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Mobile Edge Computing Aided Cell-Free Massive MIMO Networks
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DOI：10.1109/TMC.2022.3232510.png)
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摘要
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A mobile edge computing (MEC) aided cell-free massive MIMO network is investigated in this paper that aims at optimizing the task offloading process from the wireless devices to the MEC server. Partial computation offloading strategies are designed that aim at optimizing either the aggregated latency or the energy consumption by considering the finite computational capability of the MEC server and assuming that the tasks are subject to a maximum latency constraint. The proposed optimization approach considers the joint optimization of both the per-task offloading ratio and the corresponding computational resources allocated to the tasks at the MEC server. This optimization is performed by taking into account the computing capabilities of both the wireless devices and the MEC server and both the UL and DL spectral efficiencies provided by the cell-free massive MIMO network. The proposed optimization problems are shown to be convex and, inspired by the well-known waterfilling algorithm, optimal solutions based on low-complexity iterative algorithms are devised. Extensive numerical results reveal the potential of the proposed MEC-enabled cell-free massive MIMO network.
Keyword:
Task analysis
Massive MIMO
Servers
Optimization
Wireless communication
Energy consumption
Resource management
Cell-free massive MIMO
mobile edge computing
task offloading
optimization
期刊
IF:
9.2
论文数:
5.8K
被引数:
1.8W
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