User Antenna Diversity for efficient multipath mitigation

User Antenna Diversity for efficient multipath mitigation


The impact of multipath and fading in harsh propagation conditions is still among the main sources of errors in PNT solutions for mobile users. Besides code-based positioning accuracy, they affect convergence time of carrier-based solutions (e.g. PPP) and may prevent ambiguity resolution. For handheld user equipment (HH-UE) such as smartphones and tablets, antenna performance is traded against integration and cost, which yields degraded multipath rejection and positioning performance compared to solutions using high-end antennas (or even standard patch antennas, as used for instance in automotive applications).

Despite significant R&D efforts (e.g. novel design, innovative materials) and very promising results, solutions to mitigate multipath still yield high costs for HH-UE.

In wireless communications, capabilities of antenna diversity algorithms are well known and widely used to mitigate channel impairments (multipath and non-line-ofsight signals). HH-UE mounting multiple low-performance antennas is being considered for future wireless systems.

Antenna diversity algorithms and architectures for HH-UE could be considered as a relevant alternative to enhance performance and multipath mitigation without sacrificing complexity and cost. With the advent of GNSS chipsets with two RF frontends (supporting dual-frequency which could also support two antennas) for HH-UE, antenna diversity may be among the future trend to enhance performance of massmarket handheld applications.

The main objective of the proposed activity is to investigate user antenna diversity algorithms and architectures to enhance multipath mitigation on handheld devices using low cost antennas.

 The tasks to be performed will include:

  • assessing algorithms exploiting both spatial diversity (different location of the antennas on the smartphone or tablet) and polarisation diversity; 
  • developing antenna diversity architectures based on low cost HH UE;
  • implementing and testing selected solutions in real conditions (e.g. urban environment);
  • assessing resulting performance, to be benchmarked against off-the-shelf solutions (e.g. smartphones, mass-market chipsets with high-end antennas).

The main result of the activity will provide a concept demonstrator, together with assessment implementation of different spatial diversity algorithms and architectures in real test conditions.
Results from related GSA H2020/FE projects will be duly considered and assessed.