Spectrum-based Distributed Clustering and Proximate Device Discovery in Wireless Networks

碩士 === 國立交通大學 === 電信工程研究所 === 102 === Direct short range device-to-device (D2D) communication enjoys many a advantage with respect to conventional cellular systems: high transmission rates, lower propagation delays, reduced transmit power and interference level. Moreover, direct D2D links offload tr...

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Bibliographic Details
Main Authors: Lin, Chih-Yu, 林志宇
Other Authors: Su, Yu-Ted
Format: Others
Language:en_US
Published: 2013
Online Access:http://ndltd.ncl.edu.tw/handle/29268978744494042600
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Summary:碩士 === 國立交通大學 === 電信工程研究所 === 102 === Direct short range device-to-device (D2D) communication enjoys many a advantage with respect to conventional cellular systems: high transmission rates, lower propagation delays, reduced transmit power and interference level. Moreover, direct D2D links offload traffics from existing macro-cellular networks (MCN) and support emergency communications when the core network fails. To realize the above-mentioned advantages, a device or user equipment (UE) must be able to discover other devices or UEs in the proximity and establish links with them. The purpose of this thesis is to present feasible and efficient distributed solution to these two critical issues for a D2D communication system underlaying an MCN. We propose a clustering scheme which generating a probing frequency-hopped (FH) sequence based on the device’s sensed spectrum. Such scheme is based on the presumption that devices in close proximity would observe similar spectrums. Hence if they can exchange the spectrum information the devices with similar spectra should lie in the same neighborhood and be grouped into the same cluster. Our scheme includes a novel spectrum compressing method that not only compresses the spectrum information but converts it into a FH probing sequence with embedded automatically-generated cluster ID to discover if there exit devices in the neighborhood. The main idea is to model the sensed spectrum, which is represented by a real vector denoting the spectral heights at the subcarriers of interest, as a corrupted nonbinary codeword so that similar spectra are different noise-corrupted versions of the same codeword while dissimilar spectra are originated from different codewords. As Reed-Solomon (RS) codes are maximum distance separable (MDS), they are perfect candidate code to model the sensed spectra and to resolve dissimilar spectra. We first quantize the spectrum vector into an M-ary vector and decode it into a legitimate systematic RS codeword. The non-binary RS codeword is then randomly cyclic-shifted and used to generate an FH sequence with the information symbols as the cluster (neighborhood) ID. Such a design allows multiple simultaneous probing and clustering with minimum collision. It also naturally fits into an interference avoiding adaptive spread spectrum transmission scheme. We verify the feasibility and efficiency of our solution through computer simulations, assuming that devices and MCN UEs are located according to mutually independent Poisson point processes (PPP) with different densities.