International Journal of Satellite Communications and Networking最新文献

The ultra-dense low earth orbit (LEO) satellite constellation (UD-LSC) networks are expected to be incorporated in future wireless networks, particularly 6G networks, to provide global wireless access with enhanced data rates. This paper investigates the downlink multigroup multicast transmission for UD-LSC networks, in which LEO satellites provide the multicast service for ground users with full frequency reuse. Moreover, in-network caching, as a key enabling technology of information-centric networking, is brought into UD-LSC networks to achieve both bandwidths saving and delay reduction. However, the multicast capacity is constrained by the signal to interference and noise ratio (SINR) of bottleneck users in each multicast group. Besides, the high-speed movement of LEO satellites makes cache placement and updating more challenging than ground networks with immobile base stations. To track these problems, we first propose a cache-enabled multi-satellite cooperation framework and formulate the multicast transmission problem and the content caching problem. Then, to reduce the average content delivery delay (CDD) of ground users, we propose a cooperative multicast beamforming and transmission-aware dynamic caching (CMB-TDC) algorithm based on the sample average approach and successive convex approximation. Simulation results show that the proposed CMB-TDC algorithm can improve the multicast capacity, and then the average CDD is reduced for UD-LSC networks.

The general Global Navigation Satellite System (GNSS) receiver faces several challenges because of jamming signals, spoofing signals, and multipath signals, which severely influence its safety. In this paper, a receiver scheme with an interference recognition function is designed. In the latter, the correlation peak with different shapes is produced according to different interferences. The machine learning method is then applied to recognize and classify these feature maps. This transforms the interference recognition problem into a machine learning-based classification problem. In order to reduce the complexity of the machine learning network, only the finite-length correlation peak region of interest (ROI) is extracted as network input, endowing the shallow neural network with the interference recognition function. Afterward, five data acquisition environments are designed: authentic, spoofing, jamming, non-line-of-sight (NLOS) multipath, and line-of-sight (LOS) multipath. Moreover, several experimental data are acquired, followed by the production of the correlation peak maps dataset, that are then learned and tested using two machine learning networks: one-dimensional convolutional neural network (1D-CNN) and bidirectional long short-term memory neural network (BiLSTM-NN). The results demonstrate that a recognition accuracy rate of over 98% can be reached using the shallow machine learning network.

Recently, Yulei Chen and Jianhua Chen (An enchanced dynamic authentication scheme for mobile satellite communication systems. Int J Satell Commun Netw. 2020; 39(3): 250-262) presented an enhanced dynamic authentication scheme for mobile satellite communication systems in 2020. The authors found that there is a flaw in the authentication phase of the scheme proposed by Yulei Chen and Jianhua Chen's scheme. Due to this flaw, user is unable to authenticate to NCC (network control center) and also fails to establish the session key with NCC. In this paper, the authors improved the Yulei Chen and Jianhua Chen's scheme. In the proposed scheme, it is shown that user is able to authenticate to NCC (network control center) and also establish the session key with NCC. The authors also demonstrate that the computation cost and communication cost are also decreased.

In this research, an implementation of artificial deep neural networks (ANN) over outputs of 24-h multi-domain high-resolution nested real case Weather Research and Forecasting (WRF) model runs was carried out over two high-resolution simulation domains, which are tested and compared for rainfall generation in order to assess the signal fading event observed on geostationary telecommunication spacecraft in orbit for a real multiscale storm case. Our methodology of ANN, which is driven by WRF model output parameters, focuses on prediction of the rain attenuation signal impairment which is observed on the communication satellite telemetry (TM) downlink signal levels under significant aerosol presence due to dust storm which occurred on 12 September 2020. This modelling approach is then compared to rain attenuation observed on TM signal and correlated with communication satellite ground station TM signal measurements. Preliminary results from conducted error analysis (RMSE) on multiple input single output feed-forward neural network (MISO FFNN) prediction model outputs tested with several neural algorithms indicate good correlation with the TM downlink signal attenuation observations taken from the ground station TM baseband demodulator.

