Joint Link Adaptation and Resource Allocation for Uplink in 3GPP Machine-Type Communications

Enhanced Machine-Type Communications (eMTC) is a low-power wide-area network technology introduced by the 3
^rd
Generation Partnership Project (3GPP). The eMTC devices are of low cost and can operate in poor signal coverage areas. To ensure successful transmission in such scenarios, 3GPP has adopted the repetition of data over time. In 4G-LTE/5G-NR, the resource allocation and link adaptation are one-dimensional problems where the modulation and coding scheme (MCS) is either incremented or decremented over time. However, in eMTC, there exists a two-dimensional problem, as the base station can update either MCS or repetitions. Further, the base station has to consider the devices' limited transmit power while allocating resources in the uplink. An optimal selection of these values has a significant impact on the network capacity and the devices' battery power. Motivated by this, we present novel resource allocation, link adaptation, and scheduling algorithms for the eMTC uplink. We show that the proposed algorithms result in a suitable selection of resource blocks, MCS, repetition levels, and link adaptation. To reduce the computation load, we also propose a low-complexity sub-optimal scheduling algorithm. Through system-level simulations, we show that all the proposed algorithms significantly outperform the state-of-the-art algorithms.