Decentralized Massive MIMO Uplink Signal Estimation by Binary Multistep Synthesis

While linear equalization schemes like zero forcing or minimum mean-square error achieve a near optimal uplink signal estimation performance in large-scale multi-user multiple-input multiple-output systems, the corresponding algorithms lean on centralized processing. To avoid disproportionate interconnect data rates due to the centralized signal estimation, performing a decentralized equalization can mitigate these effects. In this paper, we present a decentralized signal estimation architecture, which combines the ideas of existing decentralized architectures to (i) reduce the overall latency of the signal estimation and (ii) maintain a high data detection performance.