To improve test data compression efficiency, the order of the scan unit need be adjusted, which indirectly changes the content of the test pattern. Scan chain partitioning is a common method that utilises this concept. However, current scan chain partitioning methods can still be optimised in terms of entropy and test data compression efficiency, and lack universality. To enhance the efficiency of code-based compression efficiency, we propose a scan slice reordering algorithm that minimizes entropy. This algorithm first calculates the rank of each scan slice or column vector of the test set, and then dynamically adjusts the order of the scan slices according to the descending order of these ranks in the pursuit of minimizing the entropy of the test set. By iterating through this process, the optimal position of each scan slice in the test set is ultimately determined. Compression experiments should be performed on all test patterns using different code-based schemes. This not only reduces the entropy of the test set but also significantly improves the efficiency of different codes. Compared to traditional scan chain partitioning method, FDR encoding achieved an average compression ratio increase of 6.16%, and RL-Huffman encoding achieved an average compression ratio increase of 4.96%. The experimental results demonstrate that our proposed algorithm is feasible, effective, and universal.

In power conversion applications utilizing GaN HEMTs at elevated switching frequencies, the predominant source of power loss is attributed to switching, which becomes particularly sensitive to parasitic parameters due to the rapid switching operation. Traditional methods of calculating switching loss have exhibited inconsistencies when applied to designs incorporating GaN HEMTs and various operational conditions. Consequently, there is a pressing need for more precise methods to estimate switching loss in GaN HEMTs. This paper introduces two distinct switching loss calculation models, presented both as empirical formulas and analytical models. These models take into account the influence of critical parasitic inductances and junction temperature. The comparative analysis of these two calculation methods with the experimental results is provided to demonstrate their efficacy. Furthermore, the impact of nonideal factors, such as power loop parasitic inductance, common-source inductance, and junction temperature, is assessed.

In power conversion applications using GaN HEMT with high switching frequency, switching loss dominates in total power loss and could be very sensitive to parasitic parameters as a result of fast-switching operation. Since conventional switching loss calculation formula suffers from inconsistent error in designs with GaN HEMTs and various conditions, it is desirable to have effective ways for more accurate estimation on switching loss of GaN HEMT. In this paper, two different kinds of switching loss calculation model are developed in forms of both empirical formula and analytical model, taking into account the effect of critical parasitic inductances and junction temperature. The comparison results of two calculation methods with traditional calculation method are presented for the effectiveness of models. Moreover, the effect of nonideal parameters, such as power loop parasitic inductance, common-source inductance and junction temperature are evaluated.

Time-sensitive services (TSSs) have been widely envisioned for future sixth-generation (6G) wireless communication networks. Due to its inherent low-latency advantage, mobile-edge computing (MEC) will be an indispensable enabler for TSSs. The random characteristics of the delay experienced by users are key metrics reflecting the Quality of Service (QoS) of TSSs. Most existing studies on MEC have focused on the average delay. Only a few research efforts have been devoted to other random delay characteristics, such as the delay-bound violation probability and the probability distribution of the delay, by decoupling the transmission and computation processes of MEC. However, if these two processes could not be decoupled, the coupling will bring new challenges to analyze the random delay characteristics. In this article, a MEC system with a limited computation buffer at the edge server is considered. In this system, the transmission process and the computation process form a feedback loop and could not be decoupled. We formulate a discrete-time two-stage tandem queueing system. Then, by using the matrix-geometric method, we obtain the estimation methods for the random delay characteristics, including the probability distribution of the delay, the delay-bound violation probability, the average delay, and the delay standard deviation. The estimation methods are verified by simulations. The random delay characteristics are analyzed by numerical experiments, which unveil the coupling relationship between the transmission process and computation process for MEC. These results will largely facilitate the elaborate allocation of communication and computation resources to improve the QoS of TSSs.

To achieve secure group communication, one-time session keys need to be shared among group members in a secure and authenticated manner. In this paper, we propose an improved authenticated key transfer protocol based on Shamir's secret sharing. The proposed protocol achieves key confidentiality due to security of Shamir's secret sharing and provides key authentication by broadcasting a single authentication message to all members. Furthermore, the proposed scheme resists against both insider and outsider attacks.