With the ever-growing demands of communication quality and rate, the combination of terrestrial networks and space networks is becoming the next recognized solution. The space-ground integrated network (SGIN) is a massive Internet of Things (IoT) network that accommodates large amounts of mobile terminals. The interactivity of information between those terminals will request higher communication rates and lead to more frequent handovers, which will increase the network burden and degrade the user's experience, especially in ultra-dense Low-Earth Orbit (LEO) satellite networks. In this article, a modified matching algorithm is proposed to get the optimal association matrix between users and base stations. Based on the results, the sum rate of users and the handover rate are calculated. A modified particle swarm optimization (MPSO) method is also proposed to generate the special-shaped beams on the satellites to deal with the complex optimization problems. By combining the MPSO-based beamforming algorithm and the modified matching algorithm, the non-convex sum-rate optimization problem is decomposed into two optimal subproblems, which are solved separately. The simulation results demonstrate that the SGIN significantly outperforms the non-integrated ones in terms of the sum data rate and backhaul capacity. The handover performance under the user mobility model is also discussed.

With the ever-growing communication demands and the unceasing miniaturization of mobile devices, the Internet of Things is expanding the amount of mobile terminals to an enormous level. To deal with such numbers of communication data, plenty of base stations (BSs) need to be deployed. However, denser deployments of heterogeneous networks (HetNets) lead to more frequent handovers, which could increase network burden and degrade the users experience, especially in traffic hotspot areas. In this article, we develop a unified framework to investigate the handover performance of wireless networks with traffic hotspots. Using the stochastic geometry, we derive the theoretical expressions of average distances and handover metrics in HetNets, where the correlations between users and BSs in hotspots are captured. Specifically, the distributions of macro cells are modeled as independent Poisson point processes (PPPs), and the two tiers of small cells outside and inside the hotspots are modeled as PPP and Poisson cluster process (PCP) separately. A modified random waypoint (MRWP) model is also proposed to eliminate the density wave phenomenon in traditional models and to increase the accuracy of handover decision. By combining the PCP and MRWP model, the distributions of distances from a typical terminal to the BSs in different tiers are derived. Afterward, we derive the expressions of average distances from a typical terminal to different BSs and reveal that the handover rate, handover failure rate, and ping-pong rate are deduced as the functions of BS density, scattering variance of clustered small cell, user velocity, and threshold of triggered time. Simulation results verify the accuracy of the proposed analytical model and closed-form theoretical expressions.

Terminal positioning using a single low earth orbit (LEO) communication satellite is an important means to compensate for the loss of positioning capability under global navigation satellite system (GNSS) denial. Traditional single-satellite positioning relies on the accumulative measurement over a segment of the trajectory, resulting in a long response time. In this paper, we propose a novel single-satellite positioning scheme, achieving instant positioning through the joint use of time-frequency Doppler analysis of signals and communication beam switching. First, through wide beam reception, range and velocity information are extracted using interpolation enhanced parameter estimation to determine candidate coordinates. To eliminate ambiguity in this process, further disambiguation is achieved through the high directivity of the narrow beam. The proposed scheme is proved to reach the Cramér-Rao lower bound (CRLB) while achieving real-time positioning with the central limit theorem (CLT). Simulation results indicate that at a signal-to-noise ratio (SNR) of 17 dB, the probability of positioning error being lower than 50 meters can reach 97.5%, demonstrating performance comparable to existing schemes.

In order to meet the tremendous requirements on the convergence between broadband and broadcast, this paper proposes to incorporate layered division multiplexing (LDM), an important variant of non-orthogonal multiple access (NOMA) technologies, into Millimeter wave (mmWave) multiple-input multiple-output (MIMO) system with device-to-device (D2D) communications to simultaneously provide broadcast and unicast services. The performance of the proposed full-duplex D2D-aided mmWave MIMO-NOMA with randomly deployed users is then analyzed under practical assumptions. Closed-form expressions of both the outage probability and the ergodic capacity are then derived by using the Laplace transform technique. Finally, detailed numerical results reveal the performance gains of the proposed scheme compared with the LDM without D2D communications and conventional time division multiplexing based scheme. The impacts of the antenna array gain and the transmission power of both the base station and the full-duplex link on system performance are also presented. Besides, we observe that it is vital to optimal the transmission power of the full-duplex link which ensures less self-interference to enhance the system capacity.

Orthogonal Frequency Division Multiplexing (OFDM) technique is obtained significant attention in radar applications for its interference resilience property. In this paper, Fractional Fourier Transformation (FRFT) and phase analysis techniques are proposed to enhance ranging accuracy of an OFDM Radar. A proof-of-concept radar is built and tested at 79 GHz and a range accuracy of 20 m at 5 MHz measurement rate was measured. The range accuracy is 500 times higher than using fast Fourier transformation (FFT) method.

Enabling nonorthogonal multiple access (NOMA) in device-to-device (D2D) communications under the millimeter wave (mmWave) multiple-input multiple-output (MIMO) cellular network is of critical importance for 5G wireless systems to support low latency, high reliability, and high throughput radio access. In this paper, the closed-form expressions for the outage probability and the ergodic capacity in downlink MIMO-NOMA mmWave cellular network with D2D communications are considered, which indicates that NOMA outperforms TDMA. The influencing factors of performance, such as transmission power and antenna number, are also analyzed. It is found that higher transmission power and more antennas in the base station can decrease the outage probability and enhance the ergodic capacity of NOMA.