# Integration of Directional Antennas in an RSS Fingerprinting-Based Indoor Localization System
## 1 Introduction
Independent of the inferring technique, the unpredictable temporal fluctuation of the RSS inside indoor buildings is one of the main issues that any RSS-based ILS encounters and which jeopardizes their robustness and maximum accuracy [16; 17]. These irregularities of the electromagnetic channel are produced by uncontrolled factors, such as interfering electric/electronic devices, people moving, open/closed doors, temperature/humidity variation as a function of the daytime/climatology and other dynamic phenomena [29; 30]. Due to these phenomena, in-building location estimation from RSS is a complex problem that is difficult to be engineered using classical mathematical methods. For this reason, recent works have tried to incorporate improvements to filter the RSS noise sources and finely tune the tag position by combining different techniques [31; 32; 33; 34; 35; 36; 37; 38], introducing additional sensor data (e.g., digital compass or pedometers [29; 31], accelerometers [36; 37; 38], _etc._), employing Kalman or particle swarm filters [32; 33; 34; 35] or improving the radio map quality [18; 19]. Nonetheless, it is interesting to note that RSS fingerprinting-based indoor localization techniques exploit the RSS variability, but from the spatial perspective, _i.e._, the greater the RSS changes along space, the more robust and the easier is the fingerprinting-matching task, as more dissimilar fingerprints arise at each possible tag location; hence, the higher the accuracy that can be achieved [16]. Indeed, this spatial variance can be interpreted as a negative effect, which increases the overall RSSI variance and degrades the localization performance, but this interpretation is not strictly right. The proper indoor channel complexity (mainly given by phenomena, such as non-line of sight (NLOS) multi-path effects because of reflections/refractions due to the building geometry, wall/floors, building material losses, _etc._) can be an advantageous property for these systems, as it increments this spatial variation in the RSS distribution compared to outdoors, where RSS decay is mainly predicted by the distance losses with respect to the source. In this paper, we study the employment of omnidirectional and directional antennas to improve the accuracy of an RSS fingerprinting-based ILS for room-level positioning. The hypothesis behind it is: the variance of the RSSI (in terms of space) could be increased by integrating suitably-positioned and -oriented directional antennas (more directive antennas introduce higher sensitivity/variance with space). Thus, increased spatial variability should create more dissimilarity between different locations (fingerprints); the radio map quality can be enhanced, as fingerprints will be more robust to noise (generated by the aforementioned dynamic phenomena) and, hence, more easily associated with the location. The rest of the paper is organized as follows. Related work is provided in Section 2. System operation concepts and architecture are introduced in Section 3. Section 4 describes the system deployment cycle, focusing on the description of the sensor network planning and calibration phases. Finally, Sections 5 and 6 discuss experimental test results and conclusions, respectively.