Universiti Teknologi Malaysia Institutional Repository

Coded Collaborative Spectrum Sensing With Joint Channel Decoding and Decision Fusion

Azmi, Marwan Hadri and Leib, Harry (2015) Coded Collaborative Spectrum Sensing With Joint Channel Decoding and Decision Fusion. IEEE Transactions On Wireless Communications, 14 (4). pp. 2017-2031. ISSN 1536-1276

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Official URL: http://dx.doi.org/10.1109/TWC.2014.2378789

Abstract

This paper considers the integration of channel decoding with fusion based decision, for coded collaborative spectrum sensing (CSS) employing local Neyman-Pearson (NP) testing at each sensor. We derive a belief-propagation (BP) algorithm for joint channel decoding and decision fusion (JCDDF), based on a factor graph model for coded CSS schemes. Using the Lloyd-Max method, we also propose a new methodology for the local sensor to quantize its observation. The design of the quantizer embeds the binary NP test outcome in the quantization bits. Using the JCDDF algorithm, we show that coded CSS paired even with a short (8,4) extended Hamming code outperforms not only uncoded CSS, but also schemes where channel decoding and decision fusion are executed separately. Then, we consider the design of good channel codes for such CSS schemes. We demonstrate that the JCDDF algorithm employing unequal error protection (UEP) coding improves performance and outperforms equal error protection coding. Furthermore, we present a simple code search algorithm for identifying short UEP codes. Using such UEP codes, we finally show that a performance improvement over uncoded CSS can be attained also without bandwidth expansion using higher order modulations.

Item Type:Article
Uncontrolled Keywords:belief propagation, cognitive radio, Lloyd-Max quantization, Neyman-Pearson test, Spectrum sensing, unequal error protection
Subjects:A General Works
ID Code:58074
Deposited By: Haliza Zainal
Deposited On:04 Dec 2016 12:07
Last Modified:01 Mar 2017 09:08

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