Abstract:We introduce mathematical tools and fixed point algorithms for optimal statistical max-min power control in cellular and cell-less massive MIMO systems. Unlike previous studies that rely on the use-and-then-forget (UatF) lower bound on Shannon achievable (ergodic) rates, our proposed framework can deal with alternative bounds that explicitly consider perfect or imperfect channel state information (CSI) at the decoder. In doing so, we address limitations of UatF-based power control algorithms, which inherit the shortcomings of the UatF bound. For example, the UatF bound can be overly conservative: in extreme cases, under fully statistical (nonadaptive) beamforming in zero-mean channels, the UatF bound produces trivial (zero) rate bounds. It also lacks scale invariance: a realization-dependent random scaling of the beamformers can change the bound drastically. In contrast, our framework is compatible with information-theoretic bounds that do not suffer from the above drawbacks. We illustrate the framework by solving a max-min power control problem considering a standard bound that exploits instantaneous CSI at the decoder.
From: Renato L. G. Cavalcante [view email]
[v1]
Mon, 13 Oct 2025 16:26:32 UTC (143 KB)
[v2]
Wed, 29 Oct 2025 19:42:57 UTC (143 KB)
[v3]
Thu, 29 Jan 2026 12:06:45 UTC (140 KB)
[v4]
Mon, 7 Sep 2026 14:45:47 UTC (160 KB)
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