| No | Date | Title | Speaker | Presentation | Discussion |
| 1 | 2013-07-11 | A sparse signal reconstruction perspective for source localization with sensor arrays | J.Oliver | (pdf) | |
| In this paper, the authors present a source localization method based on sparse representation of sensor measurements. In particular, they use SVD of the data matrix obtained from the sensors to summarize the multiple measurements. The SVD summarized data is then sparsely represented in order to detect the sources. The authors also proposed grid refinement in order to mitigate the effects of limiting estimates to a grid of spatial locations. They demonstrate the superior resolution ability with limited time samples of their method over the existing methods via various experiments. | |||||
| 2 | 2013-07-18 | Enhancing Iterative Decoding of Cyclic LDPC Codes Using Their Automorphism Groups | Jeongmin | (pdf) | |
| In this paper they focus on cyclic LDPC codes defined by a circulant parity-check matrix and consider two known subgroups of the automorphism group of a cyclic code. For the large class of idempotent-based cyclic LDPC codes in the literature, they show that the two subgroups only provide equivalent parity-check matrices and thus cannot be harnessed for iterative decoding. Towards exploiting the automorphism group of a code, they propose a new class of cyclic LDPC codes based on pseudo-cyclic MDS codes with two information symbols,for which nonequivalent parity-check matrices are obtained. Simulation results show that for our constructed codes of short lengths, the automorphism group can significantly enhance the iterative decoding performance. | |||||
| 3 | 2013-07-25 | Multiuser detection of sparsely spread CDMA | Jaewook | ||
| Abstract: This paper has discussed about design and analysis of multiuser detection (MUD) using sparsely spread CDMA systems. The objective of the MUD problem is how to detect multiple user signals simultaneously at the low computational cost. The main obstacle is multiple-access interference (MAI). These multiple user signals are interference for each user detection one another. The MAI problem arise in most CDMA systems, and optimal detection in such systems requires exponentially growing computation as the number of user increases. But a good news is that the simultaneous users in time is very few. Therefore, this paper investigates a suboptimal MUD detection using sparse CDMA systems. The key idea of the proposed system is to encode the transmitted waveforms using sparse spread CDMA codes and detect the signal using a linear-complexity belief propagation (BP) algorithm. We summarize the contributions of this work is following: – Description the sparse CDMA system – Properties of the sparsly spread CDMA codes for the convergence of the BP algorithm – Design of the BP algorithm for the MUD problem – Asymptotic analysis of performance of the BP algorithm based MUD detection In this report, we aim to sketch the key point of each contribution of this paper. |
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June 2013