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Abstract In this paper, a two‐way relay‐aided cognitive satellite terrestrial network (TR‐CSTN) model is proposed, where primary users are located at the edge of the base station. In the TR‐CSTN, one of satellite terminal users (STUs) is selected by the fusion center as the TR to forward information between two edge primary users with power of the TR. Meanwhile, these edge primary users share the licensed frequency band with the selected TR to send information to the satellite. Then, given the limited spectrum utilization and energy efficiency (EE) of the communication system, the cooperative spectrum sensing is employed to realize green communication. Specifically, the fusion center threshold, energy detection threshold, sensing duration and number of STUs are jointly optimized to enhance EE. Furthermore, considering that the node's energy shortage results in a short network lifetime, absolute EE gets improved. In detail, a power allocation scheme named normalized power aided Lévy flight trajectory‐based whale optimization algorithm (NP‐LWOA) is provided, which fulfills effective energy compensation among STUs to prolong the network lifetime notably. Finally, numerical results confirm the theoretical analysis and show the effectiveness of the TR‐CSTN and the NP‐LWOA in efficiently achieving the concept of green communication compared with other methods.

Unmanned Aerial Vehicle (UAV) clustering is promising for performing large-scale missions because of high mobility and easy deployment. However, the connectivity problems caused by the high mobility of UAVs and the interferences are mostly ignored in existing UAV mission executions. Rapid restoration of UAV network connectivity is essential for preventing communication disruption and improving the overall network performance. Thus, a graph coalition formation game that integrates the UAV time-varying topology graph with the coalition formation game is proposed to rapidly restore the connectivity of the UAV network in need. The method improves the utility of UAV clustering and ensures the network connectivity. Then, a graph coalition formation game algorithm based on the shortest path tree (SPT-GCF) rapidly forms an approximately optimal coalition structure. The simulation results show that the proposed approach increases the average utility of UAV clustering by 6.5% and 14.5% respectively when compared with the existing non-overlapping coalition formation game (NOCFG) and the coalition formation game without considering the cluster connectivity.

Abstract In high‐speed mobile scenarios, due to the high‐speed relative motion between transmitter and receiver, the high Doppler frequency shift interferes with the inter‐subcarrier orthogonality in orthogonal frequency‐division multiplexing (OFDM) systems. Therefore its performance is significantly degraded. Recently, orthogonal time–frequency space (OTFS) is considered as an effective alternative scheme to OFDM for time‐varying channels. As with OFDM‐massive multiple input multiple output (MIMO) systems, downlink channel estimation is necessary for OTFS‐massive MIMO systems to improve the spectral efficiency in frequency‐division duplex (FDD) mode without channel reciprocity. Here, first the cyclic prefix ‐OFDM‐based massive MIMO OTFS system channel with antenna directivity pattern is analyzed, and transform the burst sparsity in the angle domain into block sparsity by using non‐uniform Fourier transform (NUFT). Furthermore, to solve the problem that the pilot overhead grows linearly with the number of antennas, we propose a three‐dimensional (3D) dynamic support detect (DSD) algorithm. Compared with the traditional OMP algorithm, and the 3D‐structured orthogonal matching pursuit algorithm, simulation results demonstrate the proposed DSD algorithm has higher channel estimation accuracy, and lower pilot overhead.

In this paper, we propose an energy‐efficient unmanned aerial vehicle (UAV) relaying network. In this network, the channels between UAVs and ground transceivers are model‐free. A UAV acting as a flying relay explores better channels to assist in efficient data delivery between two ground nodes. The full‐duplex relaying mode is applied for potential energy efficiency (EE) improvements. With the genetic algorithm, we manage to optimize the UAV trajectory for any arbitrary radio map scenario. Numerical results demonstrate that compared to other schemes (eg, fixed trajectory/speed policies), the proposed algorithm performs better in terms of EE. Additionally, the impact of self‐interference on average EE is also investigated.

In this paper, an energy-efficient full-duplex (FD) unmanned aerial vehicle (UAV) relaying network is proposed, where UAV acts as a mobile relay and assists information exchange between two transceivers. Specifically, the load-carry-and-delivery scheme is applied to positively take advantage of the time-varying channel gain in delay-tolerant networks; meanwhile, the FD communication policy is used to potentially further increase the energy efficiency (EE). In particular, the self-interference channel gains follow the complex Gaussian distribution instead of being constant. The EE is first rigorously derived and then, the optimum flight speed is determined under the information causality constraint to maximize the EE. Numerical results demonstrate that the proposed scheme outperforms the half-duplex as well as static schemes in terms of the EE. In addition, the impact of the self-interference cancellation factor on the EE is also demonstrated, which provides valuable insights for the system design of UAV-assisted relaying networks.

In this paper, a new type of quadrature phase shift keying (QPSK) modulation, named as special QPSK (SQPSK), is proposed and optimized. For SQPSK, the quadrant of the symbol is determined by the bits in information sequence according to QPSK constellation, while the offset relative to the original QPSK constellation is controlled by the bits in synchronization sequence. Under this scheme, the simultaneous transmission of information and synchronization sequences is implemented to improve spectrum efficiency with low computational complexity. In order to achieve the best balance between the bit error rate (BER) and the synchronization performance, we optimize the parameter design. Furthermore, a joint synchronization scheme is proposed for frame synchronization, frequency offset estimation, and frequency offset compensation to solve the performance loss caused by Doppler frequency shift in practical applications. Then based on the characteristics of the constellation map, a dynamic threshold demodulation scheme which further improves the BER performance is discussed. Finally, some simulation results are given to show that the SQPSK not only has both good error performance and acquisition performance, but also improves the spectrum utilization of channel resource significantly.

