Joint UL-DL Power Allocation for Massive MIMO URLLC IoT Networks: A Comparative Study of Different Pilot Patterns

Abstract

In this paper, we employ massive multiple-input and multiple-output (MIMO) technology to support multiple Internet-of-Things devices with ultra-reliability and low-latency communication (URLLC) industrial applications. Specifically, we first derive lower bounds (LBs) on the achievable uplink (UL) and downlink (DL) data rates under the finite blocklength (FBL) and pilot contamination, where each base station (BS) employs maximum-ratio transmission (MRT) in the DL and maximum-ratio combining (MRC) in the UL detection. In addition, the LB rates are derived for two types of pilot of the regular pilot (RP) and superimposed pilot (SP). We study joint UL-DL power allocation optimization where the objective is to maximize the UL-DL overall average weighted sum rate (WSR) for the systems individually with RP and SP schemes. We propose to employ successive convex approximation to transform the original problems into a series of geometric program problems. Then, an iterative algorithm is proposed to jointly optimize the UL and DL pilot and data payload power allocation. Simulation results are shown to compare the performances of the systems with RP and SP schemes for different settings. Simulation results also verify that the derived LB rates tightly match the corresponding ergodic rates and confirm the rapid convergence speed of the proposed iterative algorithms.