Stochastic Geometry-Based MCS Adaption Analysis for Uplink Cellular Networks

The link adaptation plays a crucial role in the fifth generation (5G) and future wireless networks, where adaptive modulation and coding (AMC) is vital for significantly increasing the data transmission rate and quality of service (QoS) by adjusting the modulation and coding scheme (MCS). In this work, we investigate the stochastic geometry-based MCS adaption for the uplink cellular networks with Poisson distributed base stations (BS) and user equipments (UE). We first define the conditional received rate by quantizing the channel quality, i.e., signal to interference ratio (SIR), using the sets of thresholds. Basically, higher SIR indicates better channel condition and applys higher order of modulation scheme, which leads to higher received rate. We then derive the framework of meta distribution on the conditional received rate, the spatially-average spectral efficiency (SE), and the variance of the SE. In addition, beta approximation and several bounds are presented to simplify the calculation of meta distribution. We validate the proposed framework by numerical simulations under different system parameters.