Savannah: Efficient mmWave Baseband Processing with Minimal and Heterogeneous Resources

5G new radio (NR) employs frequency range 2 (FR2) in the millimeter-wave (mmWave) bands, which employs a much shorter slot duration compared to FR1 (sub-7 GHz) systems and, therefore, poses significant challenges for softwarized baseband processing in virtualized radio access networks (vRANs). Existing systems supporting software baseband processing focus on enabling (massive) multiple-input and multiple-output (MIMO) using multi-core edge server(s). These solutions may fail to meet the more stringent processing deadline in FR2 or require more intensive computational resources. In this paper, we present Savannah, an efficient mmWave baseband processing framework using minimal and heterogeneous computing resources including CPU and eASIC. Savannah addresses the challenges associated with baseband processing in FR2 by applying techniques for vectorizing matrix operations and memory access patterns, supporting heterogeneous computation via offloading LDPC decoding to an eASIC, and enabling single-core operation. We show that Savannah, using a single CPU core and the ACC100 accelerator, can support a 2×2 MIMO link with 100 MHz bandwidth, yielding a data rate of up to 487 Mbps.