January 2014
| 1 | 2014-01-28 | Cooperative Spectrum Sensing with Transmit and Relay Diversity in Cognitive Radio Networks | Zafar Iqbal | (DOC) | ||
| The authors investigate the problem of cooperative spectrum sensing in cognitive radio (CR) networks over Rayleigh fading environment. The performance is analyzed by studying the error effects on the decision reporting and the results show that the cooperative spectrum sensing performance is limited by the probability of reporting errors. | ||||||
December 2013
| 1 | 2013-12-09 | Robust Compressive Data Gathering in Wireless Sensor Networks | Jongmok Shin | (DOC) | ||
| In this paper, authors investigate the impact of outlying sensor readings and broken links on high-fidelity data gathering, and propose approaches based on the compressive sensing theory to identify outlying sensor readings and derive the corresponding accurate values, and to infer broken links in Wireless Sensor Networks. |
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November 2013
| 1 | 2013-11-18 | Missing-Area Reconstruction in Multispectral Images Under a Compressive Sensing Perspective | Hyeonghobaek | (DOC) | ||
| The intent of this paper is to propose new methods for the reconstruction of areas obscured by clods. They are based on compressive sensing theory, which allows finding sparse signal representations in underdetermined linear equation systems. | ||||||
| 2 | 2013-11-25 | Power and Channel Allocation for Cooperative Relay in Cognitive Radio Networks | Muhammad asif | (DOC) | |
| In this paper authors mention that cognitive radio relay channels can be divided into three categories: direct, dual-hop, and relay channels. The relay node involves both dual-hop and relay diversity transmission. They develop power and channel allocation approaches for cooperative relay networks. They also develop a low complexity approach that can obtain most of the benefits from power and channel allocation with minor performance loss. | |||||
October 2013
| No | Date | Title | Speaker | Presentation | Discussion | |
| 1 | 2013-10-14 | The Exact support recovery of sparse signals with noise via orthogonal matching pursuit | Oliver | (DOC) | ||
| This letter derives sufficient conditions for the OMP to recover the support set of a sparse vector from noise corrupted measurements. In particular, the conditions are given in terms of the minimum absolute values of the signal amplitudes. That is, if the minimum values of the non-zero coefficient of the signal satisfies certain conditions then OMP guarantees exact support recovery. | ||||||
| 2 | 2013-10-21 | Hierarchical and High-Girth QC LDPC codes | Jeongmin Ryu | (PDF) | ||
| They present an approach to designing capacity approaching high-girth low-density parity-check (LDPC) codes that are friendly to hardware implementation, and compatible with some desired input code structure defined using a protograph. The approach is based on a mapping of any class of codes defined using a protograph into a family of hierarchical quasi- cyclic (HQC) LDPC codes. Next, they present a girth-maximizing algorithm that optimizes the degrees of freedom within the family of codes to yield a high-girth HQC LDPC code, subject to bounds imposed by the fact that HQC codes are still quasi-cyclic. Finally, they discuss how certain characteristics of a code protograph will lead to inevitable short cycles and show that these short cycles can be eliminated using a “squashing” procedure that results in a high-girth QC LDPC code. | ||||||
| 3 | 2013-10-26 | Ultra-Wideband Compressed Sensing : Channel Estimation | JuSung Kang | (DOC) | ||
| In this paper, they have introduced two novel ultra-wideband (UWB) channel estimation approaches based on compressive sensing (CS). The proposed approach relies on the fact that transmitting an ultra-short pulse through a multipath UWB channel leads to a received UWB signal that can be approximated by a linear combination of a few atoms from a pre-defined dictionary which means sparse representation of the received signal. The key in the proposed approach is in the design of a dictionary of parameterized waveforms (atoms) that closely matches the information-carrying pulse shape leading thus to higher energy compaction and sparse representation, and, therefore higher probability for CS reconstruction. In the first approach, the CS reconstruction capabilities are exploited to recover the composite pulse-multipath channel from a reduced set of random projections. This reconstructed signal is subsequently used as a referent template in a correlator-based detector. In the second approach, from a set of random projections of the received pilot signal, the Matching Pursuit algorithm is used to identify the strongest atoms in the projected signal that are related to the strongest propagation paths that composite the multipath UWB channel. | ||||||
August 2013