Architectures and synchronization techniques for distributed satellite systems: a survey

Cohesive Distributed Satellite Systems (CDSSs) is a key enabling technology for the future of remote sensing and communication missions. However, they have to meet strict synchronization requirements before their use is generalized. When clock or local oscillator signals are generated locally at each of the distributed nodes, achieving exact synchronization in absolute phase, frequency, and time is a complex problem. In addition, satellite systems have significant resource constraints, especially for small satellites, which are envisioned to be part of the future CDSSs. Thus, the development of precise, robust, and resource-efficient synchronization techniques is essential for the advancement of future CDSSs. In this context, this survey aims to summarize and categorize the most relevant results on synchronization techniques for Distributed Satellite Systems (DSSs). First, some important architecture and system concepts are defined. Then, the synchronization methods reported in the literature are reviewed and categorized. This article also provides an extensive list of applications and examples of synchronization techniques for DSSs in addition to the most significant advances in other operations closely related to synchronization, such as inter-satellite ranging and relative position. The survey also provides a discussion on emerging data-driven synchronization techniques based on Machine Learning (ML). Finally, a compilation of current research activities and potential research topics is proposed, identifying problems and open challenges that can be useful for researchers in the field.This work was supported by the Luxembourg National Research Fund (FNR), through the CORE Project COHEsive SATellite (COHESAT): Cognitive Cohesive Networks of Distributed Units for Active and Passive Space Applications, under Grant FNR11689919.Award-winningPostprint (published version

Sidelobe Control in Collaborative Beamforming via Node Selection

Collaborative beamforming (CB) is a power efficient method for data communications in wireless sensor networks (WSNs) which aims at increasing the transmission range in the network by radiating the power from a cluster of sensor nodes in the directions of the intended base station(s) or access point(s) (BSs/APs). The CB average beampattern expresses a deterministic behavior and can be used for characterizing/controling the transmission at intended direction(s), since the mainlobe of the CB beampattern is independent on the particular random node locations. However, the CB for a cluster formed by a limited number of collaborative nodes results in a sample beampattern with sidelobes that severely depend on the particular node locations. High level sidelobes can cause unacceptable interference when they occur at directions of unintended BSs/APs. Therefore, sidelobe control in CB has a potential to increase the network capacity and wireless channel availability by decreasing the interference. Traditional sidelobe control techniques are proposed for centralized antenna arrays and, therefore, are not suitable for WSNs. In this paper, we show that distributed, scalable, and low-complexity sidelobe control techniques suitable for CB in WSNs can be developed based on node selection technique which make use of the randomness of the node locations. A node selection algorithm with low-rate feedback is developed to search over different node combinations. The performance of the proposed algorithm is analyzed in terms of the average number of trials required to select the collaborative nodes and the resulting interference. Our simulation results approve the theoretical analysis and show that the interference is significantly reduced when node selection is used with CB.Comment: 30 pages, 10 figures, submitted to the IEEE Trans. Signal Processin

Collaborative Beamforming for Distributed Wireless Ad Hoc Sensor Networks

The performance of collaborative beamforming is analyzed using the theory of random arrays. The statistical average and distribution of the beampattern of randomly generated phased arrays is derived in the framework of wireless ad hoc sensor networks. Each sensor node is assumed to have a single isotropic antenna and nodes in the cluster collaboratively transmit the signal such that the signal in the target direction is coherently added in the far- eld region. It is shown that with N sensor nodes uniformly distributed over a disk, the directivity can approach N, provided that the nodes are located sparsely enough. The distribution of the maximum sidelobe peak is also studied. With the application to ad hoc networks in mind, two scenarios, closed-loop and open-loop, are considered. Associated with these scenarios, the effects of phase jitter and location estimation errors on the average beampattern are also analyzed.Comment: To appear in the IEEE Transactions on Signal Processin

