Sequential Processing Strategies in Fronthaul Constrained Cell-Free Massive MIMO Networks

In a cell-free massive MIMO (CFmMIMO) network with a daisy-chain fronthaul, the amount of information that each access point (AP) needs to communicate with the next AP in the chain is determined by the location of the AP in the sequential fronthaul. Therefore, we propose two sequential processing strategies to combat the adverse effect of fronthaul compression on the sum of users’ spectral efficiency (SE): 1) linearly increasing fronthaul capacity allocation among APs and 2) Two-Path users’ signal estimation. The two strategies show superior performance in terms of sum SE compared to the equal fronthaul capacity allocation and Single-Path sequential signal estimation.

💡 Research Summary

This paper investigates uplink signal processing in cell‑free massive MIMO (CF‑mMIMO) systems where the access points (APs) are connected by a daisy‑chain (sequential) fronthaul. In such a topology each AP refines the users’ signal estimate received from the previous AP, compresses the refined estimate, and forwards it to the next AP. Because the estimate at AP l contains the contributions of all preceding APs, the amount of information that must be sent grows with the AP index. When the fronthaul links have limited capacity, the required compression introduces quantization noise that accumulates along the chain and degrades the users’ spectral efficiency (SE).

To mitigate this effect the authors propose two complementary strategies.

1. Linearly increasing fronthaul capacity allocation (LF). The total fronthaul budget (R_T) (bits per uplink sample) is split among the L APs according to
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