Context-aware handover in mmWave 5G using UE's direction of pass

By 2020, the global mobile data traffic will reach 30.6 exabytes per month. Hence, microwave bands will become saturated and insufficient to deliver that increment of data. Millimeter wave (a.k.a. mmWave) is a promising band, from 30 to 300 GHz, to allocate that data. A drawback is the high attenuation in non-line-of-sight scenarios because the millimeter wavelengths are blocked by common obstacles. Opposite to Long Term Evolution (LTE) networks, which transmit in an isotropic manner, mmWave small base stations (SBS) have to transmit through directional antennas to increase the signal to noise ratio, reaching a radius up to 200 meters. Hence, hundreds of SBSs will be needed to cover large spaces, and as a consequence, a user equipment (UE) will perform several handover (HO) procedures in a short distance. This requires an algorithm to decrease the handover delay for increasing the UE quality of service. We propose a direction of pass detection algorithm which predicts the next base station that the UE will approach for a faster detection. Our low-complexity algorithm is based on a linear regression model which uniquely uses the detection of the UE as input information, avoiding power consuming functions such as accelerometer sensors and global positioning systems in battery-limited devices to provide additional data. Results returned a 64% and 60% prediction accuracy with low and high outage probability, respectively. Our prediction algorithm also reduces the HO delay when an exhaustive-search algorithm is implemented