The carrier phase (CP) measurements should be unambiguous to achieve the enhanced accuracy of Global Navigation Satellite System (GNSS) services. However, all the real-time CP measurements are manipulated by different errors, namely, satellite and receiver clock error, ionosphere delay, troposphere delay, integer ambiguity, etc. Even after removing or minimizing all these errors, the CP measurements are influenced by multipath error and receiver hardware residual or bias. In this research article, a double difference (DD) method is proposed to estimate residual or bias in CP observations of Navigation with Indian Constellation (NavIC). The proposed method abolishes all the common errors and provides bias. However, the CP measurement with a bit of bias value can be considered a high-quality signal. Here, we investigate the quality of NavIC satellites L5 (1176.45 MHz) signal with real-time measurements obtained through zero base length (ZBL) and short base length (SBL) experiments conducted at Kurnool (15.79°N, 78.07°E), India. The results show that the CP measurement bias of the L5 signal is within the range ±0.338 and ±1.688 m, respectively, for stationary and moving receivers. The bias was enhanced to 3.71 m for the SBL measurements. The results also demonstrate that the bias is low when carrier to noise (C/No) is high, and its range is nearly the same for all the days. This research would be helpful to estimate the bias that improves accuracy of precise point positioning (PPP) applications.

The use of space-based Automatic Dependent Surveillance-Broadcast (ADS-B) receivers to extend aircraft surveillance beyond line-of-sight communication has been discussed since the late 2000s and has been demonstrated in various missions. Although recent demonstrations have relied on small CubeSat platforms, the use of the smallest possible form factor has not been explored. This paper describes development of a spacecraft representing the first use of a 1 U CubeSat platform for aircraft tracking. To comply with the platform's limited power budget, the receiver departs from the typical application of FPGA boards to decoding ADS-B signals and instead employs a general microprocessor. The spacecraft also features some innovations over traditional CubeSat platforms, such as distributed system-level software amenable to extensive code reuse, redundant communications mechanisms, and software-based radiation mitigation strategies. Having designed, built, and integrated all subsystems, as well as performed multiple test campaigns at system and subsystem level, the team now aims at completing formal functional and environmental testing before undergoing the launch campaign, foreseen for 2022.

In the fifth-generation (5G) and future sixth-generation (6G) networks, improving spectral efficiency and system capacity is still the main concern. Adding LEO satellite to the construction of 5G and 6G can make the network structure three-dimensional, which lets the network construction get rid of the limitation of ground space propagation distance and makes the wider area enjoy the convenience of 5G and 6G. However, due to the large link distance between space and the ground, the communication of LEO satellite in Ka band is greatly affected by rain attenuation and shadow fading. In order to improve the ergodic capacity of LEO satellite downlink, this paper attempts to apply nonorthogonal multiple access (NOMA) to hybrid channels with rainfall fading and shadow fading. In the simulation results, the ergodic capacity of orthogonal frequency division multiple access (OFDMA) and NOMA is compared, and it is found that the system capacity of hybrid channel can be improved by increasing the power allocation factor of NOMA. The experiments have studied the influence of LEO satellite's orbital height, fading degree, and transmission power in the communication link on the performance of LEO satellite system in this paper. The experimental results show that the lower the orbit height is, the better system performance will become under the same fading degree. Moreover, the energy consumed gradually decreases with the transmission power becoming small.

In this paper, downlink multigroup multicast transmission in the ultra-dense low Earth orbit satellite constellation networks with full frequency reuse is studied. Multicast transmission significantly improves the system performance compared with point-to-point transmission. However, multicast capacity is constrained by the signal to interference and noise ratio (SINR) of bottleneck users in each group. To tackle this problem, we propose an alternating optimization-based joint power allocation and cooperative beamforming algorithm (AO-JPACB) to enhance the SINR of the bottleneck users and improve the system capacity. Simulation results show that the proposed AO-JPACB algorithm can improve the system capacity compared to single-satellite schemes.

The latest technical recommendation by the International Telecommunication Union (ITU) for a data exchange system in the VHF maritime mobile band defines a random access channel (RAC) for communications on the uplink channel between vessels and satellites. The physical layer frame for random uplink channel is designed to allow for a more efficient use of the power amplifiers and includes features to assist the satellite receivers to resolve overlapping reception of multiple messages. This paper presents the performance results of an over-the-air test campaign carried out exploiting the NorSat-2 Low Earth orbit (LEO) satellite. After a review of the VDE-SAT RAC and Link ID 20 burst, a possible demodulator implementation is shown. Then, the VDE-SAT transmitter platform, located in Pisa, Italy, emulating a population of vessels transmitting to the NorSat-2 LEO satellite is introduced, and the test cases are described. Afterward, the analysis of the recorded signals is provided. The post-analysis first focuses on the demodulation performance in terms of probability of successful demodulation of the interfering bursts. Further investigation has also been carried out to better understand the interference environment in this frequency band for satellite signal reception. Tests indicate promising results of successfully detecting and demodulating up to 22 overlapping RAC messages, confirming the robustness of the protocol. Finally, capitalizing on the above analysis, conclusions suggest possible improvements.