Browsing by Subject "Practical systems"

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    An asynchronous two-way relay system with full delay diversity in time-varying multipath environments
    (IEEE, 2015-02) Salim, A.; Duman, Tolga M.
    We consider design of asynchronous OFDM-based diamond two-way-relay (DTWR) systems in time-varying frequency-selective (doubly-selective) fading channels such as underwater acoustic (UWA) channels. In a DTWR channel, two users exchange their messages with the help of two relays. Most of the existing work on asynchronous DTWR systems assume only small relative propagation delays between the received signals at each node. However, in practical systems, significant delays may take place. Our proposed system is able to tolerate the delay even if it exceeds the length of the OFDM block which is almost inevitable in UWA channels. We provide analytical and numerical results to verify the advantages of the proposed scheme in mitigating large delays in different fading conditions.
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    Sparse ground-penetrating radar imaging method for off-the-grid target problem
    (SPIE, 2013) Gurbuz, A. C.; Teke, O.; Arıkan, Orhan
    Spatial sparsity of the target space in subsurface or through-the-wall imaging applications has been successfully used within the compressive-sensing framework to decrease the data acquisition load in practical systems, while also generating highresolution images. The developed techniques in this area mainly discretize the continuous target space into grid points and generate a dictionary of model data that is used in image-reconstructing optimization problems. However, for targets that do not coincide with the computation grid, imaging performance degrades considerably. This phenomenon is known as the off-grid problem. This paper presents a novel sparse ground-penetrating radar imaging method that is robust for off-grid targets. The proposed technique is an iterative orthogonal matching pursuit-based method that uses gradientbased steepest ascent-type iterations to locate the off-grid target. Simulations show that robust results with much smaller reconstruction errors are obtained for multiple off-grid targets compared to standard sparse reconstruction techniques. © 2013 SPIE and IS&T.