BeamCIM: A Compute-In-Memory based Broadband Beamforming Accelerator using Linear Embedding

We propose a mixed-signal Compute-In-Memory (CIM) based beamforming accelerator (BeamCIM) that uses linear embedding to transform high-dimensional analog inputs to lower dimension digital features and perform digital beamforming using those features. We show that BeamCIM reduces both digitization (number of ADCs) and computation requirements while maintaining beamforming quality. Simulations in 28nm CMOS for a 256 input to 16 output beam system shows that proposed system achieves 19 x reduction in area and 14 x reduction in power compared to a baseline true time delay based digital implementation of a beamformer.