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Multi-user receivers for the ARGOS system

Context

The ARGOS system is a satellite system dedicated to the study of the environment [1][2]. ARGOS beacons transmit their data periodically to low polar orbit satellites that receive, decode, and then forward the data to ground processing stations [3]. One of the major issues of the ARGOS system concerns the service rate, i.e., the percentage of visible beacons that are successfully processed by an ARGOS satellite. Note that only 6% of the total number of beacons are visible from an ARGOS satellite. The service rate is decreasing with the increasing number of beacons. It is now 68% for a population of 21,000 beacons (2011) but it will fall under 50% when the population will reach 37,600. This is because the Multiple Access Interference (MAI) at the ARGOS satellite receivers is increasing with the number of deployed beacons and the receivers have not been designed to take into account this kind of interference. The origin of the MAI is twofold. First, the relative motion between the beacons and the satellites induces large Doppler shifts on the transmitted frequencies, so the emitted signals overlap in frequency. This happens despite the fact that each beacon has its own carrier frequency. Second, the signals overlap in time since there is no time synchronization between the users. Increasing the system bandwidth or designing spectrally efficient waveforms only provide short term solutions since these techniques do not tackle the main problem, i.e., the suppression of the MAI. 

ARGOS system


Designing MUD receivers for the ARGOS satellite system

We have designed Multi-User Detection (MUD) receivers for the ARGOS system. MUD techniques have been widely used in the context of Code Division Multiple Access (CDMA) systems [4], [5].
MUD receivers have been first evaluated in the synchronous case, i.e., when the beacon signals are all received at the same time at the satellite [6]: converntional detector, maximum likelihood receiver, decorrelator, successice interference cancellation (SIC) receiver and parallel interference cancellation (PIC) receivers. Although this case is unrealistic, it provides useful guidance on the design of MUD techniques in the asynchronous case. The design of MUD receivers in the asynchronous case has also been addressed in [7].
We have also determine the conditions in which two signals are successfully decoded when two signals are received at the satellite [8]. For instance, the next figure shows the areas of successful decoding for different relative frequency shifts and different reltive time delays, when exactly two ARGOS beacons are received by the satellite.


Fig. 1: Area of successful decoding as a function of the relative frequency shift Δf/R and the relative time delay Δt/T , for a signal to interference ratio of 10 dB and a received signal to noise ratio of 10 dB on the user of interest. The dots denote the cases for which both users are successfully decoded. The circles denote the cases for which only one user is decoded, and there is no marker when none of the two users has been decoded.

This is a first step toward the successful decoding of all the colliding signals. We have shown that our approach is able to process 98% of the cases. In this way, the service rate can reach 83% for a population of 37,600 beacons when the signals parameters are perfectly estimated, and 67% when imperfect parameter estimation is considered [10].
The impact of imperfect parameter estimates has also been addressed and a Viterbi & Viterbi algorithm has been  proposed for the joint estimation of the amplitude and carrier phase [9].
Receivers have been evaluated in terms of Bit Error Rate (BER) as a function of several system parameters: the relative frequency shift and the signal to interference ratio between the two received signals, and the Eb/N0 ratio, where Eb is the average energy received per bit and N0 is half the noise variance of the AWGN (Additive White Gaussian Noise) channel. Note that the Eb/N0 ratio is similar to a Signal to Noise Ratio (SNR) per bit.

References and Contributions

  1. “ARGOS: Worldwide Tracking and Environmental Monitoring by Satellite,” http://www.argos-system.org.
  2. D. Clark, “Overview Of the Argos System,” in Proceedings of OCEANS’89, 1989, pp. 934–939.
  3. CNES, “Platform Transmitter Terminal (PTT-A2) Platform Message Transceiver (PMT-A2) - Physical Layer System Requirements,” in AS3-SP-516-274-CNES, 2006.
  4. S. Verdu, “Multiuser Detection.” Cambridge Press, 1998.
  5. R. Lupas and S. Verd´u, “Linear Multiuser Detectors for Synchronous Code-Division Multiple-Access Channels,” IEEE Transactions on Information Theory, vol. 35, no. 1, pp. 123–136, 1989.
  6. F. Fares, M.-L. Boucheret, B. Escrig, T. Calmettes, and H. Guillon, “Multiuser Detection for Time Synchronous ARGOS Signals,” in Proc. International Communications Satellite Systems Conference (ICSSC), 2009.
  7. F. Fares, M.-L. Boucheret, B. Escrig, T. Calmettes, and H. Guillon, “Multiuser Detection for Time Asynchronous ARGOS Signals,” in Proc. IEEE, IET International Symposium on Communication Systems, Networks and Digital signal Processing (CSNDSP), 2010.
  8. B. Escrig, F. Fares, M.-L. Boucheret, T. Calmettes, and H. Guillon, “Impact of Imperfect Parameter Estimation on the Performance of Multi-User ARGOS Receivers,” in Proc. IEEE Global Telecommunications Conference (GLOBECOM), 2010.
  9. F. Fares, B. Escrig, M.L. Boucheret, T. Calmettes, H. Guillon : “Non Data Aided Parameter Estimation for Multi-User ARGOS Receivers,” Wireless Telecommunications Symposium (WTS), London, UK, april 2012.
  10. F. Fares, B. Escrig, M.L. Boucheret, T. Calmettes, H. Guillon : “Multi-User Detection for the ARGOS Satellite System,” International Journal of Satellite Communications and Networking, Wiley, (Second revision in progress).