Preprint Article Version 1 This version is not peer-reviewed

Applying Case-Based Reasoning to Tactical Cognitive Sensor Networks for Dynamic Frequency Allocation

Version 1 : Received: 13 October 2018 / Approved: 15 October 2018 / Online: 15 October 2018 (09:42:58 CEST)

A peer-reviewed article of this Preprint also exists.

Park, J.H.; Lee, W.C.; Choi, J.P.; Choi, J.W.; Um, S.B. Applying Case-Based Reasoning to Tactical Cognitive Sensor Networks for Dynamic Frequency Allocation. Sensors 2018, 18, 4294. Park, J.H.; Lee, W.C.; Choi, J.P.; Choi, J.W.; Um, S.B. Applying Case-Based Reasoning to Tactical Cognitive Sensor Networks for Dynamic Frequency Allocation. Sensors 2018, 18, 4294.

Journal reference: Sensors 2018, 18, 4294
DOI: 10.3390/s18124294

Abstract

This paper proposes a cognitive radio engine platform for making exploitation of available frequency channels usable for a tactical wireless sensor network in presence of incumbent communication devices known as the primary user (PU) required to be protected from undesired harmful interference. In the field of tactical communication networks, it is desperate to find available frequencies for opportunistic and dynamic access to channels in which PU is in active. This paper introduces a cognitive engine plaform for determining available channels on the basis of case-based reasoning technique deployable as core functionality on cognitive radio engine to enable dynamic spectrum access (DSA) with high fidelity. Towards this, this paper introduces a plausible learning engine to characterize channel usage pattern to extract best channel candiates for the tactical cognitive radio node (TCRN). Performance of the proposed cognitive engine is verified by conducting simulation tests which confirm the reliability in functional aspect of the proposed cognitive engine covering the learning engine as well as the case-based reasoning engine with showing how well TCRN can avoid the collision against the PU operation considered as the etiquette secondary user (SU) should have.

Subject Areas

tactical cognitive radio sensor network; case-based reasoning; cognitive radio engine; channel occupancy probability; military tactical communications

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