A modeling framework for supporting and evaluating connectivity in cognitive radio ad hoc networks with beamforming

LT Dung, B An - Wireless Networks, 2017 - Springer
LT Dung, B An
Wireless Networks, 2017Springer
In this paper, we present an analytical modeling framework for supporting and evaluating
the impact of shadowing and beamforming on the topological connectivity of cognitive radio
ad-hoc networks (CRAHNs) where primary users (PUs) are equipped with omnidirectional
antennas while secondary users (SUs) are equipped with directional antennas such as
uniform linear array (ULA) antenna and uniform circular array (UCA) antenna. The main
features and contributions in this paper are as follows. First, we derive a formula for …
Abstract
In this paper, we present an analytical modeling framework for supporting and evaluating the impact of shadowing and beamforming on the topological connectivity of cognitive radio ad-hoc networks (CRAHNs) where primary users (PUs) are equipped with omnidirectional antennas while secondary users (SUs) are equipped with directional antennas such as uniform linear array (ULA) antenna and uniform circular array (UCA) antenna. The main features and contributions in this paper are as follows. First, we derive a formula for calculating effective coverage area of a node in secondary network by taking the effect of path loss, antenna model, and beamforming scheme into consideration. Second, we mathematically analyze the expected number of neighbors and communication probability of a SU based on the effective coverage area of SU and the spatial–temporal existence of PU’s operation. We also derive the expression of the upper bound of path connectivity between two arbitrary SUs in the networks. Third, we point out that UCA antenna is the most suitable antenna for CRAHNs. We find the optimal number of elements corresponding to each type of directional antenna at which the highest connectivity can be achieved. The validity of our analysis is verified by comparing with simulations. The results in this paper provide efficient guidelines for system designers to characterize and optimize the connectivity of CRAHNs with beamforming.
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