Boroujerdi, Mahdi N and Abbasfar, Aliazam and Ghanbari, Mohammad (2019) Cell Free Massive MIMO with Limited Capacity Fronthaul. Wireless Personal Communications, 104 (2). pp. 633-648. DOI https://doi.org/10.1007/s11277-018-6038-1
Boroujerdi, Mahdi N and Abbasfar, Aliazam and Ghanbari, Mohammad (2019) Cell Free Massive MIMO with Limited Capacity Fronthaul. Wireless Personal Communications, 104 (2). pp. 633-648. DOI https://doi.org/10.1007/s11277-018-6038-1
Boroujerdi, Mahdi N and Abbasfar, Aliazam and Ghanbari, Mohammad (2019) Cell Free Massive MIMO with Limited Capacity Fronthaul. Wireless Personal Communications, 104 (2). pp. 633-648. DOI https://doi.org/10.1007/s11277-018-6038-1
Abstract
Massive MIMO has shown to be a promising candidate for the next generation of mobile communications 5G. Cell free massive MIMO is an implementation in which antennas are distributed throughout the coverage area and the whole area is considered as a single cell. Despite increasing spectral efficiency, cell free massive MIMO has some practical challenges. One challenge is the limited capacity of fronthaul links connecting antennas to the central unit. In this paper, the problem of power weight allocation for a cell free massive MIMO with limited capacity fronthaul links is formulated and solved. The precoded signals for all of the distributed antennas are calculated at the central unit. These signals are then compressed and sent through the limited capacity links to the antennas. Several scenarios are explored, including joint power weight allocation and compression, separate power weight allocation and compression, and no compression. Results show that for limited capacity fronthaul, including compression effect rather than ignoring it, can enhance the performance of power weight allocation considerably.
Item Type: | Article |
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Uncontrolled Keywords: | Massive MIMO; Fronthaul capacity; Limited capacity links; Fronthaul compression; Cellular communications |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 30 Apr 2019 12:43 |
Last Modified: | 30 Oct 2024 17:09 |
URI: | http://repository.essex.ac.uk/id/eprint/23954 |