An investigation into the constellation design methodology of high-altitude platform (HAP) broadband networks is presented. The quality of service (QoS) metrics and user demand model are established in the HAP broadband networks. Each HAP is seen as a mobile base station, and a methodology of mobile base station placement is proposed with QoS and user demand guarantee for the first time. The multiple HAP coverage is analyzed with link geometry based on the single HAP coverage model. Besides, a cost-efficient optimization design framework for the HAP constellation is established by optimizing the design vector to maximize the network capacity per cost under the constraints of QoS metrics. In addition, the optimization model and improved artificial immune algorithm based on immune review are designed, and performance of the proposed method is demonstrated through in-depth numerical simulations. Simulation results show that the proposed constellation design method can effectively solve the problem of the mobile base station layout in the HAP broadband networks.

A typical application scenario of remote wireless sensor networks (WSNs) is identified as an emergency scenario. One of the greatest design challenges for communications in emergency scenarios is energy-efficient transmission, due to scarce electrical energy in large-scale natural and man-made disasters. Integrated high altitude platform (HAP)/satellite networks are expected to optimally meet emergency communication requirements. In this paper, a novel integrated HAP/satellite (IHS) architecture is proposed, and three segments of the architecture are investigated in detail. The concept of link-state advertisement (LSA) is designed in a slow flat Rician fading channel. The LSA is received and processed by the terminal to estimate the link state information, which can significantly reduce the energy consumption at the terminal end. Furthermore, the transmission power requirements of the HAPs and terminals are derived using the gradient descent and differential equation methods. The energy consumption is modeled at both the source and system level. An innovative and adaptive algorithm is given for the energy-efficient path selection. The simulation results validate the effectiveness of the proposed adaptive algorithm. It is shown that the proposed adaptive algorithm can significantly improve energy efficiency when combined with the LSA and the energy consumption estimation.

One of the main design challenges in wireless sensor networks (WSNs) is achieving a high-data-rate transmission for individual sensor devices. The high altitude platform (HAP) is an important communication relay platform for WSNs and next-generation wireless networks. Multiple-input multiple-output (MIMO) techniques provide the diversity and multiplexing gain, which can improve the network performance effectively. In this paper, a virtual MIMO (V-MIMO) model is proposed by networking multiple HAPs with the concept of multiple assets in view (MAV). In a shadowed Rician fading channel, the diversity performance is investigated. The probability density function (PDF) and cumulative distribution function (CDF) of the received signal-to-noise ratio (SNR) are derived. In addition, the average symbol error rate (ASER) with BPSK and QPSK is given for the V-MIMO model. The system capacity is studied for both perfect channel state information (CSI) and unknown CSI individually. The ergodic capacity with various SNR and Rician factors for different network configurations is also analyzed. The simulation results validate the effectiveness of the performance analysis. It is shown that the performance of the HAPs network in WSNs can be significantly improved by utilizing the MAV to achieve overlapping coverage, with the help of the V-MIMO techniques.

In this study, security schemes at the physical layer are proposed for an amplify‐and‐forward relay system in the presence of a passive eavesdropper. We focus on maximising the transmit power of the artificial noise (AN) to degrade the minimum mean square error (MMSE) level at the eavesdropper, while achieving MMSE constraint for the desired receiver. Assuming that the desired receiver and the passive eavesdropper possess perfect channel state information (CSI), AN is designed to lie in the null space of legitimate channels. However, the available CSI is impossible to be perfect in practice. Therefore the authors present a robust beamforming scheme which maximises the worst‐case transmit power of the AN under the condition of imperfect CSI and recovers a large fraction of the performance in the perfect CSI case. A classical alternating optimisation algorithm is proposed to obtain the relay beamforming weights, and simulation results show the benefit of proposed schemes.

The integrative development of hybrid satellite terrestrial communication systems (HSTCSs) has become a hot research field for next generation communications. This letter proposes the hybrid 1-D and 2-D beam models for the return link (RL) of the HSTCSs by considering the equivalent interference factor $ \beta $ from the TCSs and the equivalent interference factor $ \alpha $ from inter-beam. Then, the channel profile matrices of the hybrid 1-D and 2-D beam models are constructed and the eigenvalues are obtained. The closed-form approximations of Shannon theoretic limits for the optimal joint decoding capacity and linear minimum mean square error (MMSE) capacity are derived and evaluated through simulations. Monte Carlo simulations show that the closed-form approximations can be considered as the optimal capacity and MMSE capacity upper bound for the RL of HSTCSs under the Rician fading.

Relay strategies can increase coverage range and improve reliability for power‐limited sensors. In this study, cooperative jamming schemes are investigated for security communications in two‐hop multi‐sensors relay networks where a passive eavesdropper can wiretap the relay channels in both hops. The normally inactive nodes can be used as cooperative jamming sources to confuse the eavesdropper. Artificial noise (AN) is maximised to degrade the signal‐to‐interference‐plus‐noise ratio (SINR) level at the eavesdropper, while satisfying the individual power constraint of each relay sensor and SINR constraint at the desired receiver. Assuming that CSI is perfect, relay beamforming weights can be obtained by solving a second‐order cone programming problem. However, the available CSI is impossible to be perfect in practice. Therefore, a robust beamforming scheme is also presented. The transmit power used for AN is maximised, while satisfying the power constraint of each relay sensor and worst‐case SINR constraint at the desired receiver under a bounded spherical region for the norm of the CSI error vector from the relays to the destination. Robust beamforming weight vector can be obtained by using S‐procedure and rank relaxation techniques. The benefits of the proposed schemes are shown in simulation results.