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Distributed Resource Allocation Optimization for User-Centric Cell-Free MIMO Networks
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DOI：10.1109/TWC.2021.3118303.png)
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Abstract
En 中文
We develop two distributed downlink resource allocation algorithms for user-centric, cell-free, spatially-distributed, multiple-input multiple-output (MIMO) networks. In such networks, each user is served by a subset of nearby transmitters that we call distributed units or DUs. The operation of the DUs in a region is controlled by a central unit (CU). Our first scheme is implemented at the DUs, while the second is implemented at the CUs controlling these DUs. We define a hybrid quality of service metric that enables distributed optimization of system resources in a proportional fair manner. Specifically, each of our algorithms performs user scheduling, beamforming, and power control while accounting for channel estimation errors. Importantly, our algorithm does not require information exchange amongst DUs (CUs) for the DU-distributed (CU-distributed) system, while also smoothly converging. Our results show that our CU-distributed system provides 1.3- to 1.8-fold network throughput compared to the DU-distributed system, with minor increases in complexity and front-haul load - and substantial gains over benchmark schemes like local zero-forcing. We also analyze the trade-offs provided by the CU-distributed system, hence highlighting the significance of deploying multiple CUs in user-centric cell-free networks.
Keywords:
Resource management
MIMO communication
Array signal processing
Scalability
Fading channels
Copper
Wireless communication
Distributed resource allocation
user scheduling
user-centric clustering
cell-free MIMO
cooperative cellular networks
distributed antenna system
scalable resource allocation
fairness
Journal
IF:
10.7
Papers:
1.3W
Citations:
5.3W