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Trusted content delivery in large-scale SIC-enabled wireless networks
- Trusted content delivery in large-scale SIC-enabled wireless networks
- Cui, Ying; Jiang, Dongdong; Xing, Jifang; Lee, Je Min
- DGIST Authors
- Lee, Je Min
- Issue Date
- 18th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2017, 1-6
- In this paper, we consider trusted content delivery in a large-scale SIC-enabled wireless network in the presence of trust degree information. The trust degree of a node quantifies a degree of its trustworthiness, and we model the network with multiple tiers based on the trust degrees of nodes. To improve the successful receive probability of an authentic file, we adopt a simple but effective serving node selection rule based on maximum long-term biased-received-power (BRP), and a decoding method based on successive interference cancellation (SIC). First, by utilizing tools from stochastic geometry, we derive a tractable expression and a closed-form expression for the successful receive probability, in the general and small (file transmission) rate regimes, respectively. The analytical results indicate that the advantage of SIC in the general rate regime increases with the number of interferers that can be cancelled and the dominant advantage of SIC in the small rate regime can be achieved by cancelling the nearest interferer only. Then, we maximize the successful receive probability by choosing the optimal bias factor for each trust tier in the general and small rate regimes, respectively. By exploring structural properties, in the general rate regime, we obtain a locally optimal solution of the challenging optimization problem with a non-convex and non-differentiable objective function using the gradient projection method, and in the small rate regime, we obtain a closed-form globally optimal solution. The asymptotic optimization result indicates that obtaining the desired file from the nearest node in the most trusted tier achieves the maximum successful receive probability. © 2017 IEEE.
- Institute of Electrical and Electronics Engineers Inc.
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- Department of Information and Communication EngineeringISC(Information Security and Communication) Lab2. Conference Papers
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