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Device-to-Device (D2D) communication has become a promising candidate in future cellular networks to improve spectrum efficiency and energy efficiency, while reducing the latency. As the capacity of D2D user equipments (DUEs) increases, it makes DUEs caching possible, and it can offload traffic from macro base stations, perform computation-intensive and latency-critical tasks. In this paper, in-band communication is considered, and the Poisson cluster process is utilized to model and analyze the clustered D2D networks under cluster-centric caching strategy. Firstly, we use the Thomas cluster process to model cellular user equipments (CUEs) and DUEs, and give a deployment scheme of clustered D2D caching networks. Secondly, the aggregated interference of the typical D2D receiver is analyzed in the clustered D2D networks. Then the Laplace transform of the aggregated interference is analyzed, and the expressions of coverage probability, average achievable rate and cache hit probability of the typical D2D receiver are deduced. The simulation results show that we can adjust the path loss exponent, densities of DUEs and CUEs, transmitting power of CUEs, mean of simultaneously active transmitters in each cluster and Zipf exponent to improve the performance of clustered D2D caching networks.

D2D (Device-to-Device) communication has become a crucial part of 4G and 5G networks. It can not only decrease the transmit power of user equipments (UEs) and increase area spectral efficiency of cellular networks, but also offload traffic from cellular networks and alleviate scarcity of spectrum resources by using in-band communication. In this paper, we consider a real tele-communication scenario in which the mobile UEs are primarily located in hotspots and cell edges. By integrating Poisson Hole Process with Thomas Cluster Process, a kind of D2D-Aided Underlaying Cellular Networks (D2D-UCNs) is built. In the D2D-UCNs, we first investigate the aggregation interference of the typical UE and D2D user by using stochastic geometry. Subsequently we analyze their coverage probability and area spectral efficiency. The simulation results show that the coverage probability of D2D users and UEs can be effectively guaranteed by establishing exclusion zone, whilst the area spectral efficiency of the D2D-UCNs can be maximized by optimizing the number of simultaneously active D2D links.

Along with the surge in mobile data, dense small cell network has become an effective method to improve system capacity and spectrum efficiency. However, because more small cells are deployed, the interference among dense small cells exacerbates. It also makes frequent handover for mobile users (UEs), which brings a great deal of signaling overhead to the core network. In order to solve the problems of interference and frequent handover, a novel clustering scheme for dense small cell network is proposed in this paper. The scheme is based on the weighted graph. First, we present a dense small cell clustering model based on X2 interface to minimize core network signaling overhead. To improve the usability of the model, we model the system as an undirected weighted graph. Then we propose the maximum benefit merging algorithm to reduce the complexity. This method enables adjacent small cells to cooperate and form virtual cellular cluster according to handover statistics information. Then we select cluster head (CH) according to certain rule in each cluster. Cluster head acts as the mobility anchor, managing the handovers between cluster members. This can reduce core network signaling overhead and the interference among small cells effectively. Compared with the 3GPP handover algorithm, the proposed clustering model in this paper can reduce the signaling overhead more than 70%. The simulation results show that the proposed clustering model can effectively cluster the dense small cell.

With the development of large-scale integrated circuits and Internet, 5G has become the hot topic of current mobile communication. Device-to-device communication (D2D) is one of the key technologies of 5G. In this paper, considering the in-band communication, we use the Poisson cluster process (PCP) to model and analyze the heterogeneous cellular and D2D networks. Firstly, we use the Thomas cluster process to model cellular users and D2D users. Secondly, we analyze the aggregated interference of the typical D2D receiver in the heterogeneous cellular and D2D networks. Then we analyze the Laplace transform of the aggregated interference and deduce the coverage probability of the typical D2D receiver. Simulation results show that the path loss exponent and D2D users' distribution density have significant influence on the performance of heterogeneous cellular and D2D networks. Compared with the grid model and PPP model, PCP model can realize the performance optimization of the clustered D2D networks.

