributed Data Fusion over Correlated Log-Normal Sensing and Reporting Channels: Application to Cognitive Radio Networks
No full textIn this Letter, we propose an advanced framework for performance analysis and design of decentralized data fusion problems. In particular, the performance of a multilayer system setup for data detection, which includes realistic sensing/reporting channels and correlated log-normal shadow-fading in all wireless links of the cooperative network, will be studied. The system setup will be used to analyze the performance of cooperative spectrum sensing problems adopting an amplify-and-forward (AF) relay protocol.We will show that, even though often overlooked in typical cooperative spectrum sensing analysis, shadowing correlation on the reporting channel can yield similar performance degradations as shadowing correlation on the sensing channel. All findings will be substantiated via theoretical arguments and Monte Carlo simulations, and, in particular, novel approximation methods to account for correlated log-normal shadowing in cooperative spectrum sensing problems will be introduced in this paper
Second-order statistics of Amplify-and-Forward multi-hop wireless networks: A framework for computing the end-to-end SNR auto-correlation function over Log-Normal shadowing channels
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