Joint Compression and Multiuser Equalization for Multi-Carrier Massive MIMO Systems With Decentralized Baseband Processing

Abstract

The decentralized baseband processing (DBP) architecture is recently proposed for massive MIMO systems to reduce the interconnection cost of fronthaul links and baseband (BB) computational complexity. This paper studies the uplink multiuser equalization (MUE) problem under the DBP architecture in a multi-carrier system. Specifically, we consider a linear compression-based MUE (LC-MUE) scheme where the distributed BB units first compress the received multi-carrier signals in the frequency domain and send dimension-reduced signals to a central unit for data equalization, leading to a multi-carrier joint compression 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 develop low-complexity algorithms, we propose two new algorithms. Specifically, the first algorithm is devised based on the block coordinated descent method and non-convex alternating direction method of multipliers, which can achieve a compelling equalization accuracy and meanwhile benefit a guaranteed convergence property. The second algorithm is heuristic but enjoys further reduced complexity, which first adopts the simple carrier-wise JCDE solution, followed by a succinct aggregation step to generate a high-quality shared compressor. Simulations show that our LC-MUE scheme and proposed algorithms can approach the centralized scheme but with notably reduced fronthaul cost.