In this paper, we present a WiFi-based intrusion detection system called Wi-Alarm. Motivated by our observations and analysis that raw channel state information (CSI) of WiFi is sensitive enough to monitor human motion, Wi-Alarm omits data preprocessing. The mean and variance of the amplitudes of raw CSI data are used for feature extraction. Then, a support vector machine (SVM) algorithm is applied to determine detection results. We prototype Wi-Alarm on commercial WiFi devices and evaluate it in a typical indoor scenario. Results show that Wi-Alarm reduces much computational expense without losing accuracy and robustness. Moreover, different influence factors are also discussed in this paper.

Key generation and distribution is a fundamental problem of communication security. To avoid the potential risk due to static key, a physical-layer dynamic key generation and encryption scheme is proposed for orthogonal frequency division multiplexing passive optical network (OFDM-PON) systems. By exploiting the inherent channel randomness, the shared secret key between the OLT and ONU is generated and renewed periodically, thereby effectively improving the security against malicious attacks. The transmission experiment of 3.5 Gb/s 16-quardrature-amplitued-modulatin encrypted OFDM data is successfully demonstrated over a 25 km standard single-mode fiber. The key space of the proposed encryption scheme reaches 10 ⁶⁶ , which provides privacy between users and protection against eavesdropping.

Ultra-dense networks (UDN) have been considered as one of the best ways to improve the network throughput and energy efficiency (EE). However, massive and unplanned deployment of small cells will cause severe intra-tier interference among small cells and then deteriorate the network EE. For this, a Cluster-based Energy-Efficient Resource Management (CEERM) scheme is proposed to mitigate the interference while guaranteeing the quality of service (QoS) of user equipments (UEs) in this paper. Firstly, we propose a cell clustering algorithm to divide small cells into disjoint cell clusters according to the neighboring relationship. Then, the UEs in each cell cluster are further grouped into UE groups with the target of minimizing intra-cluster interference. Finally, a two-step subchannel allocation and non-cooperative game based power allocation scheme is proposed to maximize the network EE. The simulation results show that the proposed scheme CEERM can effectively boost the network EE with low computation complexity.

This paper analyzes the convergence of iterative learning control for a class of discrete-time systems over networks with successive input data compensation. Specifically, the successively dropped input data in current iterations are compensated by the one actuator received correctly with the same time instant label in the latest iteration. Through analyzing the variation of elements in the transition matrices of the input errors at the controller side, the convergence of output errors is addressed. The analysis shows the selection range of learning gain is determined by the maximum number of input data dropped successively. Moreover, the convergence of system with successive input data compensation is guaranteed by trading the convergence speed, and the more input data are successively compensated in iteration domain, the more convergence speed of the system is reduced. Finally, numerical experiments are given to corroborate the theoretical analysis.

Heterogeneous networks, constituted by conventional macro cells and overlaying pico cells, have been deemed a promising paradigm to support the deluge of data traffic with higher spectral efficiency and Energy Efficiency (EE). In order to deploy pico cells in reality, the density of Pico Base Stations (PBSs) and the pico Cell Range Expansion (CRE) are two important factors for the network spectral efficiency as well as EE improvement. However, associated with the range and density evolution, the inter-tier interference within the heterogeneous architecture will be challenging, and the time domain Enhanced Inter-cell Interference Coordination (eICIC) technique becomes necessary. Aiming to improve the network EE, the above factors are jointly considered in this paper. More specifically, we first derive the closed-form expression of the network EE as a function of the density of PBSs and pico CRE bias based on stochastic geometry theory, followed by a linear search algorithm to optimize the pico CRE bias and PBS density, respectively. Moreover, in order to realize the pico CRE bias and PBS density joint optimization, a heuristic algorithm is proposed to achieve the network EE maximization. Numerical simulations show that our proposed pico CRE bias and PBS density joint optimization algorithm can improve the network EE significantly with low computational complexity.

With the development of the Internet of Things, FMCW (Frequency Modulated Continuous Wave) radars are widely used in medical treatment, human behavior detection, Internet of Vehicles and UAV (Unmanned Aerial Vehicle) detection. However, the existing systems have some shortcomings, such as high requirements for synchronization signal, lack of flexibility and high design cost. In this paper, to address these problems, a software-synchronization based, flexible, low-cost FMCW radar is proposed. Firstly, the radar uses periodic intermittent slope signal as modulation signal, and analyze echo signal to detect a target with a software synchronization algorithm. Most interestingly, hardware synchronization signal is not needed in the proposed radar as in conventional designs, which greatly facilitate implementation. Secondly, the radar system has a high flexibility due to the use of a software waveform generator and a software data processor. The system is built without expensive integrated chips and equipment, which greatly reduces the design cost. Finally, two groups of experiments under different environments are designed. Through the analysis of the results, it can be seen that the radar system designed in this paper achieves a good accuracy while greatly reduces the design cost and complexity.