Because of extreme sensitivity to time and energy consumption, many computation-and data-intensive tasks are difficult to implement on mobile terminals and cannot meet the needs of the rapid development of mobile networks. To solve this problem, mobile edge computing (MEC) appears to be a promising solution. In this study, we propose two offloading schemes in the multiple unmanned aerial vehicles (UAVs) enabled MEC network. Their optimisation goals are to minimise the global computing time and energy consumption of all UAVs, respectively. Different from previous research, the UAV can perform tasks locally or offload an appropriate percentage to the desired MEC server in the two proposed schemes. In order to get the minimum global computing time, we prove the existence condition and obtain the optimal offloading proportion. In addition, in order to minimise global energy consumption, we also obtain the optimal offloading proportion and present the optimal transmission power through solving Karush-Kuhn-Tucker conditions. Finally, because UAVs are selfish, we adopt the game theory to get optimal solutions of the proposed offloading strategies. Numerical results verify that the proposed schemes can effectively decrease the global computing time and energy consumption, especially for a large number of UAVs.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

SUMMARY Increasing the transmitting power will improve the system performance, but it will also increase the potential intercepted risk. Thus, the research of security‐reliability trade‐off (SRT) is valuable. In this paper, we investigate the physical layer security in cognitive radio network (CRN), which consists of a source node, a destination node, an eavesdropper, and multiple relays. The security and reliability are measured by intercept probability (IP) and outage probability (OP), respectively. Different from the previous researches, a more actual scenario is studied for the CRN in the Rayleigh fading environment; that is, the eavesdropper can eavesdrop on the secondary source (SS) and the relays. Besides, we consider the probability of false alarm and missing alarm and study their impact on the OP and IP for direct transmission (DT) and relay selective transmission (RST). The closed‐form expressions of OP and IP show that the false alarm affects the OP and the missing alarm has influence on the OP and IP. Furthermore, we accumulate the sum of the OPs for the RST in the two time slots and compare them with the DT, when we explore the OP. In addition, since the signals may be both intercepted in the two stages of RST, we analyze the IPs in the two time slots respectively and compare them with the DT separately. The simulation results show that the RST scheme can greatly improve the security and reliability by increasing the number of relays compared with the DT scheme.

An efficient number estimation method is proposed for target detection by using the forward-backward matrix pencil method. Compared with the traditional parameter estimation methods, the proposed method can work well even for sparse signals. At first, the radar cross section of the group targets arranged in linear array is obtained at some certain angles or frequencies. Then, the Hankel-Toeplitz matrix is constructed from the known radar echoes, and the singular value decomposition is performed on this matrix. Finally, the number of the group targets arranged in linear array can be accurately estimated by setting an appropriate threshold to select the singular value with a large proportion. In addition, the influence of different signal-to-noise ratios (SNR) on the estimation results is also discussed. In order to enhance the accuracy, several groups of different echoes are used to estimate the number of group targets jointly. The simulation results demonstrate that the proposed method is effective and accurate in estimating the number of group targets arranged in linear array. Moreover, the estimation result of the proposed method in this paper is not affected by the noise, which shows that this method has better robustness.

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