A novel algorithm for source location by utilizing the time-difference-of-arrival (TDOA) of a signal received at spatially separated sensors is proposed. The algorithm is based on the constrained total least-squares (CTLS) technique and gives an explicit solution. Simulation results demonstrate that the proposed algorithm has high location accuracy and its performance is close to the Cramer-Rao lower bound (CRLB).

We analyze the connectivity of simulation ad hoc networks, which use random mobility models. Based on the theorem of minimum degree, the study of connectivity probability is converted into an analysis of the probability of minimum node degree. Detailed numerical analyses are performed for three mobility models: random waypoint model, random direction model, and random walk model. For each model, the connectivity probability is calculated and its relations with the communication range r and the node number n are illustrated. Results of the analyses show that with the same network settings, the connectivity performance decreases in the following order: random walk model, random direction model, and random waypoint model. This is because of the non-uniform node distribution in the last two models. Our work can be used by researchers to choose, modify, or apply a reasonable mobility model for network simulations.

Location of a source is of considerable interest in wireless sensor networks, and it can be estimated from passive measurements of the arrival times. A novel algorithm for source location by utilizing the time of arrival (TOA) measurements of a signal received at spatially separated sensors is proposed. The algorithm is based on total least-squares (TLS) method, which is a generalized least-squares method to solve an overdetermined set of equations whose coefficients are noisy, and gives an explicit solution. Comparisons of performance with standard least-squares method are made, and Monte Carlo simulations are performed. Simulation results indicate that the proposed TLS algorithm gives better results than LS algorithm.

The latest versatile video coding (VVC) introduces some novel techniques such as quadtree with nested multi-type tree (QTMT), multiple transform selection (MTS) and multiple reference line (MRL). These tools improve compression efficiency compared with the previous standard H.265/HEVC, but they suffer from very high computational complexity. One of the most time-consuming parts of VVC intra coding is the coding tree unit (CTU) structure decision. In this paper, we propose a low-complexity multi-type tree (MT) pruning method for VVC intra coding. This method consists of lookahead search and MT pruning. The lookahead search process is performed to derive the approximate rate-distortion (RD) cost of each MT node at depth 2 or 3. Subsequently, the improbable MT nodes are pruned by different strategies under different cost errors. These strategies are designed according to the priority of the node. Experimental results show that the overall proposed algorithm can achieve 47.15% time saving with only 0.93% Bjøntegaard delta bit rate (BDBR) increase over natural scene sequences, and 45.39% time saving with 1.55% BDBR increase over screen content sequences, compared with the VVC reference software VTM 10.0. Such results demonstrate that our method achieves a good trade-off between computational complexity and compression quality compared to recent methods.