Fronthaul-Efficient Multiuser Equalization for Multi-Carrier Massive MIMO Systems with Decentralized Baseband Processing

The decentralized baseband processing (DBP) architecture is recently proposed for massive MIMO systems to reduce the inter-connection cost of fronthaul links and baseband (BB) computational complexity. Under DBP architectures, the multiuser equalization (MUE) problem has been studied, but most of the existing algorithms are designed for the single-carrier case or plagued by excessive fronthaul costs, limiting their practical applicability. To tackle these challenges, this paper focuses on a multi-carrier massive MIMO system using DBP architecture and considers a fronthaul-efficient linear compression-based MUE (LC-MUE) scheme. By the LC-MUE scheme, the distributed BB units first compress the received signals and send dimension-reduced signals to a central unit for data equalization, leading to a multi-carrier joint compressor and data equalization (MC-JCDE) design problem. The MC-JCDE problem is challenging to handle because in practice the compressor is shared across multiple subcarriers, which couples the subcarrier-wise equalizers and leads to a large-dimensional problem. To handle the problem in a low-complexity manner, we propose a new algorithm based on the block coordinated descent method and non-convex alternating direction method of multipliers. Numerical results show that our MC-JCDE scheme can approach the centralized scheme with significantly reduced fronthaul cost.