Open AccessJoint resource optimisation in cell‐free massive MIMO with low‐resolution ADCs
Author(s) -
Zhang Yao,
Zhou Meng,
Cao Haotong,
Liu Yun,
Yang Longxiang,
Zhu Hongbo
Publication year - 2020
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2019.0865
Subject(s) - telecommunications link , lagrange multiplier , computer science , mimo , converters , mathematical optimization , backhaul (telecommunications) , convex optimization , bit error rate , relay , transmitter power output , geometric programming , beamforming , wireless , regular polygon , power (physics) , algorithm , decoding methods , channel (broadcasting) , mathematics , telecommunications , physics , geometry , transmitter , quantum mechanics
In this study, the uplink performance of cell‐free massive multi‐input multi‐output (mMIMO) system with multi‐antenna access points (APs) and users is investigated, assuming low‐resolution analogue–digital converters (ADCs) are employed at the APs. By exploiting the additive quantisation noise model, a tight closed‐form rate expression is derived. This tractable finding characterises the impacts of the multi‐antenna APs and users, the imperfect quantisation error and the channel estimation error. In order to maximise the uplink sum‐rate, a joint quantisation bit and power control problem is formulated, subjecting to the backhaul capacity and each user power constraints. The original resource optimisation problem is non‐convex and it is decomposed into two sub‐problems, namely quantisation bit design and power allocation problem, to alleviate the difficulties. In particular, the resultant two sub‐problems can be efficiently determined by utilising the Lagrange Multiplier and sequential convex approximation methods, respectively. Finally, numerical simulations are presented to examine the analytical findings and evaluate the effectiveness of the proposed algorithm.