Joint Signal Detection for Low-Altitude Aerial Cell-Free Networks With Wireless Fronthaul: Framework, Analysis, and Optimization

In this paper, we investigate the uplink joint signal detection for low-altitude aerial cell-free (CF) networks, where each flying access point (AP) locally processes the received signals and then forwards these information to a central processing unit (CPU) for the final detection. However, unlike terrestrial CF networks that typically adopt optic fiber fronthaul links, wireless fronthaul in aerial CF networks connecting flying APs with the CPU will significantly affect the communication performance, due to the practically limited fronthaul capacity. Therefore, we adopt a realistic channel model for wireless fronthaul links, which experience Rician fading and are shared among the flying APs through a combination of frequency division multiple access (FDMA) and space division multiple access (SDMA) protocol. Taking into account the imperfect and capacity-limited wireless fronthaul, we propose a joint uplink signal detection framework, where the local processing matrix at APs and the central detector at the CPU are designed based on the long-term statistical channel state information (CSI) by leveraging the operator-valued free probability theory. This approach significantly reduces the need for frequent, high-capacity signaling exchanges between APs and the CPU. Numerical results demonstrate the accuracy and effectiveness of the proposed joint signal detection framework.