Vehicles travelling as platoons can reduce the huge traffic jams on the highway. Platoon members can share vehicle information such as speed and acceleration via vehicular ad hoc networks (VANETs) communication to maintain a constant inter-vehicle and inter-platoon distances. However, connectivity is a fundamental measurement to indicate the linking quality of VANETs. This paper analyzes the access and connectivity probability between the vehicles and the road side units (RSUs) of the multi-way platoon-based VANETs with roadside infrastructure. We denote the connectivity probability as the probability that the vehicles on the highway can access to at least one RSU besides the road within a designated number of hops. Moreover, besides considering the connection on the same road, we study the connection between the vehicles and the RSU via vehicles on the nearby neighbor roads. The analytical results have been validated by simulations and results show that the connectivity probability can be improved when there are platoons in a network. Meanwhile, the connectivity probability is higher in the multi-way vehicle-to-infrastructure (V2I) communication network than that in a one-way V2I communication network. The results in this paper can help to reduce the jams on the highway and achieve intelligent driving. Then the safety and comfort of the drivers and passengers on the highway can be improved. Moreover, these results can provide forceful theoretical support to the future intelligent transportation system (ITS) design.

It is necessary to estimate channel quality in order to put Bluetooth adaptive packet selection strategies into practice. However, the current Bluetooth channel quality estimation algorithms are either poor at timeliness or not applicable to systems which only support basic rate data?packets (Gaussian Frequency Shift Keying modulation scheme). It is investigated to apply the channel quality estimation algorithm based on power spectrum to Bluetooth adaptive packet selection strategies in this paper. Simulation results and analysis show that the proposed channel quality estimation algorithm based on power spectrum can achieve the accuracy less than 0.2 dB?in the estimation range required by Bluetooth adaptive packet selection strategies. It has simple calculation and strong timeliness. The algorithm can also be suitable for different modulation schemes of Bluetooth data packets. It provides a good precondition for the achievement of Bluetooth adaptive packet selection strategies.

This paper proposes a low-cost hardware architecture based on concurrent dual-band digital pre-distorter (DPD). The architecture is implemented on field programmable gate array (FPGA) to compensate for the nonlinearity of the concurrent dual-band power amplifier (PA). This implementation introduces a novel model complexity reduction technique into system, namely, time-division multiplexing for out-of-band lookup tables (LUTs) sharing. Performances are evaluated with an experimental test setup using a wideband class-F PA. The dual-band signal center frequency separated by 80 MHz. Lower and upper center frequency are located at 2.61 GHz and 2.69 GHz, respectively. This novel DPD implementation maintains excellent performance, but uses hardware resources reduced by 29.17% compared with conventional approaches. The results show that the adjacent channel power ratio (ACPR) is less than 59 dBc and normalized mean square error (NMSE) is around 62dB for lower sideband (LSB) and 63dB for upper sideband (USB).

In combination of the characteristic of the network architecture of wireless multimedia sensor networks (WMSNs), a distributed multi-node cooperative network model called DMCN is designed by using the concept of in-network processing to improve their energy, memory and computational power. To balance the energy consumption of the network, according to roles division, camera nodes and common nodes are cooperated to accomplish the workload of image acquisition, compression and transmission. Camera nodes gather images and send blocking images to the common nodes in cluster. Common nodes adaptively compress the partitioned images by using a noise-tolerant distributed image compression algorithm based on principal component analysis (PCA) called NDIC-PCA and send the compressed data to the cluster head node. Then, the cluster head node sends the compressed image data to the station. Simulation results demonstrate that, DCNM can effectively balance the energy consumption of network and largely extend the network lifecycle. In addition, compared with previous algorithms, the proposed NDIC-PCA algorithm achieves higher peak signal to noise ratio without decreasing compression ratio.

The co-site interference exists in kinds of communication systems, especially in digital communication systems, also is one of the biggest threats in electromagnetic compatibility (EMC) designation of the systems. Analyzing the co-site interference is an important process in achieving EMC performance of the system. Under the situation, the co-site interference simulation analysis of a vehicular digital communication system based on interference margin (IM) prediction method by bit error ratio (BER) was proposed in the paper. In the simulation analysis, some physical models of the vehicular communication system were established on SIMULINK environment, the upper limit of BER level for audio signals was defined as the interference margin, three different types of co-site interference was analyzed respectively, and the simulation results were obtained in the form of system interference bandwidth. From these results, the EMC performance evaluation of the vehicular communication system was predicted based on the IM prediction method. By comparing with the actual test results, the correctness of the simulation results was validated and the simulation analysis method can be used for reference by other communication systems was indicated.

