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CUSUM algorithm is one of the core methods which is commonly used in early prediction of events both at home and abroad. It has been shown in many years of practice that the forecasting method is too simple and the timeliness of the analysis is not ideal. In this paper, the improved EW_CUSUM algorithm came into being. First, calculate the amount of expected data under different baseline windows according to the amount of historical data generated. Then, calculate the baseline level based on the expected data amount. Finally, add the prediction statistics under two baselines. The required forecasting statistics will be helpful to figure out the high incidence of the situations. This paper validates the effectiveness of this method in commodity sales forecasting by using this method. This method has successfully improved the ability of forecasting events, advanced the time of the forecast and enhanced the timeliness of forecasting.

This paper focuses on the energy efficiency of cognitive relay (CR) networks with cooperative sensing, joint optimization of the sensing time and the signal-to-noise ratio (SNR) is studied to maximize the energy efficiency of CR network. Theoretical analysis shows that there exists an optimal sensing time and optimal SNR to make the energy efficiency maximized under a constraint of detection probability. Simulation results illustrate that the optimal fusion rule performs better than the OR rule and the AND rule in terms of the energy efficiency. By properly designing the fusion rule threshold as well as the number of cooperative sensing users, the energy efficiency of CR networks can be further improved.

This paper deals with the sum-rate performance in the broadcasting channel of a decentralized multiuser multi-antenna system. With the assumption of limited channel state information available at the base station and a large number of single antenna decentralized users in a cell, we propose a Semi-orthogonal precoding method with a total feedback rate constraint, and analyze its the sum-rate performance. A lower bound to the sum-rate of broadcast channels with quantized channel direction information and channel quality information is obtained. It can be used to evaluate the performance of broadcast channels with finite-rate feedback of channel state information and semi-orthogonal user selection. Numerical examples show that our analytical results agree with Monte Carlo simulations.

This paper deals with the blocking performance of a dynamic channel allocation (DCA) algorithm in different cellular topologies, and points out that the performance is not only related to the DCA algorithm itself, but also to the cellular topology where it is applied. By Monte Carlo simulation, this relationship between DCA algorithm and cellular topology is obtained, which can be used for cellular mobile communication network design.

The problem of dynamic channel allocation (DCA) in cellular networks is discussed. We draw the conclusion that the system performance improvement by DCA is due to the fact that DCA increases the trunking efficiency and a simple but useful method is developed to calculate the lower limit of the call blocking probability of DCA. By using this method, we can compare the performance of fixed channel allocation (FCA) with any kind of DCA schemes easily and clearly. We also discuss the performance of DCA in different occasions.

In this paper, we investigate the energy efficiency and throughput optimization problem of cognitive relay networks. We propose to design sensing time and signal to noise ratio (SNR) to maximize the energy efficiency and throughput, since analytical and empirical studies have shown that sensing time and SNR are key factors for energy efficiency and throughput. We design a method that simultaneously considers the parameters of spectrum sensing time and SNR to optimize the energy efficiency of cognitive radio networks. Furthermore, we conduct deep experiments which show that there exists the optimal sensing time to maximize energy efficiency and throughput. In addition, optimal sensing time and optimal SNR can be jointly designed to maximize energy efficiency. Finally, we provide simulation results to show that energy efficiency of cognitive relay transmission scheme can be significantly improved compared with that of direct transmission scheme in cognitive radio networks.