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This paper proposes a novel technique to detect the main moving trajectory of indoor pedestrians. Based on Long Short- Term Memory(LSTM) Network, this deep learning network is capable of learning the trajectory of human beings using indoor Wi-Fi positioning data. The data is collected by Wi-Fi detectors densely installed in a public building in the urban area, which can ensure the detection of any portable devices as long as the Wi-Fi module is turned on. Then the model works in the form of sequence modeling to learn the trajectory of the main stream extracted from massive pedestrian positioning data. In compare with methods like Recurrent Neural Network (RNN) and Gated Recurrent Unit(GRU), there is an obvious performance improvement of this method.

This paper proposes an explicit adaptive algorithm to solve the problem of heterogeneous dynamic synchronization of multi-agent uncertain systems. Different from the existing works, the proposed algorithm depends on less control parameters and achieves zero synchronization error between the agents of heterogeneous uncertain dynamic networks and virtual target. By introducing appropriate assumptions, a class of explicit adaptive synchronization protocols is designed based on a combination of the virtual target's states, distributed feedback gain, and the limited neighboring agents' information. By using Lyapunov function approach, it is proved that the explicit adaptive synchronization problem of closed-loop multi-agent uncertain systems with heterogeneous dynamic networks can be solved, if the control parameters of the explicit adaptive synchronization algorithm are suitably selected. Finally, an example is given to demonstrate the proposed theory.

Acquisition is a key technology in DSSS system. The differential correlation is usually employed to eliminate the effect of frequency deviation. However, as the length of pseudo-code grows and the decrease of the SNR, the traditional differential acquisition algorithms will result in great loss of SNR. This paper presents an improved differential acquisition method, named as M-orders Auto-Correlation based on Differential correlation (MAC-DF). In the proposed method, the input signal is multiplied by the complex conjugate of the pseudo-code to eliminate its effect. After that, the product is applied to the M-orders Auto-Correlation to compensate the SNR loss caused by the differential process. By means of mathematical model to analyze its acquisition performance. We compare MAC-DF acquisition algorithm with the differential coherent and non-coherent acquisition algorithms through simulation. The simulation results indicate that this algorithm is approximately 5–6dB superior to the traditional differential acquisition algorithms in improving acquisition sensitivity and more adaptive to work under low SNR.

In this paper, the energy efficiency (EE) of distributed antenna system (DAS) with multiple receive antennas is investigated over composite fading channel that takes the path loss, shadow fading and Rayleigh fading into account. Our aim is to maximize EE which is defined as the ratio of the transmission rate to the total consumed power under the constraints of maximum transmit power of each remote antenna. According to the definition of EE and using the upper bound of average EE, the optimized objective function is provided. Based on this, utilizing Karush-Kuhn-Tucker (KKT) conditions and mathematical derivation, a suboptimal energy efficient power allocation (PA) scheme is developed, and closed-form expression of PA coefficients is achieved. The developed scheme can obtain the EE close to the existing optimal scheme due to better approximation, especially for larger receive antenna number. Moreover, it has lower calculation complexity than the existing optimal scheme because only the statistic channel information is needed. Simulation results verify the effectiveness of the developed scheme.

In this paper, a new direction of arrival (DOA) estimation method is proposed based on the sparse presentation of array covariance matrix of a difference co-array, which is obtained by exploiting fourth order cumulants. The DOAs are estimated by finding the sparsest solution in a redundant basis. We also give a theoretical guidance to select the regularization parameter. Since fourth order cumulants are used, our method can not only detect more sources than sensors but also can suppress spatially colored noise. Besides, our method achieves higher resolution compared with existing methods. Simulation results are given to demonstrate the effectiveness and excellent performance of the proposed method.

The blasting spot monitoring is very important to reduce the occurrence of emergencies and to protect the workers' safety in practical applications. In this paper, we design an early warning system based on WSN (Wireless Sensor Network) which can be used in explosion operations. This system consists of two parts: the hardware part mainly uses several sensors to capture data we need and transmits them to the monitor center through wireless module; the software part mainly receives and processes the captured data, then analyzes the parameters to judge whether the environment parameters are abnormal, if yes, it will alarm in advance to protect the workers. Experiment results show that this system can alarm correctly when the environment parameters are out of limit, which improves the system's reliability and gets some social economic benefits in the meantime. This system does have a grand application prospect.

With the increasing pollution of lake water environment and frequent outbreaks of blue-green algae, it is very significant to establish one kind of distributed real-time monitoring network on all typical locations of the lake. In this way, the pollution of lake water environment can be effectively controlled. Nowadays, the stability of data reporting and how to maximize the use of limited power are the biggest problems to the design of real-time monitoring networks. In this paper, according to characteristics of lake monitoring, the design of lake water quality detection system based on wireless sensor network is presented. Key technologies and issues were discussed in the paper based on lake monitoring sensor network topology design, network protocol design and node hardware and software design. Also the application of lake water quality detection system in the Taihu lake was discussed.

In this paper, we propose a multiple CFOs(Carrier Frequency Offset) estimation and mitigation algorithm for the destination node in a cooperative OFDM(Orthogonal Frequency Division Multiplex) system. In a cooperative OFDM system, every relay node has a separate local oscillator, so that each relay-to-destination link has individual CFO parameter, so that the traditional estimation and mitigation algorithms are no longer applicable. In the proposed algorithm, based on the specially designed training sequences, the destination node can decouple the signal from different relay nodes by correlation and simplify the MD(Multi-Dimensional) nonlinear problem to an ID linear problem. Then, an mitigation matrix can be constructed, and the ICI(Inter-Carrier-Interference) caused by multiple CFOs can be perfectly compensated based on the over sampled OFDM symbol vectors. Theoretical analysis and simulation results prove that the proposed algorithm is effective in estimating the multiple CFOs and mitigating the performance degradation.

This paper presents a simple single-carrier (SC) distributed space-time block coded transmission scheme for asynchronous cooperative communications over frequency-selective channels. The cyclic prefix (CP) at the source node and relay nodes is used to combat inter-symbol interference from multi-path fading and the timing errors from the relay nodes. In this scheme, the relay nodes only implement very simple operations on their received signals to construct distributed space-time block code, and decoding, DFT and IDFT operations are only needed at the destination node. The low complexity SC zero-forcing frequency domain equalization (ZF-FDE) is applied at the destination node to recover the transmitted signals. The analysis and simulation results demonstrate that this simple SC scheme can achieve order-two spatial diversity gain for amplify-and-forward based cooperative communication over frequency-selective channels in the presence of asynchronization between relay nodes.