In this paper, in order to settle the problem of unintentional interference between communication devices and obtain effective information quickly and accurately in cognitive radio (CR), and an intelligent modulation pattern recognition method based on wavelet approximate coefficient entropy (WACE) is proposed. Based on the traditional wavelet entropy, an improved wavelet entropy, WACE, is presented, which can characterize the modulated signal pattern and suppress the noise effectively. Furthermore, in order to solve the problem of high complexity for linear weighting calculation, the deep neural network (DNN) is adopted, and the vector of the WACE is used as the input of the DNN to realize intelligent recognition of a variety of typical communication signal modulation patterns. Simulation results verify the correctness of the theoretical analysis, and show that the proposed intelligent recognition method can effectively realize the modulation pattern recognition of multiple signals at low signal-to-noise ratio (SNR), with relative low computational complexity.

Destination‐assisted jamming (DAJ) is usually used to protect confidential information against untrusted relays and eavesdroppers in wireless networks. In this paper, a DAJ‐based untrusted relay network with multiple antennas installed is presented. To increase the secrecy, a joint optimization of beamforming and power allocation at the source and destination is studied. A matched‐filter precoder is introduced to maximize the cooperative jamming signal by directing cooperative jamming signals toward untrusted relays. Then, based on generalized singular‐value decomposition (GSVD), a novel transmitted precoder for confidential signals is devised to align the signal into the subspace corresponding to the confidential transmission channel. To decouple the precoder design and optimal power allocation, an iterative algorithm is proposed to jointly optimize the above parameters. Numerical results validate the effectiveness of the proposed scheme. Compared with other schemes, the proposed scheme shows significant improvement in terms of security performance.

In a typical downlink massive multiple-input and multiple-output (massive MIMO) system, the available degree of freedom (DoF) and multiplexing gain improve the channel rate. However, while a finite base station (BS) antenna limits the DoF, the line of sight (LoS) component decreases the multiplexing gain as a result of reducing the rank of the Ricean channel matrix. This paper provides the simple and tight approximations of the massive MIMO channel rate using the zero-forcing (ZF) precoding over the Ricean fading channel and with a finite antenna. We derive an accurate approximation of the ZF Ricean channel covariance matrix by exploiting the arbitrary-rank channel mean. This allows the ZF precoding to focus on the nonzero eigenmode of the correlation matrix in order to improve the channel gain. Subsequently, we deduce the first-, second- and third-eigenvalue moments. We then obtain an asymptotic series expansion in the closed-form expressions of the ZF achievable rates. Numerical results confirm the accuracy of the approximations, as the approximated ZF achievable rates converge to the ideal channel rate. In particular, the convergence shows a dependence on the Ricean factor and effective signal-to-noise ratio (SNR), while a finite BS antenna in ZF massive MIMO channel offers the required diversity order.

In practical massive multiple-input-multiple-output (MIMO) system, limited transmitted antennas installed at the base station (BS) cannot guarantee the ideal orthogonality and the theoretical channel rate cannot thus be achieved. In this paper, we consider the approximation of channel rate for the configuration of large but finite number of antennas at BS in a massive MIMO system. A perturbation matrix is introduced to model the non-ideal orthogonality. And then, Taylor expansion of determinant is utilized to derive the closed form of the achievable channel rate. The convergence of the Taylor expansion is theoretically proved and simulated. Numerical results show that our calculation of channel rate can get a better approximation compared with the practical rate, especially in the case of high expansion order and large number of antennas.

In this paper, a destination-assisted-jamming-based secure transmission is devised for an untrusted and energy harvesting relay network. In the proposed scheme, both source and destination split their energies into two parts for energy harvesting at the relay and transmissions of confidential and cooperative jamming signals, respectively. We formulate an optimization problem to maximize the achievable secrecy rate by jointly optimizing the energy splitting for the source and destination. The existence of the solution for the optimization is carefully analyzed. Due to high complexity of the joint optimization, an iterative optimization algorithm to obtain the near-optimal energy splitting policy is proposed. The numerical results validate that the optimized energy splitting policy leads to a higher achievable secrecy rate, and the iterative algorithm has a quick convergence rate.

The Global Navigation Satellite System (GNSS) receiver is vulnerable to active jamming, which results in imprecise positioning. Therefore, antijamming performance of the receiver is always the key to studies of satellite navigation system. In antijamming application of satellite navigation system, if active jamming is received from array antenna main-lobe, main-lobe distortion happens when the adaptive filtering algorithm forms main-lobe nulling. A robust method to suppress jamming for satellite navigation by reconstructing sample covariance matrix without main-lobe nulling is proposed in this paper. No nulling is formed while suppressing the main-lobe jamming, which avoids main-lobe direction distortion. Meanwhile, along with adaptive pattern control (APC), the adaptive pattern of array antenna approaches the pattern without jamming so as to receive the matching navigation signal. Theoretical analysis and numerical simulation prove that this method suppresses jamming without main-beam distortion. Furthermore, the output SINR will not decrease with the main-lobe distortion by this method, which improves the antijamming performance.