A novel multi-phase charge-sharing technique is proposed for the dot-inversion method to reduce AC power consumption of the TFT-LCD column driver without requiring any external capacitor for charge conservation. Simple and easy-to-control circuitry is applied in the proposed method, and the power saving efficiency depends on number of charge phases. Increasing the number of charge phases, the saving power efficiency is also raised. Excluding power dissipation of switches, the power saving efficiency is up to 75% theoretically with infinite phases. For previous work, the maximum power saving efficient is 50% without external capacitor. The HSPICE simulation results including power dissipation of all switches show that the proposed method with seven charge phases (eight-column lines as one group) decreases the power consumption of 23-68% and 10-18%, respectively, compared with original circuit (without any low-power scheme) and previous low-power charge-recycling works.

To achieve scalability and security, large networks are often structured hierarchically as a collection of domains. In hierarchical networks, the topology and QoS parameters of a domain have to be first aggregated before being propagated to other domains. However, topology aggregation may distort useful information. Although spanning tree aggregation can perfectly encode attribute information of symmetric networks, it can not be applied to asymmetric networks directly. In this paper, we propose a spanning tree based attribute aggregation method for asymmetric networks. The time complexity of the proposed method and the space complexity of its resulted aggregated topology are the same with that of the spanning tree aggregation method in symmetric networks. This method can guarantee that the attributes of more than half of the links in the networks are unaltered after aggregation. Simulation results show that the proposed method achieves the best tradeoff between information accuracy and space complexity among the existing asymmetric attribute aggregation methods.

Channel estimation using data-dependent superimposed training (DDST) is developed to doubly selective channels of Orthogonal Frequency Division Multiplexing (OFDM) systems; it consumes no extra bandwidth. An Inter-carrier interference (ICI) Self-cancelation method based on DDST scheme, IS-DDST, is designed which mitigates the interference from adjacent subcarriers to estimation. Moreover, a dual-iteration detection method is proposed to mitigate the ICI for IS-DDST scheme. Theoretical analysis and simulations show that the proposed scheme can achieve better Mean Square Error (MSE) and Bit Error Ratio (BER) performance than the existing DDST based scheme.