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• A nonparametric variable step-size normalized least-mean-square (VSS-NLMS) algorithm is proposed, where the step-size adjustment rule is derived by exploiting the traditional NLMS weight update equation. • The step-size adjustment rules employ the square root of the estimated error power and the system noise power. • Detailed transient-state and steady-state analyses are presented and suggest that the steady-state performance of the proposed algorithm is independent of the smoothing parameter. This paper presents a new and effective nonparametric variable step-size normalized least-mean-square (VSS-NLMS) algorithm which provides excellent performance in various signal-to-noise ratio (SNR) scenarios. The step-size update expressions are based on steady-state step-size which derives from the filter weight update equations. Specifically, the step-size adjustment rules employ the square root of the estimated error power and the system noise power to enhance the effectiveness of the proposed algorithm. Detailed transient-state and steady-state analyses are presented for the Gaussian white input signal and suggest that the steady-state performance of the proposed algorithm is independent of the smoothing parameter (used in the step-size update expressions). In addition, performance comparisons between the proposed algorithm and other well-known VSS-NLMS algorithms show the improvements of the proposed algorithm. Furthermore, theoretical analyses and simulated behaviors of the proposed algorithm are in good agreement for both transient-state and steady-state. Through simulation results, the irrelevance between the steady-state performance and the smoothing parameter is verified. [ABSTRACT FROM AUTHOR]

Due to the wide spread of 5G networks, network users have higher requirements for communication delays. Software-defined network is a new paradigm of decoupling the control logic from packet forwarding devices. We can reduce communication latency in the network by optimizing the location of the controller and improve the communication performance of the network. In this paper, the controller deployment problem of multi-network area is studied in order to reduce the average communication latency. In order to solve this problem, we proposed an optimized DPC algorithm. Specifically, on the basis of DPC algorithm we quoted the idea of triangular stability from the BeeDPC algorithm, and introduced SC measurement indicators, the degree of separation between sub-network regions and the degree of aggregation within the sub-network region, so as to divide the network region more reasonably. At the same time, we have break out of the constraints in the DPC algorithm and introduced closeness centrality to get a more reasonable placement scheme and reduced the limitations of the DPC algorithm. Simulation results have shown that the optimized DPC algorithm can effectively reduce the average delay between the control layer and the data layer, improve the network performance, and enhance network stability and reliability. [ABSTRACT FROM AUTHOR]