Collaborative Wideband Compressed Signal Detection in Interplanetary Internet

Abstract

As the development of autonomous radio in deep space network, it is possible to actualize communication between explorers, aircrafts, rovers and satellites, e.g. from different countries, adopting different signal modes. The first mission to enforce the autonomous radio is to detect signals of the explorer autonomously without disturbing the original communication. This paper develops a collaborative wideband compressed signal detection approach for InterPlaNetary (IPN) Internet where there exist sparse active signals in the deep space environment. Compressed sensing (CS) can be utilized by exploiting the sparsity of IPN Internet communication signal, whose useful frequency support occupies only a small portion of an entirely wide spectrum. An estimate of the signal spectrum can be obtained by using reconstruction algorithms. Against deep space shadowing and channel fading, multiple satellites collaboratively sense and make a final decision according to certain fusion rule to gain spatial diversity. A couple of novel discrete cosine transform (DCT) and walsh-hadamard transform (WHT) based compressed spectrum detection methods are proposed which significantly improve the performance of spectrum recovery and signal detection. Finally, extensive simulation results are presented to show the effectiveness of our proposed collaborative scheme for signal detection in IPN Internet. Compared with the conventional discrete fourier transform (DFT) based method, our DCT and WHT based methods reduce computational complexity, decrease processing time, save energy and enhance probability of detection.

Efficient distributed storage strategy based on compressed sensing for space information network

“…For convenience to the theoretical analysis and fair comparison with other strategies, each node i has a limited memory and generates one symbol x i independently every period. Then, the original data of the entire AS network can be denoted by a vector 24 x is often spatially sparse in some orthonormal basis C based on the nature of space information. Without loss of generality, we assume that the vector x is K-sparse in the canonical basis (i.e.…”

“…[18][19][20][21][22][23] As a result, both the decoding ratio and data dissemination cost are greatly reduced for the same order of erasure codes. As presented in Wang et al 24 and Huleihel et al, 25 communication signals between space nodes are also compressible due to the spatial correlation. Therefore, it is significant if the CS theory can be utilized in the SIN.…”

A Novel Approach to Wideband Spectrum Compressive Sensing Based on DST for Frequency Availability in LEO Mobile Satellite Systems

“…For cognitive power line communication (PLC) systems, [17] applied several time-frequency transforms included DFT, discrete cosine transform (DCT), and discrete sine transform (DST) to spectrum sensing. Additionally, the cooperative sensing technique has attracted considerable research attention in wideband cognitive radio networks as it is capable of significantly improving the performance of wireless communication systems [18][19][20][21][22]. To the best of our knowledge, these works are mostly concerning CR in terrestrial wireless network.…”

Wideband spectrum compressive sensing for frequency availability in LEO‐based mobile satellite systems

“…For cognitive power line communication systems, [23] applied several time-frequency transforms included DFT, discrete cosine transform (DCT), and discrete sine transform to spectrum sensing. Furthermore, the cooperative sensing technique has attracted considerable research attention in wideband cognitive radio networks as it is capable of significantly improving the performance of wireless communication systems [24][25][26][27][28]. Although authors in [28] considered DCT-based and Walsh-Hadamard transform (WHT)-based schemes for collaborative compressive wideband sensing, the analysis in this work is significantly different from that of [28].…”

“…Furthermore, the cooperative sensing technique has attracted considerable research attention in wideband cognitive radio networks as it is capable of significantly improving the performance of wireless communication systems [24][25][26][27][28]. Although authors in [28] considered DCT-based and Walsh-Hadamard transform (WHT)-based schemes for collaborative compressive wideband sensing, the analysis in this work is significantly different from that of [28]. For example, this paper theoretically proves that the representation of signal in DCT and WHT domain is much sparser than that of DFT domain, takes into account of the impaction of threshold factor on the receiver operating characteristic (ROC) performances, adopts both OR fusion rule and MAJ fusion rule at fusion center, and focuses the issue of frequency availability in the application scenarios of LEO mobile satellite system.…”