Browsing by Author "Perera, S. S"

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Embargo
Carrier frequency offset estimation for OFDM system using extended kalman filter
(IEEE, 2008-12-12) Senevirathna, S. B; Jayawardena, C; Perera, S. S; Perera, C. L; Ranasignhe, D; Wijerathna, S. R; Bandara, T. N
The ability of Orthogonal Frequency Division Multiplexing (OFDM) systems to achieve higher data rates and facilitate bandwidth friendly communication is impaired by the presence of Carrier Frequency Offset (CFO) in the OFDM communication system. CFO can be caused by Doppler frequency shift, or by the differences of the transmitter and the receiver local oscillator frequencies. We propose a new method for CFO estimation for (OFDM) communication systems, with experimental proof which was gathered in the process of real world data transmission using the OFDM communication system in a simulation environment (MATLAB).
Open Access
Topological structure of manufacturing industry supply chain networks
(Hindawi, 2018-10-03) Perera, S. S; Bell, M. G. H; Piraveenan, M; Kasthurirathna, D; Parhi, M
Empirical analyses of supply chain networks (SCNs) in extant literature have been rare due to scarcity of data. As a result, theoretical research have relied on arbitrary growth models to generate network topologies supposedly representative of real-world SCNs. Our study is aimed at filling the above gap by systematically analysing a set of manufacturing sector SCNs to establish their topological characteristics. In particular, we compare the differences in topologies of undirected contractual relationships (UCR) and directed material flow (DMF) SCNs. The DMF SCNs are different from the typical UCR SCNs since they are characterised by a strictly tiered and an acyclic structure which does not permit clustering. Additionally, we investigate the SCNs for any self-organized topological features. We find that most SCNs indicate disassortative mixing and power law distribution in terms of interfirm connections. Furthermore, compared to randomised ensembles, self-organized topological features were evident in some SCNs in the form of either overrepresented regimes of moderate betweenness firms or underrepresented regimes of low betweenness firms. Finally, we introduce a simple and intuitive method for estimating the robustness of DMF SCNs, considering the loss of demand due to firm disruptions. Our work could be used as a benchmark for any future analyses of SCNs.