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UAV-Based Cell-Free Massive MIMO: Joint Placement and Power Optimization under Fronthaul Capacity Limitations

Neetu R. R, Ozan Alp Topal, Özlem Tuğfe Demir, Emil Björnson, Cicek Cavdar, Gourab Ghatak, Vivek Ashok Bohara

TL;DR

This work addresses UAV-based cell-free mMIMO under wireless fronthaul capacity constraints. It introduces a joint UAV-AP activation and power-allocation framework under two fronthaul functional splits (Option 7.2 and Option 8) and compares mmWave versus sub-6 GHz fronthaul. A new fronthaul model is developed and solved via mixed binary second-order cone programming to achieve max-min SINR fairness and total UAV-AP power minimization, using LMMSE/L-MMSE processing for access. Results show that the 7.2 split reduces required fronthaul bandwidth and increases UE SINR by enabling more UAV-APs, while mmWave fronthaul offers higher capacity and can reduce UAV power, highlighting a trade-off between fronthaul load, SINR, and energy efficiency.

Abstract

We consider a cell-free massive multiple-input multiple-output (mMIMO) network, where unmanned aerial vehicles (UAVs) equipped with multiple antennas serve as distributed UAV-access points (UAV-APs). These UAV-APs provide seamless coverage by jointly serving user equipments (UEs) with out predefined cell boundaries. However, high-capacity wireless networks face significant challenges due to fronthaul limitations in UAV-assisted architectures. This letter proposes a novel UAV-based cell-free mMIMO framework that leverages distributed UAV-APs to serve UEs while addressing the capacity constraints of wireless fronthaul links. We evaluate functional split Options 7.2 and 8 for the fronthaul links, aiming to maximize the minimum signal-to-interference-plus-noise ratio (SINR) among the UEs and minimize the power consumption by optimizing the transmit powers of UAV-APs and selectively activating them. Our analysis compares sub-6 GHz and millimeter wave (mmWave) bands for the fronthaul, showing that mmWave achieves superior SINR with lower power consumption, particularly under Option 8. Additionally, we determine the minimum fronthaul bandwidth required to activate a single UAV-AP under different split options.

UAV-Based Cell-Free Massive MIMO: Joint Placement and Power Optimization under Fronthaul Capacity Limitations

TL;DR

This work addresses UAV-based cell-free mMIMO under wireless fronthaul capacity constraints. It introduces a joint UAV-AP activation and power-allocation framework under two fronthaul functional splits (Option 7.2 and Option 8) and compares mmWave versus sub-6 GHz fronthaul. A new fronthaul model is developed and solved via mixed binary second-order cone programming to achieve max-min SINR fairness and total UAV-AP power minimization, using LMMSE/L-MMSE processing for access. Results show that the 7.2 split reduces required fronthaul bandwidth and increases UE SINR by enabling more UAV-APs, while mmWave fronthaul offers higher capacity and can reduce UAV power, highlighting a trade-off between fronthaul load, SINR, and energy efficiency.

Abstract

We consider a cell-free massive multiple-input multiple-output (mMIMO) network, where unmanned aerial vehicles (UAVs) equipped with multiple antennas serve as distributed UAV-access points (UAV-APs). These UAV-APs provide seamless coverage by jointly serving user equipments (UEs) with out predefined cell boundaries. However, high-capacity wireless networks face significant challenges due to fronthaul limitations in UAV-assisted architectures. This letter proposes a novel UAV-based cell-free mMIMO framework that leverages distributed UAV-APs to serve UEs while addressing the capacity constraints of wireless fronthaul links. We evaluate functional split Options 7.2 and 8 for the fronthaul links, aiming to maximize the minimum signal-to-interference-plus-noise ratio (SINR) among the UEs and minimize the power consumption by optimizing the transmit powers of UAV-APs and selectively activating them. Our analysis compares sub-6 GHz and millimeter wave (mmWave) bands for the fronthaul, showing that mmWave achieves superior SINR with lower power consumption, particularly under Option 8. Additionally, we determine the minimum fronthaul bandwidth required to activate a single UAV-AP under different split options.

Paper Structure

This paper contains 10 sections, 14 equations, 1 figure.

Table of Contents

  1. Introduction
  2. System Model
  3. Wireless Fronthaul
  4. mmWave channel
  5. sub-6 GHz
  6. Cell-free Access
  7. Max-Min Fairness
  8. Total UAV-AP Power Minimization
  9. Numerical Results and Discussion
  10. Conclusion

Figures (1)

  • Figure 1: a) Number of fronthaul antennas versus the fronthaul bandwidth to activate one UAV-AP for Options 8 and 7.2. b) Number of fronthaul antennas versus the SINR at the UE with fronthaul bandwidth $B_F=500$ MHz for mmWave, $B_F=150$ MHz for sub-6 GHz for Options 8 and 7.2. c) Total power consumption versus SINR requirement with $B_F=500$ MHz, $N_c= 1024$ for mmWave, $B_F=150$ MHz, $N_c= 64$ for sub-6 GHz, for Options 8 and 7.2. d) Comparison for max-min fairness optimization and power minimization for different options with maximized SINR requirement.