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When a vehicle moves from one base station (BS) to another, a large number of on-board user equipments (UE) may simultaneously and individually perform a handover (HO) procedure, resulting in increased HO overheads. A mobile relay node (MRN), connected via a wireless backhaul to a donor base station (DBS), is deployed on the rooftop of a bus to improve the link quality and reduce the associated HO overhead via group mobility. However, at moderate to high speeds, the on-board UEs can still suffer from frequent HOs due to the MRN failing to HO to a new DBS using the legacy downlink measurement-based HO (DL-HO) method. As a consequence, the connection towards all associated mobile users will be lost which poses tight reliability requirements on the backhaul link to avoid becoming a single point of failure (SPoF). In order to improve the reliability during group handover, in this work, we propose an uplink reference signal (UL RS) based HO procedure (coined as UL-HO) for the MRN which relies on the existing sounding reference signal in long term evolution (LTE) /new radio (NR). In the proposed scheme, and unlike the legacy DL-HO procedure in LTE/NR, the measurement report (MeasReport) transmission is not required between MRN and the DBS, therefore the HO delay can be reduced, decreasing the SPoF chances and thus, uninterrupted services can be provided to on-board UEs. We investigate the gain in terms of HO rate, HO failure rate, ping-pong rate and power consumption (both at the UE and the BS). Performance evaluations demonstrate that the proposed UL-HO scheme outperforms the legacy DL-HO scheme in current cellular networks.

To the best of our knowledge, effective indoor positioning for the long term evolution (LTE) has not been addressed in the literature. In this paper, the uplink sounding reference signal (SRS), which contains timing and received signal strength (RSS) information, is exploited to achieve this task. Accordingly, an LTE based localization system using time-difference-of-arrival (TDOA) and fingerprint of RSS that operates in two steps is devised to meet the requirement of high-precision indoor positioning. In the first step, peak value detection is applied to the SRSs from spatially separated sensors to estimate the TDOAs, from which a coarse target location is computed with the use of least squares. Based on deep neural network, fingerprinting in a subarea containing the coarse solution is then performed to obtain the final position estimate. Due to the instability in the RSS values caused by non-line-of-sight and multipath propagation, we propose a novel extraction method to select reliable RSSs as input to the network. Experimental results show that our two-step localization system can provide an accuracy of sub-meter level. [ABSTRACT FROM AUTHOR]

In beyond 5G (B5G) indoor positioning time of arrival (TOA) positioning method is an important one. Base stations measure reference signals sent by terminals to calculate the TOA. The accuracy of position calculation is highly dependent on the TOA estimation resolution. This paper proposes a high-resolution TOA estimation algorithm based on Sounding Reference Signal (SRS) of 5G communication system. The algorithm achieves high resolution estimation by two steps. The Least Mean Square (LMS) adaptive filtering method is used as the first step to obtain the integer part of TOA, which is a coarse estimation of TOA. In the second step, we use weighted Generalized Cross-Correlation (GCC) algorithm to obtain the fractional part of TOA in frequency domain to get a more precise TOA estimation. Moreover, the stability of the estimated results is improved by the threshold value setting. The proposed algorithm is simulated in both Additive White Gaussian Noise (AWGN) and Rayleigh fading channels. The simulation results show that the TOA error achieves 0.56 m in AWGN and 0.96 m in Rayleigh fading channels for 80 % of test samples respectively. [ABSTRACT FROM AUTHOR]