Anderson-Darling (AD) sensing, Characteristic Function (CF) sensing and Order Statistic (OS) sensing are three common spectrum sensing methods based on goodness of fit (GOF). However, AD and OS sensing needs the prior information of noise variance; CF and OS sensing have high computation complexity. To circumvent those difficulties, in this paper, the ratio of the mean square to variance (RM2V) of the samples, after deriving its probability density function (PDF), is employed as a test statistic to detect the availability of the vacant spectrum in the cognitive radio system. Then a blind spectrum sensing method based on RM2V is proposed, which is dubbed as RM2V sensing, and its exact theoretical threshold is obtained via the derived PDF of RM2V. The performance of RM2V sensing is evaluated by theoretical analysis and Monte Carlo simulations. Comparing with the conventional energy detection, AD, CF and OS sensing, RM2V sensing, with no need of noise variance, has advantages from the aspect of computation complexity and detection performance.

Most of the existing routing protocols for heterogeneous multi-hop wireless networks use the on-demand routing protocols owing to its suitability for dynamic topology environments, but it will easily lead to a waste of network resources because of the large number of data packets being broadcast. What’s more, some nodes of heterogeneous multi-hop wireless networks may be malicious nodes or selfish nodes which can easily lead to a link attack, so the routing security issues are also important for heterogeneous multi-hop wireless networks. Thus, how to build a secure routing protocol with a lower overhead for heterogeneous multi-hop wireless networks is a challenge. This paper propose a novel routing protocol called TSRAL for heterogeneous multi-hop wireless networks, which combines the location information of nodes and trust value to select the next forwarding node. Simulation results show that TSRAL can reduce the number of data packets being broadcast and the number of hops during routing and it can also ensure the safety of the route.

In this paper, the influence of sampling intervals on the chattering in sliding mode (SM) control systems is considered. The describing function (DF) approach is employed to analyze the chattering characteristics in the sampling SM control. By the DF calculations and limit cycle existence conditions, an unstable limit cycle and two stable limit cycles are found in the SM control system. The frequencies and amplitudes of the two limit cycles can also be estimated by graphical calculations. The estimation accuracy of chattering parameters is evaluated by the simulations. The results of simulations show that the system could converge to a large and a small limit cycle from different initial conditions.

The process of urbanization is formed by regular movements of human beings. It yields different functional zones in a city, such as residential zone and commercial zone. Consequently, there exists a close connection between the human mobility pattern and the city’s zones. However, it is not easy to collect large-scale society-wide data that can precisely capture the underlying relations between the individual’s movement and the regional functions. Hence, our knowledge for understanding the basic patterns of human mobility is still limited. In order to discover the functions of different regions in a city, we propose an affinity based method in this paper. The affinity is a recently introduced metric for measuring the correlation of two connecting node in a complex network. The proposed model groups different functional zones by measuring user’s arrival/departure distribution via relative entropy. In addition to this, we also identify the intensity of each functional zone by taking kernel density estimation method. In the end, some experiments are conducted to evaluate our method with a large-scale real-life dataset, which consists of 3 million cellphone users’ records from a period of one month. Our findings on the interaction between the mobility pattern and the regional functions can capture the city dynamics efficiently and provide a valuable reference for urban planners.

In order to solve the non-smooth feature of support vector machine model and improve its classification performance further, a novel smooth function based on the geometry of circle tangent is constructed to smooth the non-differentiable term of support vector machine(SVM), and it proposes a circle tangent smooth support vector machine (CTSSVM). Theoretical analysis proves the global convergence of CTSSVM. Comparing to other smooth approaching functions, its smooth precision has an obvious improvement. Numerical experiments and comparisons demonstrate the efficiency of our scheme is better than other smooth models in terms of classification performance.

An dynamic system for real-time obstacle avoidance path planning of redundant robots is constructed in this paper. Firstly, the inter-frame difference method is used to identify the moving target and to calculate the target area, then on the basis of color features and gradient features extracted from the target area, the feature fusion Cam-Shift mean shift algorithm is used to track target, improving the robustness of the tracking algorithm. Secondly, a parallel two-channel target identification and location method based on binocular vision is proposed, updating the target’s three-dimensional information in real time. Then, a dynamic collision-free path planning method is implemented: the safety rods are removed through the intersection test, and the minimum distance is derived directly by using the coordinate values of the target in the local coordinate system of the rod. On this basis, the obstacle avoidance gain and escape velocity related to the minimum distance is established, and obstacle avoidance path planning is implemented by using the zero space mapping matrix of redundant robot. Experiments are performed to study the efficiency of the proposed system.

A novel design of high-efficiency broadband power amplifier (BPA) with the low-pass bias network to enhance the efficiency and output power is presented in this paper. This letter presents an approach to enhance the efficiency and output power of a broadband power amplifier (BPA) by using a low-pass filter as the bias network. Compared with other bias networks, the proposed low-pass bias network shows a smaller baseband impedance, which can reduce the electrical memory effect. While it provides a larger radio frequency (RF) impedance, which can prevent the leakage of the output power from bias network. A BPA with the proposed bias network is designed using commercial GaN device Cree40025F. The designed BPA shows a fractional bandwidth of 40%, from 1.8GHz to 2.7GHz. The measured results exhibit 73.9 % drain efficiency (DE) value with output power of 43.5 dBm at 2.7GHz, which appears an enhancement of 9.5% and 2.5dBm comparing with that adopts LC bias network.