A guided tour of Chernoff bounds
Information Processing Letters
Mobility increases the capacity of ad hoc wireless networks
IEEE/ACM Transactions on Networking (TON)
Capacity of a wireless ad hoc network with infrastructure
Proceedings of the 8th ACM international symposium on Mobile ad hoc networking and computing
Multicast capacity of wireless ad hoc networks
IEEE/ACM Transactions on Networking (TON)
Capacity scaling in ad hoc networks with heterogeneous mobile nodes: the super-critical regime
IEEE/ACM Transactions on Networking (TON)
A note on the secrecy capacity of the multiple-antenna wiretap channel
IEEE Transactions on Information Theory
Achieving single channel, full duplex wireless communication
Proceedings of the sixteenth annual international conference on Mobile computing and networking
Security-capacity trade-off in large wireless networks using keyless secrecy
Proceedings of the eleventh ACM international symposium on Mobile ad hoc networking and computing
Secure transmission with multiple antennas: part II: the MIMOME wiretap channel
IEEE Transactions on Information Theory
Multicast Throughput for Hybrid Wireless Networks under Gaussian Channel Model
IEEE Transactions on Mobile Computing
On the price of security in large-scale wireless ad hoc networks
IEEE/ACM Transactions on Networking (TON)
Delay and capacity tradeoff analysis for motioncast
IEEE/ACM Transactions on Networking (TON)
Guaranteeing Secrecy using Artificial Noise
IEEE Transactions on Wireless Communications
Closing the gap in the multicast capacity of hybrid wireless networks
Proceedings of the thirteenth ACM international symposium on Mobile Ad Hoc Networking and Computing
The capacity of wireless networks
IEEE Transactions on Information Theory
Broadcast channels with confidential messages
IEEE Transactions on Information Theory
Capacity and delay tradeoffs for ad hoc mobile networks
IEEE Transactions on Information Theory
Degenerate delay-capacity tradeoffs in ad-hoc networks with Brownian mobility
IEEE Transactions on Information Theory
Closing the Gap in the Capacity of Wireless Networks Via Percolation Theory
IEEE Transactions on Information Theory
Throughput and Delay in Random Wireless Networks With Restricted Mobility
IEEE Transactions on Information Theory
Hierarchical Cooperation Achieves Optimal Capacity Scaling in Ad Hoc Networks
IEEE Transactions on Information Theory
Wireless Information-Theoretic Security
IEEE Transactions on Information Theory
Secrecy Throughput of MANETs Under Passive and Active Attacks
IEEE Transactions on Information Theory
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Since wireless channel is vulnerable to eavesdroppers, the secrecy during message delivery is a major concern in many applications such as commercial, governmental, and military networks. This paper investigates information-theoretic secrecy in large-scale networks and studies how capacity is affected by the secrecy constraint where the locations and channel state information (CSI) of eavesdroppers are both unknown. We consider two scenarios: 1) noncolluding case where eavesdroppers can only decode messages individually; and 2) colluding case where eavesdroppers can collude to decode a message. For the noncolluding case, we show that the network secrecy capacity is not affected in order-sense by the presence of eavesdroppers. For the colluding case, the per-node secrecy capacity of $\Theta({1 \over \sqrt{n}})$ can be achieved when the eavesdropper density $\psi_e(n)$ is $O(n^{-\beta})$ , for any constant $\beta 0$ and decreases monotonously as the density of eavesdroppers increases. The upper bounds on network secrecy capacity are derived for both cases and shown to be achievable by our scheme when $\psi_e(n)=O(n^{-\beta})$ or $\psi_e(n)=\Omega(\log^{\alpha-2 \over \alpha}n)$, where $\alpha$ is the path-loss gain. We show that there is a clear tradeoff between the security constraints and the achievable capacity. Furthermore, we also investigate the impact of secrecy constraint on the capacity of dense network, the impact of active attacks and other traffic patterns, as well as mobility models in the context.