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In a wireless network, node failure due to either natural disasters or human intervention can cause network partitioning and other communication problems. For this reason, a wireless network should be fault tolerant. At present, most researchers use k-connectivity to measure fault tolerance, which requires the network to be connected after the failure of any up to k-1 nodes. However, wireless network node failures are usually spatially related, and particularly in military applications, nodes from the same limited area can fail together. As a metric of fault-tolerance, k-connectivity fails to capture the spatial relativity of faults and hardly satisfies the fault tolerance requirements of a wireless network design. In this paper, a new metric of fault-tolerance, termed D-region fault tolerance, is introduced to measure wireless network fault tolerance. A D-region fault tolerant network means that even after all the nodes have failed in a circular region with diameter D, it still remains connected. Based on D-region fault tolerance, we propose two fault-tolerant topology control algorithms—the global region fault tolerance algorithm (GRFT) and the localized region fault tolerance algorithm (LRFT). It is theoretically proven that both algorithms are able to generate a network with D-region fault tolerance. Simulation results indicate that with the same fault tolerance capabilities, networks based on both GRFT and LRFT algorithms have a lower transmission radius and lower logical degree.In a wireless network, node failure due to either natural disasters or human intervention can cause network partitioning and other communication problems. For this reason, a wireless network should be fault tolerant. At present, most researchers use k-connectivity to measure fault tolerance, which requires the network to be connected after the failure of any up to k-1 nodes. However, wireless network node failures are usually spatially related, and particularly in military applications, nodes from the same limited area can fail together. As a metric of fault-tolerance, k-connectivity fails to capture the spatial relativity of faults and hardly satisfies the fault tolerance requirements of a wireless network design. In this paper, a new metric of fault-tolerance, termed D-region fault tolerance, is introduced to measure wireless network fault tolerance. A D-region fault tolerant network means that even after all the nodes have failed in a circular region with diameter D, it still remains connected. Based on D-region fault tolerance, we propose two fault-tolerant topology control algorithms—the global region fault tolerance algorithm (GRFT) and the localized region fault tolerance algorithm (LRFT). It is theoretically proven that both algorithms are able to generate a network with D-region fault tolerance. Simulation results indicate that with the same fault tolerance capabilities, networks based on both GRFT and LRFT algorithms have a lower transmission radius and lower logical degree.

Abstract: Weak key analysis is a key issue in the design of chaotic ciphers. While most of the existing research focusing on the degradation of the chaotic sequences which causes weak keys, we point out that the parameters for which the chaotic sequences do not degrade are still possible to be weak keys. In this paper, we propose a new approach based on the rigorous statistical test to improve the weak key analysis. The weak keys of a specific chaotic cipher are investigated by using our method and a large number of new weak keys are detected. These results verify that our method is more effective. On the other hand, although statistical tests are now widely adopted to test the chaos-based bit sequences, there are few reports of analysis results on the weak keys or weak sequences of chaotic cipher. Thus our work may be helpful for current research on statistical tests of chaotic cipher.

Aggregate mobility modelling, studying macroscopic rule of human movement, benefits the performance of mobility management. This paper is primarily focused on establishing an architecture based on field theory, using scalar and vector field to describe traffic and mobility, respectively. On the basis of their temporal–spatial evolution, we try to discover the relationship between traffic field and mobility field. This field architecture fits for mobility management in large temporal–spatial scale, since it not only benefits qualitative analysis of traffic and mobility in the perspective of field, but also provides a theoretical foundation and insight for issues in mobile communication.

In this paper, we consider cognitive radar security in the presence of interceptors. By designing waveform, the cognitive radar will spread its most power to match the target channel for estimation and remove the spectrum that matches the interception channel for security. We firstly propose the signal model of a typical scenario, and then use the mutual information criterion to guide waveform design. By solving a convex optimization problem, we can obtain a globally optimal waveform. This paper also presents numerical examples to verify effectiveness of the idea and the approaches.

The effect of carrier frequency offset on the performance of BLAST-OFDM systems is presented. Analysis shows that system performance degrades as frequency offset and channel state information estimation interval increase. Numerical simulations confirm this conclusion. A pilot channel is recommended for synchronisation and phase-shift adjustment.

We realize the spatiotemporal chaotic synchronization in globally coupled Henon map lattices (HMLs) by using discrete variable structure control scheme. The proposed approach is robust against parameter mismatch of the system and is advantageous for engineering realization. Numerical simulations demonstrate the feasibility and robustness of the proposed control strategy. [Copyright &y& Elsevier]

Abstract: The construction of cryptographically strong substitution boxes (S-boxes) is an important concern in designing secure cryptosystems. The key-dependent S-boxes designed using chaotic maps have received increasing attention in recent years. However, the key space of such S-boxes does not seem to be sufficiently large due to the limited parameter range of discretized chaotic maps. In this paper, we propose a new key-dependent S-box based on the iteration of continuous chaotic maps. We explore the continuous-valued state space of chaotic systems, and devise the discrete mapping between the input and the output of the S-box. A key-dependent S-box is constructed with the logistic map in this paper. We show that its key space could be much larger than the current key-dependent chaotic S-boxes. [Copyright &y& Elsevier]