In this paper, we propose frequency allocation and path selection scheme in underlay cognitive radio (CR) networks using network coding. In the proposed scheme, we choose the path with consideration of network coding and interference temperature in underlay CR networks and propose an optimization problem to maximize the system throughput of secondary users (SUs). Then, we represent the proposed optimization problem as the multi-dimensional multiple-choice knapsack problem and give the theoretical upper bound for the system throughput of SUs by using linear programming. Finally, we compute the system throughput of SUs by using brute-force search (BFS) and link quality first (LQF) scheme in underlay CR networks. Simulation results show that the system throughput of SUs with BFS is higher than that with LQF in underlay CR networks with and without application of network coding, respectively.

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In this paper, we propose joint resource allocation and path selection schemes for OFDMA relay networks with application of network coding. We formulate the proposed schemes in both time-division duplexing (TDD) and frequencydivision duplexing (FDD)-based OFDMA relay networks. Then the problems can be transformed into the multi-dimensional multiple-choice knapsack problem (MMKP) so that they maximize the total system throughput for both downlink and uplink flows. We evaluate our schemes through simulation, comparing to link quality-based (LQB) schemes. The simulation results show that the proposed schemes provide higher total system throughput than LQB schemes with and without application of network coding, respectively, and in each scheme, network coding-based systems provide higher total system throughput than non-network coding-based systems.

Entropy is a measure of disorder or uncertainty. This terminology is qualitatively used in the understanding of its correlation to pollution in the environmental area. In this research, three different entropies were defined and characterized in order to quantify the qualitative entropy previously used in the environmental science. We are dealing with newly defined distinct entropies E1, E2, and E3 originated from Shannon entropy in the information theory, reflecting concentration of three major green house gases CO2, N2O and CH4 represented as the probability variables. First, E1 is to evaluate the total amount of entropy from concentration difference of each green house gas with respect to three periods, due to industrial revolution, post-industrial revolution, and information revolution, respectively. Next, E2 is to evaluate the entropy reflecting the increasing of the logarithm base along with the accumulated time unit. Lastly, E3 is to evaluate the entropy with a fixed logarithm base by 2 depending on the time. Analytical results are as follows. E1 shows the degree of prediction reliability with respect to variation of green house gases. As E1 increased, the concentration variation becomes stabilized, so that it follows from linear correlation. E2 is a valid indicator for the mutual comparison of those green house gases. Although E3 locally varies within specific periods, it eventually follows a logarithmic curve like a similar pattern observed in thermodynamic entropy.

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