Robust or nonrobust: On MC-DS-CDMA acquisition in LEO satellite communications

Low Earth Orbit(LEO)satellite communications can provide global coverage in the sixth generation communication(6G)networks.To combat the strong Partial Band Interferences(PBIs)and multipath fading in LEO satellite communication systems,the Multicarrier Direct Sequence Code Division Multiple Access(MC-DS-CDMA)technique is a promising alternative to the traditional Single-carrier Direct Sequence Code Division Multiple Access(SC-DS-CDMA)system for its advantages of high bandwidth efficiency,superior interference rejection capability,and low complexity of parallel signal processing.However,limited studies have been conducted on the performance analysis of MC-DS-CDMA acquisition systems in the presence of a large Doppler shift,a unique characteristic of LEO satellite communications.To bridge this gap,we investigate the performance of MC-DS-CDMA systems with two-dimensional acquisition and noncoherent equal gain combining over Rician fading channel in the presence of the Doppler shift and PBIs.The performance metrics are detection probability and Mean Square Error(MSE)of the Doppler factor and delay.Specifically,we derive the closed-form expressions for the MSE and the Probability Density Function(PDF)of the acquisition decision variable and obtain the detection probability.We conduct extensive numerical experiments to verify the theoretical analysis and performance gain of MC-DSCDMA over the SC-DS-CDMA.The results show that MC-DS-CDMA with two-dimensional acquisition is more robust to multipath Rician fading than SC-DS-CDMA.Moreover,MC-DS-CDMA outperforms SC-DS-CDMA regarding the detection probability and MSE when combating the strong PBIs.

Robust two-stage reduced-dimension STAP algorithm andits performance analysis

A new two-stage reduced-dimension space-time adaptiveprocessing （STAP） approach, which combines the subcoherentprocessing interval （sub-CPI） STAP and the principalcomponent analysis （PCA）, is proposed to achieve a more enhancedconvergence measure of effectiveness （MOE）. Furthermore,in the case of the subspace leakage phenomenon, theproposed STAP method is modified to hold the fast convergenceMOE by using the covariance matrix taper （CMT） technique. Bothsimulation and real airborne radar data processing are providedto analyze the convergence MOE performance of the proposedSTAP methods. The results show the proposed method is moresuitable for the practical radar applications when compared withthe conventional sub-CPI STAP method.

Predictive Decision and Reliable Accessing for UAV Communication in Space-Air-Ground Integrated Networks

The cooperation of multiple Unmanned Aerial Vehicles(UAVs) has become a promising scenario in Space-Air-Ground Integrated Networks(SAGINs) recently due to their widespread applications,where wireless communication is a basic necessity and is normally categorized into control and nonpayload 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.

Combined algorithm of acquisition and anti-jamming based on SFT

A communication and navigation receiver is required to remove hostile jamming signals and synchronize receiving signals effectively especially for satellite communication and navigation whose resources are becoming more and more limited. This paper proposes a novel signal receiving method by combining the pro- cesses of anti-jamming and synchronization to reduce the overall computationa~ complexity at the expense of slightly affecting the detection probability, which is analyzed in detail by derivations. Furthermore, this paper introduces sparse Fourier transformation （SFT） into the proposed algorithm to replace fast Fourier transfor- mation （FFT） so as to further reduce the calculation time especially in large frequency offset environments.

Impact of Phase Noise on TDMS Based Calibration for Spaceborne Multi-Beam Antennas

For spaceborne multi-beam antennas(MBAs), time division multiplexed switching(TDMS) based calibration receiver can reduce implementation costs effectively and is very suitable for large-scale applications. However, in practice, random phase noise imposed by noisy local oscillators can cause significant performance degradation in TDMS-based calibration systems. Characterization of phase noise effects is therefore crucial for practical applications. In this paper, we analyze the impact of phase noise on the calibration performance for a MBA system. Specifically, we derive the relationship between the probability of correct amplitude/phase estimation and various practical factors involving the signal-to-noise ratio(SNR), the standard deviation of phase noise, the given tolerance region, and the length of the spreading code. The results provide high efficiency for evaluating the calibration performance of the MBAs based on TDMS, especially for precisely anticipating the impact of phase noise. Finally, the accuracy of the derived results is assessed by simulations in different scenarios.

A Novel Angle of Arrival Tracking Method in Large-Scale-Array Systems

In this paper,we investigate the problem of angle of arrival(AOA)tracking for the largescale 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.

A Communication Middleware with Unified Data Transmission Interface

In a Modern communication network, data exchange become a complex problem because there usually exists a various data formats due to the diversity and complexity of communication devices. In this paper, a communication middleware with unified data transmission interface is introduced, which acts as the abstract communication layer in the heterogeneous distributed private communication network. Devices within the network only need to interact with the middleware, instead of directly communicate with each other by various protocols and interfaces, which can reduce the complexity and diversity of the heterogeneous network. This article describes the structure and features of the middleware, and analyses the use of “buffer pool” in message sending and receiving process. The applications of this middleware can reduce the complexity of heterogeneous network interoperation, and improve communication efficiency.

All-Digital Self-Interference Cancellation in Zero-IF Full-Duplex Transceivers

In this paper,a general scheme in digital self-interference cancellation at baseband for zero-IF full-duplex transceivers is presented. We model the self-interference signals specifically with only the nonlinear distortion signals falling in receiving band considered. A joint estimation algorithm is proposed for compensating the time delay and frequency offset taking into account the IQ amplitude and phase imbalances from mixers. The memory effect and nonlinear distortion are adaptively estimated by the de-correlated normalized least mean square(DNLMS) algorithm. Numerical simulation results demonstrate that the proposed self-interference cancellation scheme can efficiently compensate the self-interference and outperform the existing traditional solutions.

Adaptive suppression of passive intermodulation in digital satellite transceivers

For the performance issues of satellite transceivers suffering passive intermodulation interference,a novel and effective digital suppression algorithm is presented in this paper.In contrast to analog approaches,digital passive intermodulation（PIM） suppression approaches can be easily reconfigured and therefore are highly attractive for future satellite communication systems.A simplified model of nonlinear distortion from passive microwave devices is established in consideration of the memory effect.The multiple high-order PIM products falling into the receiving band can be described as a bilinear predictor function.A suppression algorithm based on a bilinear polynomial decorrelated adaptive filter is proposed for baseband digital signal processing.In consideration of the time-varying characteristics of passive intermodulation,this algorithm can achieve the rapidness of online interference estimation and low complexity with less consumption of resources.Numerical simulation results show that the algorithm can effectively compensate the passive intermodulation interference,and achieve a high signal-to-interference ratio gain.