qhjqhj00 sum-spectral-efficiency
Hybrid centralized-distributed precoding in fronthaul-constrained CF-mMIMO systems — Mobini et al. (2025) (arXiv:2510.12406, 2025)
What this evaluates
Evaluates the sum spectral efficiency of a hybrid centralized-distributed precoding scheme in fronthaul-constrained cell-free massive MIMO networks, comparing it against fully centralized and fully distributed baselines under varying fronthaul capacities and antenna configurations.
Datasets
- (no dataset; pure metric skill)
Metrics
sum spectral efficiency (sum SE)(primary) — range: other- Total achievable data rate across all served users, measured in bit/s/Hz. Computed as the sum of individual user spectral efficiencies over 2000 random user distribution samples.
Input / output format
Input: Network topology parameters (M APs, K users in 2x2 km²), fronthaul capacity limit (FH_max), antennas per AP (L), transmit power limits (500 mW pilot, 1 W data), noise power (-92 dBm), and channel models (path loss, large-scale fading).
Output: Average sum SE (bit/s/Hz) as a function of FH_max, L, or M, reported via simulation over 2000 samples.
Scoring recipe
def compute_sum_se(users, channels, precoding_scheme, fh_max):
total_se = 0.0
for _ in range(2000): # τ samples
# 1. Generate user locations & channel realizations
# 2. Determine user grouping & power allocation per scheme
# 3. Compute SINR per user based on precoding (ZF/Hybrid)
se_per_user = [compute_se(sinr) for sinr in sinrs]
total_se += sum(se_per_user)
return total_se / 2000
Common pitfalls
- Assuming increasing fronthaul capacity (FH_max) always improves distributed precoding performance; it is actually capped by the number of antennas per AP (L-1).
- Ignoring the trade-off where increasing antennas (L) improves macro-diversity but simultaneously increases fronthaul load, potentially reducing the number of centrally served users.
- Confusing the fronthaul capacity limit (FH_max) with the actual fronthaul usage metric (FH_m,pr) reported in complexity tables.
Evidence (verbatim from paper)
The proposed power allocation and user grouping solution, yields significant sum-SE performance gain against EPA and random user grouping. More specifically, the K-means-based user grouping provides a performance gain of 34%, while the K-means based user grouping together with the power allocation can provide a performance gain of 83% when FH_max=12 Gbps.
Citation
@misc{mobini2025hybridprecoding,
title={Hybrid centralized-distributed precoding in fronthaul-constrained CF-mMIMO systems},
author={Mobini et al. (2025)},
year={2025},
note={arXiv:2510.12406}
}
- arXiv: 2510.12406