Cell coverage optimization for the multicell massive MIMO uplink
Artikel i vetenskaplig tidskrift, 2015

We investigate the cell coverage optimization problem for the massive multiple-input multiple-output (MIMO) uplink. By deploying tilt-adjustable antenna arrays at the base stations (BSs), cell coverage optimization can become a promising technique that is able to strike a compromise between covering cell-edge users and pilot contamination suppression.We formulate a detailed description of this optimization problem by maximizing the cell throughput,which is shown to bemainly determined by the user distribution within several key geometrical regions. Then, the formulated problem is applied to different example scenarios. For a network with hexagonal cells and uniformly distributed users, we derive an analytical lower bound of the ergodic throughput in the objective cell; based on this, it is shown that the optimal choice for the cell coverage should ensure that the coverage of different cells does not overlap. For a more generic network with sector- shaped cells and nonuniformly distributed users, we propose an analytical approximation of the ergodic throughput. After that, a practical coverage optimization algorithm is proposed, where the optimal solution can be easily obtained through a simple 1-D line searching within a confined searching region. Our numerical results show that the proposed coverage optimization method is able to greatly increase the system throughput in macrocells for the massive MIMO uplink transmission, compared with the traditional schemes where the cell coverage is fixed.

Massive multiple-input multipleoutput (MIMO)

Cell coverage

Pilot contamination



S. Jin

Southeast University

J. Wang

Singapore University of Technology and Design

Nantong University

Q. Sun

Nantong University

Michail Matthaiou

Chalmers, Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

X. Gao

Southeast University

IEEE Transactions on Vehicular Technology

0018-9545 (ISSN)

Vol. 64 5713-5727