Proactive Low Level Mobility in Cellular Networks

Mobile users frequently face significant interruptions in transmission and reception during handovers from one Base Station (BS) to another, resulting in latencies that are incompatible with the stringent requirements of Ultra-Reliable Low Latency Communications (URLLC). To address this, 3GPP introduced a novel handover procedure, called Layer 1/Layer 2 Triggered Mobility (LTM), in Release 18. LTM uses lower level signaling to respond quicker to mobility events, bypassing the reconfiguration of higher layers while keeping modifications to the lower layers at a minimal level. This drastically reduces service interruptions during handovers, making them practically negligible. However, since LTM uses more frequent L1 measurements, it has a higher handover and ping-pong handover rates, as well as signaling overhead. In this work, we propose to incorporate future channel predictions in LTM to perform cell preparations and handover decisions with the goal of reducing signaling overhead and resource reservation. We focus on a controlled indoor scenario, where future user channel predictions are possible with a high accuracy. Our proactive algorithm reduces the cell preparation rate by 76 % and the handover rate by 72 %, without compromising the network sum throughput. Moreover, the resource reservation time at the target BS is reduced to nearly 0 ms.