6 research outputs found

    IUmote: A Framework for the Efficient Modelling, Evaluation, and Deployment of Algorithms and Hardware for Underwater Communications

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    We present an approach for the modelling and simulating of the modem section of underwater sensor networks. The proposal is based on a specially designed modem architecture and the use of simulation tools and models that represent each of the communication elements: the water medium, physical transducers, electronics, and coding/decoding software. The algorithms can be simulated in the modelling environment; this framework does not require recoding and allows the combination of real and modelled elements. In physical terms, the modem engine provides a decoupled pipelined design of the processing path for the algorithms which allows users to run complex algorithms without requiring a highly demanding specific hardware. The proposal includes a methodology that has allowed us to significantly reduce the effort required in the process, from algorithm development to the effective deployment of the system. As a case study, this paper shows its application and results in the evaluation of a multipath and Doppler-shift correction algorithms.The authors gratefully acknowledge financial support from the CICYT ANDREA: Automated Inspection and Remote Performance of Marine Fish Farms (CTM2011-29691-C02-01), RIDeWAM: Research on Improvement of the Dependability of WSN based Applications by developing a hybrid monitoring platform (TIN2011-28435-C03-01), Valencian Regional Government under Research Project GV/2014/012, and Universitat Politecnica de Valencia under Research Project UPV PAID-02-12. The translation of this paper was funded by the Universitat Politecnica de Valencia, Spain.Sánchez Matías, AM.; Perles Ivars, A.; Yuste Pérez, P.; Capella Hernández, JV.; Serrano Martín, JJ. (2015). IUmote: A Framework for the Efficient Modelling, Evaluation, and Deployment of Algorithms and Hardware for Underwater Communications. International Journal of Distributed Sensor Networks. 2015:1-14. https://doi.org/10.1155/2015/358315S114201

    Low-Complexity Detection for Faster-than-Nyquist Signaling based on Probabilistic Data Association

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    In this paper, we investigate the sequence estimation problem of faster-than-Nyquist (FTN) signaling as a promising approach for increasing spectral efficiency (SE) in future communication systems. In doing so, we exploit the concept of Gaussian separability and propose two probabilistic data association (PDA) algorithms with polynomial time complexity to detect binary phase-shift keying (BPSK) FTN signaling. Simulation results show that the proposed PDA algorithm outperforms the recently proposed SSSSE and SSSgbKSE algorithms for all SE values with a modest increase in complexity. The PDA algorithm approaches the performance of the semidefinite relaxation (SDRSE) algorithm for SE values of 0:96 bits/sec/Hz, and it is within the 0.5 dB signal-to-noise ratio (SNR) penalty at SE values of 1.10 bits/sec/Hz for the fixed values of β= 0:3

    Fast Decoder for Overloaded Uniquely Decodable Synchronous Optical CDMA

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    In this paper, we propose a fast decoder algorithm for uniquely decodable (errorless) code sets for overloaded synchronous optical code-division multiple-access (O-CDMA) systems. The proposed decoder is designed in a such a way that the users can uniquely recover the information bits with a very simple decoder, which uses only a few comparisons. Compared to maximum-likelihood (ML) decoder, which has a high computational complexity for even moderate code lengths, the proposed decoder has much lower computational complexity. Simulation results in terms of bit error rate (BER) demonstrate that the performance of the proposed decoder for a given BER requires only 1 - 2 dB higher signal-to-noise ratio (SNR) than the ML decoder
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