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- Gharanjik, A., et al.
(författare)
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Centralized Rainfall Estimation Using Carrier to Noise of Satellite Communication Links
- 2018
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Ingår i: IEEE Journal on Selected Areas in Communications. - : Institute of Electrical and Electronics Engineers (IEEE). - 0733-8716 .- 1558-0008. ; 36:5, s. 1065-1073
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we present a centralized method for real-time rainfall estimation using carrier-to-noise power ratio ( C/N ) measurements from broadband satellite communication networks. The C/N data of both forward link and return link are collected by the gateway station from the user terminals in the broadband satellite communication network and stored in a database. The C/N for such Ka-band scenarios is impaired mainly by the rainfall. Using signal processing and machine learning techniques, we develop an algorithm for real-time rainfall estimation. Extracting relevant features from C/N , we use artificial neural network in order to distinguish the rain events from dry events. We then determine the signal attenuation corresponding to the rain events and examine an empirical relationship between rainfall rate and signal attenuation. Experimental results are promising and prove the high potential of satellite communication links for real environment monitoring, particularly rainfall estimation.
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- Gharanjik, A., et al.
(författare)
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Max-min transmit beamforming via iterative regularization
- 2017
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Ingår i: Conference Record - Asilomar Conference on Signals, Systems and Computers. - : IEEE Computer Society. - 9781538639542 ; , s. 1437-1441
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Konferensbidrag (refereegranskat)abstract
- This paper introduces an iterative optimization framework to tackle the multi-group multicast Max-Min transmit beamforming problem. In each iteration, the optimization problem is decomposed into four sub-problems, all of which can be solved using computationally efficient algorithms. The advantage of proposed method lies in its ability to handle different types of signal constraints like total power and unimodularity; a feature not exhibited by other techniques. The proposed technique outperforms the well-known semidefinite relaxation method in terms of quality of solutions.
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