Cell Coverage Optimization for the Multicell Massive MIMO Uplink

Shi Jin, Jue Wang, Qiang Sun, Michail Matthaiou, Xiqi Gao

Research output: Contribution to journalArticlepeer-review

436 Downloads (Pure)

Abstract

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, cell coverage optimization can become a promising technique which 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 be mainly 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 shaped cells and uniformly distributed users, we derive an analytical lower bound of the ergodic throughput in the objective cell, based on which, 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 sectoral shaped cells and non-uniformly 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 one-dimensional 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.
Original languageEnglish
Number of pages14
JournalIEEE Transactions on Vehicular Technology
Early online date24 Dec 2014
DOIs
Publication statusEarly online date - 24 Dec 2014

Fingerprint

Dive into the research topics of 'Cell Coverage Optimization for the Multicell Massive MIMO Uplink'. Together they form a unique fingerprint.

Cite this