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Partial Cooperative Zero-Forcing Decoding for Uplink Cell-Free Massive MIMO

delete2022-06-15
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PRE
AI
X
Xinhua Wang *
J
Julian Cheng
C
Chao Zhai
A
Alexei Ashikhmin
DOI:10.1109/JIOT.2021.3122026delete
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摘要

摘要

En 中文
We propose a partial cooperative zero-forcing (PCZF) decoding scheme for the uplink cell-free massive MIMO system, wherein the neighboring access points (APs) around each user equipment (UE) share the channel state information (CSI) and jointly suppress the interference using the zero-forcing technique. Using asymptotic analysis, we derive a closed-form asymptotic expression for a lower bound on the achievable rates. Considering the unique and complex form of the achievable rates, we propose power control schemes according to two criteria. The first criterion is to maximize the minimum achievable rate. For this criterion, we propose a target-SINR-tracking (TST)-based bisection algorithm. Since the power control update functions are standard interference functions, the TST-based bisection method always converges to the optimal solution. The second criterion is to maximize the sum rate, for which we propose two power control algorithms: 1) randomization and scaling algorithm (RSA) and 2) fractional programming algorithm (FPA). In each iteration of the RAS algorithm, we first exploit the randomization technique to transform the sum-rate maximization problem into a series of power minimization problems, and then improve the sum rate by scaling. In the FP algorithm, we derive a lower bound on the sum rate, and then propose an iterative approach based on the Lagrangian dual transform and fractional programming to maximize the sum-rate lower bound. Numerical results validate the theoretical analysis and verify the efficiency of the proposed power control algorithms.
Keyword:
Decoding
Power control
Channel estimation
Antennas
Interference
Uplink
Programming
Cell-free (CF) massive MIMO (mMIMO)
fractional programming
partial cooperative zero-forcing (PCZF) decoding
power control
target-SINR-tracking (TST)

期刊

IEEE Internet of Things Journal 封面图
IEEE Internet of Things Journal
IF:
8.9
论文数:
1.4W
被引数:
7.8W

机构

Q
Qingdao University
学者数:
3.1W
论文数: 2.1W
被引数: 3.7W
S
shandong university
学者数:
9.5W
论文数: 6.4W
被引数: 94
N
nokia corporation
学者数:
1.8K
论文数: 1.5K
被引数: 1
U
University of British Columbia
学者数:
7.0W
论文数: 6.1W
被引数: 8.6W
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