Beijing University of Posts and Telecommunications

About: Beijing University of Posts and Telecommunications is a education organization based out in Beijing, Beijing, China. It is known for research contribution in the topics: MIMO & Quality of service. The organization has 39576 authors who have published 41525 publications receiving 403759 citations. The organization is also known as: BUPT.

Beamforming and Power Splitting Designs for AN-Aided Secure Multi-User MIMO SWIPT Systems

Abstract: In this paper, an energy harvesting scheme for a multi-user multiple-input-multiple-output secrecy channel with artificial noise (AN) transmission is investigated. Joint optimization of the transmit beamforming matrix, the AN covariance matrix, and the power splitting ratio is conducted to minimize the transmit power under the target secrecy rate, the total transmit power, and the harvested energy constraints. The original problem is shown to be non-convex, which is tackled by a two-layer decomposition approach. The inner layer problem is solved through semi-definite relaxation, and the outer problem, on the other hand, is shown to be a single-variable optimization that can be solved by 1-D line search. To reduce computational complexity, a sequential parametric convex approximation method is proposed to find a near-optimal solution. This paper is then extended to the imperfect channel state information case with norm-bounded channel errors. Furthermore, tightness of the relaxation for the proposed schemes is validated by showing that the optimal solution of the relaxed problem is rank-one. Simulation results demonstrate that the proposed SPCA method achieves the same performance as the scheme based on 1-D but with much lower complexity.

Distributed Consensus Control for Second-Order Agents with Fixed Topology and Time-Delay

Abstract: In this paper, distributed consensus control is investigated for networks of agents with double integrator dynamics. Two kinds of networks are analyzed, i.e., directed networks with fixed topology and undirected networks with fixed topology and time-delay. For each of the networks, a sufficient and necessary condition is given to guarantee the consensus. It is proved that the largest tolerable time-delay is only related to the largest eigenvalue of the graph Laplacian. Finally, two numerical examples are provided to illustrate the obtained results.

Dense-Coding Attack on Three-Party Quantum Key Distribution Protocols

Abstract: Cryptanalysis is an important branch in the study of cryptography, including both the classical cryptography and the quantum one. In this paper we analyze the security of two three-party quantum key distribution protocols (QKDPs) proposed recently, and point out that they are susceptible to a simple and effective attack, i.e., the dense-coding attack. It is shown that the eavesdropper Eve can totally obtain the session key by sending entangled qubits as the fake signal to Alice and performing collective measurements after Alice's encoding. The attack process is just like a dense-coding communication between Eve and Alice, where a special measurement basis is employed. Furthermore, this attack does not introduce any errors to the transmitted information and consequently will not be discovered by Alice and Bob. The attack strategy is described in detail and a proof for its correctness is given. Finally, the root cause of this insecurity and a possible way to improve these protocols are discussed.

A new monarch butterfly optimization with an improved crossover operator

Abstract: Recently, by examining and simulating the migration behavior of monarch butterflies in nature, Wang et al. proposed a new swarm intelligence-based metaheuristic algorithm, called monarch butterfly optimization (MBO), for addressing various global optimization tasks. The effectiveness of MBO was verified by benchmark evaluation on an array of unimodal and multimodal test functions in comparison with the five state-of-the-art metaheuristic algorithms on most benchmarks. However, MBO failed to come up with satisfactory performance (Std values and mean fitness) on some benchmarks. In order to overcome this, a new version of MBO algorithm, incorporating crossover operator is presented in this paper. A variant of the original MBO, the proposed one is essentially a self-adaptive crossover (SAC) operator. A kind of greedy strategy is also utilized. It ensures that only the better monarch butterfly individuals, satisfying a certain criterion, are allowed to pass to the next generation, instead of all the updated monarch butterfly individuals, as was done in the basic MBO. In other words, the proposed methodology is essentially a new version of the original MBO, supplemented with Greedy strategy and self-adaptive Crossover operator (GCMBO). In GCMBO, the SAC operator can significantly improve the diversity of population during the later run phase of the search. In butterfly adjusting operator, the greedy strategy is used to select only those monarch butterfly individuals, possessing improved fitness and hence can aid towards accelerating convergence. Finally, the proposed GCMBO method is benchmarked by twenty-five standard unimodal and multimodal test functions. The results clearly demonstrate the capability of GCMBO in significantly outperforming the basic MBO method for almost all the test cases. The MATLAB code used in the paper can be found in the website: http://www.mathworks.com/matlabcentral/fileexchange/55339-gcmbo .