M
Mohammad Yousefvand
Researcher at Rutgers University
Publications - 20
Citations - 114
Mohammad Yousefvand is an academic researcher from Rutgers University. The author has contributed to research in topics: Computer science & Service provider. The author has an hindex of 4, co-authored 17 publications receiving 75 citations. Previous affiliations of Mohammad Yousefvand include Amirkabir University of Technology & New Jersey Institute of Technology.
Papers
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Journal ArticleDOI
Maximizing Network Capacity of Cognitive Radio Networks by Capacity-Aware Spectrum Allocation
TL;DR: This paper proposes a new radix tree based algorithm that, by removing the sparse areas in the search space, leads to a considerable decrease in time complexity of solving the spectrum allocation problem as compared to the BILP algorithm.
Journal ArticleDOI
Distributed Energy-Spectrum Trading in Green Cognitive Radio Cellular Networks
TL;DR: This paper proposes a new energy spectrum trading model to enhance the energy as well as spectrum efficiency of cellular networks and designs an efficient distributed auction model including green energy aware bidding (GEAB) and adaptive bid selection (ABS) algorithms, to achieve a good approximation of the optimal solution in less time.
Journal ArticleDOI
Novel Approach to Sub-graph Selection over Coded Wireless Networks with QoS Constraints
TL;DR: Simulation results demonstrate that using of column-generation approach in combination with network coding to solve this problem can enhance the efficiency of final solution, no matter of the size of underlying network.
Journal ArticleDOI
Out-of-the-classroom learning of English vocabulary by EFL learners: investigating the effectiveness of mobile assisted learning with digital flashcards
TL;DR: In this article , the authors investigated the contribution of a digital flashcard application (i.e., NGSL builder) designed for smartphone devices in out-of-the-classroom learning of essential vocabulary in English among EFL learners.
Proceedings ArticleDOI
Interference-constraint spectrum allocation model for cognitive radio networks
TL;DR: Simulation results have shown that the capacity-aware proposed model leads to a considerable improvement in overall network capacity as compared with other solutions, and it was showed that maximizing the number of active links between SUs as an objective function does not necessarily maximize network capacity.