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In this paper, we investigate the problem of angle of arrival (AOA) tracking for the large-scale array in terahertz (THz) communication, which has a large size and a narrow beam, highly demanding an accurate angle estimation. On the one hand, the system usually adopts a hybrid structure with limited radio-frequency (RF) chains, which increases the difficulty of angle estimation; on the other hand, the rapid mobility of users also brings new challenges to angle estimation. To address the above challenges, a two-stage tracking framework is proposed in this paper, which employs the random phase matrix and orthogonal long pilots in the first stage to reduce the complicated multi-user estimation to multiple single-user estimations, followed by using both wide and narrow beams in the second stage to serve high-speed and low-speed users. Furthermore, a generalized-approximated-message-passing (GAMP) method is proposed for facilitating a low-accuracy estimation of the angles, followed by adopting a modified expectation-maximization (EM) algorithm based phase estimation to unbiased estimate the instantaneous angle with the help of high-gain characteristics of the beams. The proposed structure can not only simplify the estimation complexity, but also improve the estimation accuracy due to its capability of transferring the non-linear problem of angle observation into a linear gaussian model. In addition, the Kalman tracking framework is employed for performing a continuous angle tracking. Numerical results show that the angle estimation based on the random phase matrix in the initial stage can obtain a high enough estimation accuracy, while the GAMP algorithm implemented in the second stage can quickly capture the angle range under the Rayleigh limit. The performance of the proposed EM-based tracking method is shown to outperform the traditional extended Kalman filter (EKF) method.

The cooperation of multiple Unmanned Aerial Vehicles (UAVs) has become a promising scenario in Space-Air-Ground Integrated Networks (SA-GINs) recently due to their widespread applications, where wireless communication is a basic necessity and is normally categorized into control and non-payload communication (CNPC) as well as payload communication. In this paper, we attempt to tackle two challenges of UAV communication respectively on establishing reliable CNPC links against the high mobility of UAVs as well as changeable communication conditions, and on offering dynamic resource optimization for Quality-of-Service (QoS) guaranteed payload communication with variable link connectivity. Firstly, we propose the concept of air controlling center (ACC), a virtual application equipped on the infrastructure in SAGINs, which can collect global information for estimating UAV trajectory and communication channels. We then introduce the knapsack problem for modelling resource optimization of UAV communication in order to provide optimal access points for both CNPC and payload communication. Meanwhile, using the air controlling information, predictive decision algorithm and handover strategy are introduced for the reliable connection with multiple access points. Simulation results demonstrate that our proposal ensures an approximate always-on reliable accessing of communication links and outperforms the existing methods against high mobility, sparse distribution, and physical obstacles.

The Unmanned Aerial Vehicle (UAV) technologies are envisioned to play an important role in the era of Air-Space-Ground integrated networks. In this paper, we investigate the connectivity of a Flying Ad hoc Network (FANET) in the presence of a ground-based terminal. In particular, the connected probability of the UAV-to-UAV (U2U) link as well as that of the UAV-to-Ground (U2G) link in a three dimensional (3D) space are analyzed. Furthermore, to mitigate the aggregate interference from UAV individuals, a priority based power control scheme is implemented for enhancing the connectivity of both U2U and U2G links. Numerical results illustrate the effectiveness of the proposed analysis.

The ever increasing demand of adhoc networks for adaptive topology and mobility aware communication led to new paradigm of networking among Unmanned Aerial Vehicles (UAVs) known as Flying ad-hoc Networks (FANETs). Due to their dynamic topology, FANETs can be deployed for disaster monitoring and surveillance applications. During these operations, UAVs need to transmit different disaster data, which consists of different types of data packets. Among them there are packets which need to be transmitted urgently because of the emergency situation in disaster management. To handle this situation, we propose a methodology of disaster data classification using urgency level and based on these urgency levels, priority index is assigned to data packets. An approach of Urgency Aware Scheduling (UAS) is proposed to efficiently transmit high and low priority packets with minimum delays in transmission queue. We take into account different scenarios of UAVs for disaster management and for N number of UAVs, we propose bio-inspired mechanism using behavioral study of bird flocking for cluster formation and maintenance. Furthermore, we propose a priority based route selection methodology for data communication in FANET cluster. Simulation results show that our proposed mechanism shows better performance in the presence of evaluation benchmarks like average delay, queuing time, forward percentage and fairness.

The ever increasing wireless data services, such as imaging, video, audio, multimedia, etc., have demands for the very high speed wireless communications and network, which are unfortunately a bottleneck when combining with the wireline core network. Users' are now expecting high quality of experience with low-cost devices, ubiquitous connectivity, energy efficiency, high reliability, or even ultra-low latency if a vehicle terminal is applied.

The ergodic information rate for Orthogonal Frequency-Division Multiplexing / Orthogonal Frequency-Division Multiple Access with amplify-and-forward (AF) relaying systems in the presence of frequency offsets is evaluated. Unlike previous work, per-subcarrier adaptive power allocation is performed on each relay to optimize the system ergodic information rate. For a given frequency offset and total number of relays M, the AF ergodic information rate is proven to be a monotonically increasing function of a (the ratio of the power allocated to the source node and the total transmit power), implying that the maximum ergodic information rate can be obtained at α=1 (i.e., there is no cooperative relay). Furthermore, the proof of “cooperative relays cannot improve the AF ergodic information rate in a quasi-static wireless channel” is also provided in this letter.

The wireless sensor network (WSN) plays an important role in monitoring the environment near the harbor in order to make the ships nearby out of dangers and to optimize the utilization of limited sea routes. Based on the historical data collected by the buoys with sensing capacities, a novel data compression algorithm called adaptive time piecewise constant vector quantization (ATPCVQ) is proposed to utilize the principal components. The proposed system is capable of lowering the budget of wireless communication and enhancing the lifetime of sensor nodes subject to the constrain of data precision. Furthermore, the proposed algorithm is verified by using the practical data in Qinhuangdao Port of China.

Cognitive radio (CR) is regarded as a promising technology for providing a high spectral efficiency to mobile users by using heterogeneous wireless network architectures and dynamic spectrum access techniques. However, cognitive radio networks (CRNs) may also impose some challenges due to the ever increasing complexity of network architecture, the increasing complexity with configuration and management of large-scale networks, fluctuating nature of the available spectrum, diverse Quality-of-Service (QoS) requirements of various applications, and the intensifying difficulties of centralized control, etc. Spectrum management functions with self-organization features can be used to address these challenges and realize this new network paradigm. In this paper, fundamentals of CR, including spectrum sensing, spectrum management, spectrum mobility and spectrum sharing, have been surveyed, with their paradigms of self-organization being emphasized. Variant aspects of self-organization paradigms in CRNs, including critical functionalities of Media Access Control (MAC)- and network-layer operations, are surveyed and compared. Furthermore, new directions and open problems in CRNs are also identified in this survey.