Abstract
This work focuses on positioning on a 2D plane using a massive MIMO software defined radio, yielding distance and angle of a movable mobile station relative to a stationary base station. Within the scope of this work, the software defined radio (built by National Instruments) was programmed to save channel estimates from realworld measurements of an 8 by 2 antenna MIMO OFDM transmission. The measurements were done outdoors and indoors, as to give results with and without significant multi path components and different environments. Hardware limitations, especially very small available bandwidth had to be taken in consideration.
Furthermore, a mathematical model of the signal processing in the hardware, the channel, received signals and estimation of the distance and angle was formulated.
This mathematical model was implemented and used with data from the measurements, yielding estimates for the two parameters.
Lastly, focus shifted on a statistical evaluation of the results, comparing them to theoretical lower limits of accuracy imposed by the CramerRao lower bound.
Results showed that for two evaluated measurements the performance of distance estimation was subpar, because the (unwired) synchronization between base station and mobile station was insufficient. In a third evaluated measurement, synchronization was done with an external cable, yielding results near the CramerRao lower bound for distance estimates.
The angle estimation generally performed more reliable, but showed systematic errors for indoor localization, which could be attributed to reflections being dominant over line of sight components.
Furthermore, a mathematical model of the signal processing in the hardware, the channel, received signals and estimation of the distance and angle was formulated.
This mathematical model was implemented and used with data from the measurements, yielding estimates for the two parameters.
Lastly, focus shifted on a statistical evaluation of the results, comparing them to theoretical lower limits of accuracy imposed by the CramerRao lower bound.
Results showed that for two evaluated measurements the performance of distance estimation was subpar, because the (unwired) synchronization between base station and mobile station was insufficient. In a third evaluated measurement, synchronization was done with an external cable, yielding results near the CramerRao lower bound for distance estimates.
The angle estimation generally performed more reliable, but showed systematic errors for indoor localization, which could be attributed to reflections being dominant over line of sight components.
Translated title of the contribution  Lokalisierung mittels eines Massive MIMO Software Defined Radio 

Original language  English 
Qualification  Master of Science 
Awarding Institution 

Supervisors/Advisors 

Publication status  Published  2020 