The cellular networks in 5G are tending to be heterogeneous and ultra-dense networks. The methods used in traditional hexagonal grid model are no more adaptive to the 5G heterogeneous cellular networks today, which are too idealized and inaccurate. A popular approach for analyzing heterogeneous cellular networks is using Poisson point process (PPP), which assumes that the deployment of base stations (BSs) is completely space random (CSR) and from which we can get a lower bound of the probability of coverage probability. However, geographical and human factors should be taken into account in reality. The BSs or mobile users may be clustered in crowded areas such as enterprises and shopping malls so that the space distribution based on PPP will be inaccurate. This motivates us to find a new approach to settle it. In this paper, we focus on using Poisson clustered process (PCP) to model ultra-dense 5G heterogeneous cellular networks which include macrocells, picocells and femtocells. First of all, a model of the locations of BSs based on Poisson clustered process (PCP) has been proposed, and the formation of clusters of the BSs has been discussed. Then the probability model of coverage and its three special cases using SINR have been derived, and the proposed model obeys to the cell selection mechanism based on instantaneous SINR. Finally, according to the proposed model, comparison and analysis of coverage probability using hexagonal grid model, PCP and PPP are done respectively. The numerical results show that using PCP can get higher coverage probability than using PPP.

In recent years, with the rapid development of deep learning, pedestrian detection have brought great vitality. Convolution Neural Network (CNN) can be used for pedestrian detection to improve the detection performance, but the CNN model needs a lot of parameters and has high computational complexity. In order to settle these problems, the cascade pedestrian detection model based on Local Decorrelation Channel Features (LDCF) and CNN is proposed in this paper. In the first stage, the LDCF is used to obtain the pedestrian candidate window, and it can reduce the redundancy of the image, decrease the computation complexion of CNN. In the second stage, the output results of LDCF as the input of the CNN model, then CNN model is trained and an LDCF+CNN cascade detector is obtained by cascading the LDCF detector with the CNN model. The experimental results show that the log-average miss rate of LDCF+CNN algorithm is lower than that of LDCF algorithm alone, and the miss rate is below 13.21%.

With the development of large scale integrated circuits and Internet technology, 5G has become the hotspot of current domestic and international mobile communication research. Device-to-device communication (D2D) is one of the key technologies of 5G. It enables direct communication between proximate devices, thereby improving the overall spectrum utilization and offloading traffic of cellular networks. In this paper, we use the stochastic geometry and the Poisson cluster process to analyze the uplink of the cellular networks. Firstly, we treat the location of BSs as distributed points according to a homogeneous Poisson point process (PPP), and use the Thomas cluster process to model cellular users and D2D users. Secondly, we take the fact into consideration that the performance of the cellular networks may be different in diverse path loss exponent, node densities, and transmit power. Then, we consider the cellular and D2D heterogeneous Networks, investigate the coverage probability, average achievable rate for such networks, and we compare the performance of the heterogeneous networks when D2D users are included and otherwise. Finally, we quantify the best and worst case performance of the heterogeneous networks in terms of coverage probability.

In this paper, a new construction of optical zero correlation zone (OZCZ) code set pair is proposed for quasi-synchronous code division multiple access (QS-CDMA) visible light communication (VLC) system. Owing to its excellent correlation properties within zero correlation zone and greater code weight, the multi-user QS-CDMA-VLC system using the proposed code construction can obtain both good performance in illumination and communication. An experimental QS-CDMA-VLC system with two optical channels and two experiment setups is designed to evaluate the performance of the new OZCZ code set pair. When the free-space transmission distance difference is 1 m, we successfully achieve the 2-user and 14-user CDMA-VLC for 32.5 Mb/s and 24.1 Mb/s overall bit rate respectively, under the 7% forward-error-correction (FEC) limit of 3.8×10 -3. The experimental results indicate that, comparing to the other existing optical code sets, the proposed OZCZ construction can effectively reduce the impact of non-perfect synchronous problem, so that the bit error rate (BER) performance is improved. And dimming values and overall bit rates of the system can be significantly improved.