Collaborative Data Transmission in Wireless Sensor Networks

grant TR32043 grant III44003 grant III43002Collaborative beamforming (CBF) is a promising technique aimed at improving energy efficiency of communication in wireless sensor networks (WSNs) which has attracted considerable attention in the research community recently. It is based on a fact that beampattern with stable mainlobe can be formed, if multiple sensors synchronize their oscillators and jointly transmit a common message signal. In this paper, we consider application of CBF with one bit of feedback in different communication scenarios and analyze the impact of constraints imposed by simple sensor node hardware, on the resulting signal strength. First, we present a CBF scheme capable of reducing interference levels in the nearby WSN clusters by employing joint feedback from multiple base stations that surround the WSN of interest. Then, we present a collaborative power allocation and sensor selection algorithm, capable of achieving beamforming gains with transmitters that are not able to adjust their oscillators' signal phase. The performance of the algorithms is assessed by means of achieved beamforming gain which is given as a function of algorithm iterations. The presented results, which are based on numerical simulations and mathematical analysis, are compared with the ideal case without constraints and with negligible noise at the Base Station (BS).publishersversionpublishe

On implementation aspects of decode and forward and compress and forward relay protocols

In this work, the common relay protocols Decode-and-Forward and Compress-and-Forward (CF) are investigated from a practical point of view: This involves on the one hand the impact of imperfections like channel and carrier phase stimation errors and on the other hand, the question of how to implement relay protocol specific signal processing like quantization for CF which is modeled in information theory simply by additive quantizer noise. To evaluate the performance, achievable rates are determined either numerically with the help of the Max-Flow Min-Cut theorem or by link level simulations.Diese Arbeit untersucht die Relay-Protokolle Decode-and-Forward und Compress-and-Forward (CF) mit dem Fokus auf einer praktischen Umsetzung. Es werden sowohl Störeinflüsse wie Kanal- und Phasenschätzfehler betrachtet als auch spezielle Kompressionsverfahren für das CF Protokoll implementiert. Von großer Bedeutung ist hier die Kompression in Form der Quantisierung, weil diese in der Informationstheorie lediglich durch Quantisierungsrauschen modelliert wird. Zur Auswertung der Leistungsfähigkeit der Protokolle werden die erzielbaren Raten entweder numerisch oder durch Simulation bestimmt

Architectures and Synchronization Techniques for Distributed Satellite Systems: A Survey

Cohesive Distributed Satellite Systems (CDSSs) is a key enabling technology for the future of remote sensing and communication missions. However, they have to meet strict synchronization requirements before their use is generalized. When clock or local oscillator signals are generated locally at each of the distributed nodes, achieving exact synchronization in absolute phase, frequency, and time is a complex problem. In addition, satellite systems have significant resource constraints, especially for small satellites, which are envisioned to be part of the future CDSSs. Thus, the development of precise, robust, and resource-efficient synchronization techniques is essential for the advancement of future CDSSs. In this context, this survey aims to summarize and categorize the most relevant results on synchronization techniques for Distributed Satellite Systems (DSSs). First, some important architecture and system concepts are defined. Then, the synchronization methods reported in the literature are reviewed and categorized. This article also provides an extensive list of applications and examples of synchronization techniques for DSSs in addition to the most significant advances in other operations closely related to synchronization, such as inter-satellite ranging and relative position. The survey also provides a discussion on emerging data-driven synchronization techniques based on Machine Learning (ML). Finally, a compilation of current research activities and potential research topics is proposed, identifying problems and open challenges that can be useful for researchers in the field

A review on frequency synchronization in collaborative beamforming: a practical approach

Coherent signal reception from distributed beamforming nodes of virtual antenna array formation requires frequency synchronization of the participating nodes. Signals at the target receiver are out of phase due to unsynchronized local oscillator’s (LO) reference signal of all the nodes in the systems. Practical cases of this problem are considered. In this article, a brief overview is presented of the need for the frequency synchronization and the resulting effect of mitigation avoidance. A variant of the closed-loop feedback algorithm is used to provide LO drifts information to the beamforming transmitters. These feedbacks are used to estimate, correct, and predict the nonlinear LO offsets that will result in near (0) phase offset of the received signal. The algorithms are implemented in software defined radio (SDR) and transmitted through the RF front end of devices like the NI 2920/N210 USRP