WEB OF SCIENCE
SCOPUS
Small cell, mmWave, and massive Multi-Input Multi-Output (MIMO) technologies in 5G cellular networks becomes inevitable trend caused by killer applications such as holographic video which is traffic-intensive. In this paper, we study a sequential activation beam selection, user scheduling, and power allocation problem in a mmWave network with massive MIMO utilizing a physical layer preceding technique. We aim to maximize the time-Averaged utility of users with a time-Averaged transmit power constraint on top of the EdgeSON architecture, which takes advantage of both centralized and distributed characteristics. We decompose the original long-Term problem into two-Time scales in which solving the problem of choosing beam pattern is run at a slower time scale than solving user scheduling and power allocation. Then, to solve user scheduling and power allocation, we leverage the Lyapunov drift-plus-penalty framework which transforms an original long-Term average problem into per-slot modified sub-problems. Since provided per-slot problem to find a set of user scheduling and power allocation is known as NP-hard, we propose a low-complex and practical interference management algorithm, namely CRIM, by introducing two critical users with the highest interference channel gain in intra-BS and inter-BS respectively. Finally, via extensive simulations, we verify and compare the performance of the proposed algorithm and comparing algorithms in a real mmWave network environment. © 2022 IEEE.
더보기Department of Electrical Engineering and Computer Science