Joint Optimization of Wireless Fronthaul and Access Links in CRAN with a Massive MIMO Central Unit
Joint Optimization of Wireless Fronthaul and Access Links in CRAN with a Massive MIMO Central Unit
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DOI：
10.1109/icc45855.2022.9839160
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发表时间：
2022-05
期刊：
影响因子：
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通讯作者：
Yingjia Huang;A. Ikhlef
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文献类型：
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作者：
Yingjia Huang;A. Ikhlef
我们提出了一种新的下行链路云无线电接入网络(CRAN)结构，具有无线前端和接入链路，以及一个配备了非常大的天线阵的中央单元(CU)，以服务于多个多天线远程射电头(RRH)，这些RRH反过来服务于多个用户设备(UE)。在CU使用非常大的天线阵可以提高前端容量，从而提高整个网络的容量。我们建议通过联合优化CU处的功率分配、RRH处的预编码器和量化噪声协方差矩阵来最小化CU处的总发射功率和RRH处的总发射功率，使CU和RRH处的总发射功率受到CU和RRH处允许的最大功率和UE的速率约束的最小化。同时考虑了独立压缩方案和联合压缩方案。通过将非凸优化问题转化为半定松弛问题，提出了一种迭代算法，证明了该问题的解对原问题也是最优的。仿真结果表明，与两种基准方案相比，该系统的性能可以显著降低总发射功率。
We propose a new downlink cloud radio access network (CRAN) architecture with wireless fronthaul and access links and a central unit (CU) that is equipped with a very large antenna array to serve multiple multi-antenna remote radio heads (RRHs) that in turn serve a number of user equipments (UEs). The use of a very large antenna array at the CU allows to improve the fronthaul capacity leading to improved capacity of the whole network. We propose to minimize the total transmit power at the CU and RRHs subject to maximum powers allowed at the CU and RRHs and rate constraints of UEs via jointly optimizing the power allocation at the CU, the precoders at the RRHs, and the quantization noise covariance matrices. Both independent and joint compression schemes are considered. An iterative algorithm is proposed via reformulating the non-convex optimization problem as a semidefinite relaxation (SDR) problem of which the solution is proved to be also optimal for the original problem. Simulation results show that the performance of the proposed system can significantly decrease the total transmit power compared to two benchmark schemes.