Thomas Grelier

Regulatory analysis of potential candidate bands for the modernisation of GNSS systems in 2015–2020

With the increase of global satellite navigation systems (GNSS) in a limited number of frequency bands, the current spectrum dedicated to satellite navigation encounters congestion. A possible path to keep modernizing the different GNSS is to find new frequency bands where a satellite radio-navigation service (RNSS) could be provided. This article takes a regulatory approach to identify potential candidate bands, which are then reviewed in detail to assess their usability for a new RNSS deployment. The results of this analysis are: (1) there exist spaces in the spectrum where a RNSS allocation exists or could be added. For example, the option consisting in adding another RNSS allocation into aeronautical radio-navigation service (ARNS) bands. However, such allocation change is not planned and would require important commitment from administrations and long negotiations with the civil aviation community; (2) the use of telecommunication signals of opportunity coming from an hybrid satellite-terrestrial network of emitters. Among these solutions, some would permit to combine navigation and telecommunication services, offering a huge opportunity for mass market application.

Optimizing GNSS navigation data message decoding in urban environment

Nowadays, the majority of new GNSS applications targets dynamic users in urban environments; therefore the decoder input in GNSS receivers needs to be adapted to the urban propagation channel to avoid mismatched decoding when using soft input channel decoding. The aim of this paper consists thus in showing that the GNSS signals demodulation performance is significantly improved integrating an advanced soft detection function as decoder input in urban areas. This advanced detection function takes into account some a priori information on the available Channel State Information (CSI). If no CSI is available, one has to blindly adapt the detection function in order to operate close to the perfect CSI case. This will lead to avoid mismatched decoding due to, for example, the consideration by default of the Additive White Gaussian Noise (AWGN) channel for the derivation of soft inputs to be fed to soft input decoders. As a consequence the decoding performance will be improved in urban areas. The expressions of the soft decoder input function adapted for an urban environment is highly dependent on the available CSI at the receiver end. Based on different model of urban propagation channels, several CSI contexts will be considered namely perfect CSI, partial statistical CSI and no CSI. Simulation results will be given related to the GPS L1C demodulation performance with these different advanced detection function expressions in an urban environment. The results presented in this paper are valid for any kind of soft input decoders, such as Viterbi decoding for trellis based codes, the MAP/BCJR decoding for turbo-codes and the Belief Propagation decoding for LDPC codes.